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The universal scaling relationship between an attribute and the size of a system is widespread in nature and society and is known as allometric growth. Previous studies have explained that the allometric growth exponent of single-source systems is uniquely determined by the dimension. However, the phenomenon that the exponent shows diversity in some systems, such as rivers, freight transportation and gasoline stations, lacks a reasonable explanation. In this paper, we hold the view that allometric growth may originate from efficient delivery from sources to transfer sites in a system and propose a multisource transportation network model that can explain diversified allometric growth exponents. We apply this model to some multisource systems, and the results show that our model successfully reproduces the diversity of the allometric growth exponent., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Transport and Planning

The universal scaling relationship between an attribute and the size of a system is widespread in nature and society and is known as allometric growth. Previous studies have explained that the allometric growth exponent of single-source systems is uniquely determined by the dimension. However, the phenomenon that the exponent shows diversity in some systems, such as rivers, freight transportation and gasoline stations, lacks a reasonable explanation. In this paper, we hold the view that allometric growth may originate from efficient delivery from sources to transfer sites in a system and propose a multisource transportation network model that can explain diversified allometric growth exponents. We apply this model to some multisource systems, and the results show that our model successfully reproduces the diversity of the allometric growth exponent.

In this paper, we aim at investigating various aspects of countries' behaviour during the coronavirus pandemic period. By means of a multiplex network, we simultaneously consider government responses based on COVID-19 infections, Stringency Index, international trade and international air mobility data, to detect clusters of countries that showed a similar reaction to the pandemic. We propose a new methodological approach based on the Estrada communicability for identifying communities on a multiplex network, based on a two-step optimization process. At first, we determine the optimal inter-layer weight between levels by minimizing a distance function. Hence, the optimal weight is used to detect the communities on each layer. Our findings show that this new approach to community detection on a multiplex network provides additional insights with respect to the same procedure performed on layers separately. Indeed, clusters in the multiplex network benefit from a higher cohesion, as they are detected taking into account the mutual influence of the other networks.

Epidemic spreading can be suppressed by the introduction of containment measures such as social distancing and lockdowns. Yet, when such measures are relaxed, new epidemic waves and infection cycles may occur. Here we explore this issue in compartmentalized epidemic models on graphs in presence of a feedback between the infection state of the population and the structure of its social network for the case of discontinuous control. We show that in random graphs the effect of containment measures is simply captured by a renormalization of the effective infection rate that accounts for the change in the branching ratio of the network. In our simple setting, a piece-wise mean-field approximation can be used to derive analytical formulae for the number of epidemic waves and their length. A variant of the model with imperfect information is used to model data of the recent COVID-19 epidemics in the Basque Country and Lombardy, where we estimate the extent of social network disruption during lockdowns and characterize the dynamical trajectories in the phase space.

Spatial networks are networks where nodes are located in a space equipped with a metric. Typically, the space is two-dimensional and until recently and traditionally, the metric that was usually considered was the Euclidean distance. In spatial networks, the cost of a link depends on the edge length, i.e. the distance between the nodes that define the edge. Hypothesizing that there is pressure to reduce the length of the edges of a network requires a null model, e.g. a random layout of the vertices of the network. Here we investigate the properties of the distribution of the sum of edge lengths in random linear arrangement of vertices, that has many applications in different fields. A random linear arrangement consists of an ordering of the elements of the nodes of a network being all possible orderings equally likely. The distance between two vertices is one plus the number of intermediate vertices in the ordering. Compact formulae for the 1st and 2nd moments about zero as well as the variance of the sum of edge lengths are obtained for arbitrary graphs and trees. We also analyze the evolution of that variance in Erdos–Rényi graphs and its scaling in uniformly random trees. Various developments and applications for future research are suggested., Peer Reviewed, Postprint (author's final draft)

We introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents, with prices determined by their own resource level and a couple of macroscopic parameters that emerge naturally from the analysis, akin to mean-field parameters in statistical mechanics. When resources are scarce prices rise sharply below a turning point that marks the disappearance of excess producers. To compare the model with real empirical data, we study the relationship between commodity prices and stock-to-use ratios in a range of commodities such as agricultural products and metals. By introducing an elasticity parameter to mitigate noise and long-term changes in commodities data, we confirm the trend of rising prices, provide evidence for turning points, and indicate yield points for less essential commodities.

We introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents, with prices determined by their own resource level and a couple of macroscopic parameters that emerge naturally from the analysis, akin to mean-field parameters in statistical mechanics. When resources are scarce prices rise sharply below a turning point that marks the disappearance of excess producers. To compare the model with real empirical data, we study the relationship between commodity prices and stock-to-use ratios in a range of commodities such as agricultural products and metals. By introducing an elasticity parameter to mitigate noise and long-term changes in commodities data, we confirm the trend of rising prices, provide evidence for turning points, and indicate yield points for less essential commodities.

This study considers the changing ideals of marriage during the 19th century as reflected in acollection of Swedish bourgeoisie love-letters from the 1870s. Through a combined quantitative andqualitative effort the goal is to establish how adherents to the relatively new ideal of marriage forthe sake of romantic love; thought, wrote and experienced the material aspects of marriage. It alsoaspires to shed light on how traditional family influence on the marital sphere survived the proposedshift in ideals.The study finds that family, economy and shared feelings were themes that dominated the letters.Individuals that adhered to the ideal of romantic love spent considerable time realizing the materialpre-requisites of marriage. This leads to a conclusion that marriage ideals and marriage practiceevolved at different paces. Family influence largely survived the change of ideals through paternalauthority, individual immersion in the family-dominated socio-economic network and aspirations ofthe young to retain the socio-economic status of their elders.

We introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents, with prices determined by their own resource level and a couple of macroscopic parameters that emerge naturally from the analysis, akin to mean-field parameters in statistical mechanics. When resources are scarce prices rise sharply below a turning point that marks the disappearance of excess producers. To compare the model with real empirical data, we study the relationship between commodity prices and stock-to-use ratios in a range of commodities such as agricultural products and metals. By introducing an elasticity parameter to mitigate noise and long-term changes in commodities data, we confirm the trend of rising prices, provide evidence for turning points, and indicate yield points for less essential commodities.

This study considers the changing ideals of marriage during the 19th century as reflected in acollection of Swedish bourgeoisie love-letters from the 1870s. Through a combined quantitative andqualitative effort the goal is to establish how adherents to the relatively new ideal of marriage forthe sake of romantic love; thought, wrote and experienced the material aspects of marriage. It alsoaspires to shed light on how traditional family influence on the marital sphere survived the proposedshift in ideals.The study finds that family, economy and shared feelings were themes that dominated the letters.Individuals that adhered to the ideal of romantic love spent considerable time realizing the materialpre-requisites of marriage. This leads to a conclusion that marriage ideals and marriage practiceevolved at different paces. Family influence largely survived the change of ideals through paternalauthority, individual immersion in the family-dominated socio-economic network and aspirations ofthe young to retain the socio-economic status of their elders.

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has addressed this issue by combining the physics of complex networks with a description of interactions in terms of evolutionary game theory. We here take this research a step further by introducing a most salient societal factor such as the individuals' preferences, a characteristic that is key to understanding much of the social phenomenology these days. We consider a heterogeneous, agent-based model in which agents interact strategically with their neighbors, but their preferences and payoffs for the possible actions differ. We study how such a heterogeneous network behaves under evolutionary dynamics and different strategic interactions, namely coordination games and best shot games. With this model we study the emergence of the equilibria predicted analytically in random graphs under best response dynamics, and we extend this test to unexplored contexts like proportional imitation and scale free networks. We show that some theoretically predicted equilibria do not arise in simulations with incomplete information, and we demonstrate the importance of the graph topology and the payoff function parameters for some games. Finally, we discuss our results with the available experimental evidence on coordination games, showing that our model agrees better with the experiment than standard economic theories, and draw hints as to how to maximize social efficiency in situations of conflicting preferences.

In this paper, we show that a comprehensive analysis of temporal network evolution requires to consider measures of non-structural changes, in addition to classical topological indicators. We employ a recently proposed measure of non-structural dynamics, together with other structural indicators, to analyze the time evolution of three subnetworks, extracted from the Italian corporate board network. Consistently with recent literature, we show that, to different extent, both structural and non-structural changes are present and must be accounted for, in order to get a satisfactory description of their temporal evolution.

Recently, the study of evolutionary games on networks has attracted great interest, focused mainly on the problem of the emergence of cooperation. A well studied framework for this problem is the Prisoner’s Dilemma game on fixed, evolving or growing networks. In this paper we present a complete picture of the behavior of another important social dilemma, the Stag Hunt game, under an evolutionary preferential attachment model, in which the network grows according to the dynamical states of the elements of the system. We observe the emergence of a scale-free and hierarchical organization of the strategies according to connectivity classes as a by-product of the diffusion of cooperation in the network. Depending on the parametrization of the game dynamics, we find a smooth transition from cooperation to defection and a polymorphic state with simultaneous presence of cooperator and defector hubs, which is very unusual in coordination games., Peer Reviewed, Postprint (author's final draft)

We analyze the anonymous communication patterns of 2.5 million customers of a Belgian mobile phone operator. Grouping customers by billing address, we build a social network of cities that consists of communications between 571 cities in Belgium. We show that inter-city communication intensity is characterized by a gravity model: the communication intensity between two cities is proportional to the product of their sizes divided by the square of their distance.