Evolution Of Behavior Research Articles

Models of animal coalitions and their implications for human evolution.

Social interaction is a prime driver for the evolution of animal behaviour. Dyadic interaction, in particular, has been the focus of intensive research on the evolution of mutualistic, altruistic, selfish or spiteful behaviours. Meanwhile, triadic interaction has been the minimal framework for the study of animal coalition as observed in some species of primates, as well as in carnivores and cetaceans, where two or more individuals act jointly against a third party in a competitive context. Previous mathematical models of animal coalition have either failed to explain the observed diversity in the configuration of coalition or presumed fine-tuned decision-making that may be unrealistic for non-human animals. To approach these issues, the present study develops a new model that is fairly simple, but still able to account for the observed diversity in animal coalitions. Analysis of the model specifies key parameters affecting the predicted types of coalition: the nature of the benefit being contested, the cost-to-benefit ratio associated with fighting and the synergistic effect in coalition formation. Additionally, the model is used to evaluate the social selection hypothesis, which claims that coalition formation induced social selection favouring reduced aggression and lower fighting abilities during human evolution.

The mechanical behavior and crack propagation mechanism evolution of heterogeneous C/HfC-SiC composites caused by extreme ablation environment exceeding 2300 °C

In this study, we conducted oxyacetylene ablation, followed by bending tests and comprehensive microstructural characterization, to investigate the mechanical behavior of C/HfC-SiC composites. The findings indicate a marked reduction in the flexural strength and fracture energy of ablated C/HfC-SiC composites, which decreased from 286.09 ± 17.56 MPa and 5.04 ± 0.27 mJ/mm2 to 190.97 ± 16.69 MPa and 3.80 ± 0.29 mJ/mm2, respectively. Notably, the fracture energy retention rate (75.40 %) of the composites exceeds the flexural strength retention rate (66.75 %). Based on the microstructure of cracks and energy release rate criterion, the failure process and crack propagation mechanism were analyzed. The ablation process was found to diminish the shear strength of the fiber-matrix interface, facilitating mechanical behaviors such as fiber debonding, slipping, and pull-out. Additionally, oxidative damage induces the simultaneous propagation of multiple cracks, thereby increasing energy consumption during the bending. These plastic mechanical behaviors not only increase the failure displacement but also enhance the plastic characteristics of the composites, allowing it to maintain higher flexural strength (from 69.3 MPa to 108.3 MPa) and fracture energy (from approximately 2.71 mJ/mm2 to 4.26 mJ/mm2) after failure (at the double failure displacement).

A multi-stage game framework for new route promotion: Behavioral strategy and dynamic evolution of shippers, carriers, and governments

New freight routes are being planned and emerging globally, but often rely on government subsidies to enhance their competitiveness during the initial promotional phase. This study proposes a multi-stage game framework to explore the influence mechanism of behavioral strategies among three stakeholders: shipper, carrier, and government. Based on the assessment of shippers’ route choice preferences, we examine the dynamic evolution of carriers’ and governments’ behavioral strategies in the practical context of bounded rationality and dynamic learning. We theoretically derive the evolutionary paths and stable outcomes of dynamic systems across eight scenarios encompassing all the possible practical values to be taken, which provide broader and more valuable decision support for new route promotion. Finally, the feasibility and validity of the proposed model are verified by the actual case of the New International Land-Sea Trade Corridor. The findings indicate that government subsidies are not always effective and provide a precise subsidy range that can incentivize carriers to switch to the new route. Moreover, the study clarifies the impact of key factors such as subsidy, tax, route reliability, transportation time, and time value of cargo on the promotion of new routes through numerical simulation, and provides feasible management recommendations for government and route operations.

High temperature tensile creep behavior and microstructure evolution of Ti60 alloy rolled sheet

In this work, the high temperature tensile creep test of 2mm Ti60 alloy rolled sheet was carried out, and the creep behavior and microstructure evolution were studied. The initial microstructure of the 2mm Ti60 alloy rolled sheet is mainly composed of primary α phase and secondary α phase, and there are many dislocations and dynamic recrystallization (DRX) inside the rolled sheet. According to Norton-Bailey law, the creep stress exponent at 600 °C is calculated to be 3.6, and creep activation energy at 200MPa is calculated to be 286.4kJ/mol. It implies that the creep mechanism of the rolled sheet includes dislocation slip and dislocation climb. The initial Ti60 alloy rolled sheet has the {0001}<10-10>α texture. Stretching along the RD makes the texture direction gradually change from B-type (<0001>//ND) to T-type (<0001>//TD). Whether it is the B-type texture or T-type texture, the (0001) plane of the α phase always exhibits a basal texture state parallel to the tensile stress direction, contributing a good tensile creep property of this alloy sheet.

Influence of temperature and strain rate on deformation behaviour, microstructure, and microtexture evolution of primary-β worked Ti-4Al-2.5V-1.5Fe-0.25O alloy during sub-transus processing

Influence of temperature and strain rate on deformation behaviour, microstructure, and microtexture evolution of primary-β worked Ti-4Al-2.5V-1.5Fe-0.25O alloy during sub-transus processing

Comprehensive study of hot deformation behavior and microstructure evolution of solutioned AA7050 alloy based on HFQ process

Comprehensive study of hot deformation behavior and microstructure evolution of solutioned AA7050 alloy based on HFQ process

Analysis of health recommendations using longitudinal quality of life data: QoL@TbA - A transformer-based approach.

Objective: Health recommendation systems suggest behavioral modifications to improve quality of life. However, current approaches do not facilitate the generation or examination of such recommendations considering the multifeature longitudinal evolution of behaviors. This paper proposes the use of a deep learning transformer-based model that allows the analysis of recommendations for behavior changes. Methods: We adapted a prediction approach, namely Behavior Sequence Transformer (BST), which analyzes temporal human routines and patterns, generating inductive outcomes. The evaluation relied on a case study that employed the behavioral history and profile of the English Longitudinal Study of Ageing (ELSA) participants (n = 2682), predicting their psychological mood (normal, pre-depressed, depressed) according to input recommendations for behavioral changes. Root mean squared error (RMSE) and learning curves were used to track the recommendation accuracy evolution and possible overfitting problems. Results: Experiments demonstrated lower RMSE values for the multifeature model (0.28/0.03) when compared to its single-feature versions (marital status, 0.59/0.001), (high pressure, 0.357/0.04), (diabetes, 0.36/0.01), (sleep quality, 0.57/0.02), (level of physical activity, 0.57/0.01). Conclusions: The results demonstrate the architecture's capability to analyze multifeatured longitudinal data, supporting the generation of suggestions for concurrent modifications across multiple input features. Moreover, these suggestions align with findings in specialized literature.

How to subsidize ecotourism in a tourism supply chain? An examination with a three-party evolutionary game model

Nowadays, to promote ecotourism, governments have introduced a series of incentive policies. This study considers the impacts of government subsidy on ecotourism development and builds a three-party evolutionary game model involving the government, tourism enterprises and downstream consumers. The game strategies and behavior evolution of each party have been studied. Three conditional evolutionarily stable strategy points are obtained. The authors also investigate the final evolutionary results, influencing factors and optimization paths of various parties. Some interesting conclusions are drawn. First, in the introduction stage of ecotourism, government subsidies are effective at boosting ecotourism. However, when the market reaches stabilization, enterprises and consumers might not choose ecotourism even with government subsidies. Second, during the evolutionary process, the government subsidies probability exhibits two trends of an initial increase followed by a subsequent fall to zero, or ongoing subsidies. Finally, the initial state of the government, enterprises and consumers has a greater impact on the stability outcomes. When enterprises' and consumers' initial preferences for ecotourism grow, the government's willingness to subsidize diminishes significantly. Meanwhile, subsidies for consumers work better than those for enterprises.

Deformation behaviour and microstructure evolution of Ti-2.3Al-2.6Zr alloy in the temperature range of 700–1000 °C

Ti-2.3Al-2.6Zr alloy was hot deformed at temperatures from 700 to 1000 °C and strain rates from 10−2 −30 s−1. The uniaxial compression tests were conducted in vacuum to a true strain of 1 for this alloy. Strain rate sensitivity was calculated from the true stress- true strain data and plotted as contour plots to generate the strain rate sensitivity map. The hot working condition of this model α-Ti alloy was optimized by using the strain rate sensitivity map. The optimized hot workability domains were identified for α-phase as (a) 780–900 °C at strain rate of 10−2 to 0.3 s−1 and (b) 825–900 °C at strain rate of 3–30 s−1. The domain of hot processing condition for β-phase was found at 930–1000 °C for all strain rates. In α-phase domain the strain rate sensitivity was about 0.3, the stress exponent was 4.3 and the activation energy for deformation was 285 kJ mol−1 whereas in β-phase domain the strain rate sensitivity was about 0.34, the stress exponent was 5.3 and the activation energy for deformation was 210 kJ mol−1. These deformation parameters suggest the deformation process to be a dislocation based mechanism. Samples deformed within the high strain rate sensitivity domains showed microstructural features of dynamic recrystallization. In α-phase fine equiaxed recrystallized grains with high angle boundaries were observed. Deformation at 900 °C and 0.01 s−1 resulted in fully recrystallized equiaxed grains in the α-phase, whereas the β-phase showed lamellar grain morphology with very fine recrystallized grains.

Unveiling the Microstructural Features during Compression of a High-Modulus Mg-15Gd-8Y-6Al-0.3Mn Alloy Reinforced by a Large Volume of Al2RE Phases

Magnesium alloys with a high volume fraction of secondary phases exhibit inferior formability. Therefore, investigating their thermal deformation characteristics is critical for optimizing thermal processing techniques. In this work, isothermal compression experiments were performed on a Mg-15Gd-8Y-6Al-0.3Mn alloy with an elastic modulus of 51.3 GPa with a substantial volume of aluminum-rare earth (Al2RE) phases. The rheological behavior and microstructural evolution of the material were systematically investigated at varying temperatures (350–500 °C) and strain rates (0.001–1.000 s−1). The calculated thermal processing diagram indicates that the unstable region gradually enlarges with increased strain, and all unstable regions appear within the high-strain-rate, low-temperature domain. The ideal thermal processing range of the alloy is 350–500 °C at strain rates ranging from 0.001 to 0.016 s−1. Particle-stimulated nucleation and discontinuous dynamic recrystallization are both verified to be responsible for the recrystallized microstructure of the alloy. The recrystallized grains exhibit a relatively random crystallographic orientation. As recrystallization proceeds, the texture gradually transitions from a typical [0001] texture in the compression direction to a random texture accompanied by decreased texture intensity. This work sheds new light on the thermo-mechanical processing of high-modulus Mg alloys, which could help design suitable processing techniques for related materials.

Stochastic Evolutionary Analysis of an Aerial Attack–Defense Game in Uncertain Environments

Aiming at the problem of random environment interference in the process of strategy interaction and the behavioral evolution of an aerial attack–defense game, this paper considers the influence of the difference in the performance and value between both game players in terms of strategy evolution; explores the randomness of the complex battlefield environment, the uncertainty of the behavioral state of game players, and the limitations of the emergent situation; constructs a mathematical model of the stochastic evolution of an aerial-coordinated attack–defense game in uncertain environments; and studies the stability of the strategy interaction and behavioral decision-making process of both players of the aerial attack–defense game. Simulation results show that many factors of the performance and value between both game players have a greater impact on the strategy evolution trend in both game players, which not only causes changes in the results of the strategy selection but also affects the rate of strategy evolution for the game players. In addition, random environmental factors cause a certain degree of interference to the strategy evolution process of the game players, which usually accelerates the game players’ strategy evolution rate and greatly affects the evolution process of the game players’ strategy. This study can provide a theoretical basis and feasible reference for improving mission decision-making, response mechanisms, and system modeling of an aerial attack–defense game, which has important theoretical value and practical significance.

AI-Lorenz: A physics-data-driven framework for Black-Box and Gray-Box identification of chaotic systems with symbolic regression

Discovering mathematical models that characterize the observed behavior of dynamical systems remains a major challenge, especially for systems in a chaotic regime, due to their sensitive dependence on initial conditions and the complex non-linear interactions within the system. The challenge is even greater when the physics underlying such systems is not yet understood, and scientific inquiry must solely rely on empirical data. Despite advancements such as the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm, which has shown success in identifying chaotic systems with reasonable accuracy, challenges remain in dealing with noise, sparse data, and the need for models that generalize well across different chaotic systems. Driven by the need to fill this gap, we develop a framework named AI-Lorenz that learns mathematical expressions modeling complex dynamical behaviors by identifying differential equations from noisy and sparse observable data. We train a physics-informed neural network (PINN) with the eXtreme Theory of Functional Connections (X-TFC) algorithm by using data and known physics (when available) to learn the dynamics of a system, its rate of change in time, and missing model terms, which are used as input for a symbolic regression algorithm (PySR) to autonomously distill the explicit mathematical terms. This, in turn, enables us to predict the future evolution of the dynamical behavior. The performance of this framework is validated by recovering the right-hand sides and unknown terms of certain complex, chaotic systems, such as the well-known Lorenz system, a six-dimensional hyperchaotic system, the non-autonomous Sprott chaotic system, and the slow-fast Duffing system, and comparing them with their known analytical expressions and state-of-the-art regression and system identification methods.

Evolution of user behaviour on social media during 2018 road safety movement in Bangladesh

Evolution of user behaviour on social media during 2018 road safety movement in Bangladesh

The tripartite evolutionary game of enterprises' green production strategy with government supervision and people participation

Government supervision and people participation play vital roles in enterprises' green production strategy, but few studies have considered the strategy choices behind government supervision and people's participation. This study contended that whether an enterprise adopts the green production strategy is influenced not only by its responsible attitude facing social responsibility but also by the following two factors, the intensity of government supervision and whether people choose to participate in supervision or not when facing the enterprise adopting the green production strategy or not. We constructed a tripartite evolutionary game model to explore the behavioral evolution rules and evolutionary stability strategies of government supervision, people participation, and enterprises' green production. Then we employed numerical simulation to analyze how various factors influence the strategy selection of the government, people, and enterprises. The results show that if the utility values of government supervision and people participation are greater than 0, the enterprises will adopt the green production strategy. The system stability is affected by a synergistic relationship between participation cost, reputation benefit, and government subsidies, and an incremental relationship between enterprises' green production benefit, government subsidies, people's reported bonus, and enterprises' green production cost. This study provides a new theoretical perspective for research on government supervision, people participation, and enterprises' green production strategy, and the results provide important references for improving the enterprises' green production and urban environmental management.

The behavior evolution and case simulation of water rights trading in water transfer projects

ABSTRACT Due to the difference in the economic and social development level of each area of the water transfer project, there will be a lack of water resources in some areas, while water resources in some other areas have a surplus, resulting in the imbalance of water resources. However, the transaction willingness of both parties is not strong, and the seller has the psychology of “reluctant to sell”. The buyer hopes to make free water allocation through the government. The paper analyzes the feasibility and influence of solving the imbalance of water resources in water transfer projects through the market mechanism by the evolutionary game approach. The water right transaction between Zhengzhou and Nanyang in the middle route of the South-to-North Water Transfer Project is taken as a case for simulation. The study shows t: the lower the marginal return of the water resources in the water-rich area is, the higher the water-scarce area is, the easier to promote water rights trading; the higher the environmental and social benefits for both parties are, the easier the water rights trading; the lower the transaction cost of both parties is, the easier the water rights trading.

Multiscale framework-based crystal plasticity modeling and texture evolution of the deformation behavior of AISI 304 stainless steel microtubes manufactured through 3D-FBF technology

The grain size often influences the precision and quality of products manufactured by microforming at the microscale. Macroscale finite element modeling (FEM) cannot accurately predict nonuniform deformation and microstructural evolution at the microscale. In addition, the microscale FEM is challenging for forming processes with complex loading boundary conditions. Thus, in this study, a multiscale framework-based CPFEM is proposed to study the deformation behavior of microtubes manufactured through the 3D-FBF process. The acquired results show that significant nonuniform deformation is caused by greater geometric dimensions and smaller grain sizes, which increase the bending radius of microtubes at the macro level. In addition, a larger offset leads to higher flow stress, larger lattice rotation angles, and consequently, a larger bending radius for the microtube, and grain orientation also influences bending deformation, with easily deformable grain orientations leading to greater stress distribution within the grains.

Flow behavior and microstructural evolution of Al-1.2Mg-2.4Si-1.2Cu-0.6Mn alloy during hot compression

Thermal compression tests were conducted on Al-1.2Mg-2.4Si-1.2Cu-0.6Mn alloys with process parameters including deformation temperatures ranging from 400°C to 550°C and strain rates ranging from 0.05 s⁻¹ to 1 s⁻¹. The hot working properties of aluminum alloys were evaluated with intrinsic equations and machining diagrams. The results show that the processing safety zones of the alloy are 425–450℃ and 0.05–0.1 s−1, 450–475℃ and 0.1 s−1-0.5 s−1, and 475–500℃ and 0.5 s−1. The microstructure of the aluminum alloy following hot pressing was investigated through the use of optical microscopy (OM), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and backscattered electron diffraction (EBSD). When the deformation temperature of the alloy is below 450°C, the alloy organization exhibits a greater prevalence of inhomogeneous defects, which manifest as coarser granular regions in the micro-morphology. Upon reaching a deformation temperature of above 525°C, the deformed alloy organization exhibits an evident thermal cracking phenomenon. At the same temperature, an increase in strain rate is accompanied by a decrease in the Mg2Si phase and an increase in the precipitation of the Al(Fe,Mn)Si eutectic phase. Furthermore, the precipitated phase tends to become coarser. The presence of certain Mn-containing nanoparticle dispersions can impede the migration of subgrain grain boundaries, while simultaneously pinning dislocations and accelerating the generation of dislocation entanglement. This also can serve to inhibit the coarsening of the grains to some extent.

Dynamic recrystallization mechanisms and microstructure evolution of a novel Al-Zn-Mg-Cu-Zr alloy by isothermal compression

The dynamic recrystallization (DRX) behavior and microstructure evolution of a novel Al-Zn-Mg-Cu-Zr alloy was investigated by isothermal compression tests at temperature of 350–470 °C and strain rate of 0.0001–1 s−1. The results showed that the flow behavior revealed typical dynamic recovery (DRV) characteristics at a high strain rate (1 s−1), while exhibited a DRX shape when the strain rate decreased. The critical strains (εc) of the DRX decreased with the decrease of strain rate or the increase of deformation temperature. A low temperature was conductive to precipitation behavior, the coarse precipitates and dispersed Al3Zr particles would pin the dislocations and substructures, which inhibit the DRX process. The DRX mechanism of the Al-Zn-Mg-Cu-Zr alloy was dominated by continuous dynamic recrystallization (CDRX) and discontinuous dynamic recrystallization (DDRX) during the hot deformation process, upon increasing the temperature and decreasing the strain rate, there was a transition point of DRX mechanism from DDRX to CDRX. Moreover, the linear relationship between the Zener-Hollomon (Z) parameter and DRX grain size was established for the further exploration of the transition of the dominant DRX mechanism.

Nanocrystallization and precipitation behavior evolution of AZ80 magnesium alloy during multi-directional compression

In response to the growing demand for high-performance magnesium alloys in the aerospace and transportation industries, researchers conducted a study on the AZ80 magnesium alloy. The primary objective was to achieve a nanocrystalline structure in the alloy through severe plastic deformation using low-strain multi-directional compression at room temperature. Subsequently, an aging treatment was performed to induce the transformation of the structure into a stable state. The study aimed to investigate the morphology and mode of the second phase precipitation in the magnesium alloy after undergoing severe plastic deformation. The research findings revealed that the application of multi-directional and multi-pass compression during room temperature deformation of the magnesium alloy effectively prevented instability and fracture. Moreover, this process facilitated the accumulation of larger true strain. As the number of compression passes increased, deformation twins became increasingly denser, particularly in the intersecting areas. Consequently, ultrafine high-angle grain structures were preferentially formed in these regions. Furthermore, the number of fine-grained areas gradually increased with each deformation pass. After ΣΔε 5.12, the grain size was refined to a range of 100–200 nm. Additionally, the aging treatment following severe plastic deformation brought about a significant change in the traditional lamellar precipitation mode of the second phase Mg17Al12 in the magnesium alloy. Instead, spherical precipitation occurred.

GoFish: a foray into open-source, aquatic behavioral automation.

As the most species-rich vertebrate group, fish provide an array of opportunities to investigate the link between ecological interactions and the evolution of behavior and cognition, yet, as an animal model, they are relatively underutilized in studies of comparative cognition. To address this gap, we developed a fully automated platform for behavioral experiments in aquatic species, GoFish. GoFish includes closed-loop control of task contingencies using real-time video tracking, presentation of visual stimuli, automatic food reward dispensers, and built-in data acquisition. The hardware is relatively inexpensive and accessible, and all software components of the platform are open-source. GoFish facilitates experimental automation, allowing for customization of high-throughput protocols and the efficient acquisition of rich behavioral data. We hope this platform proves to be a useful tool for the research community, facilitating refined, reproducible behavioral experiments on aquatic species in comparative cognition, behavioral ecology, and neuroscience.