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Hundreds of years after its creation, the game of chess is still widely played worldwide. Opening Theory is one of the pillars of chess and requires years of study to be mastered. Here we exploit the "wisdom of the crowd" in an online chess platform to answer questions that, traditionally, only chess experts could tackle. We first define the relatedness network of chess openings that quantifies how similar two openings are to play. In this network, we spot communities of nodes corresponding to the most common opening choices and their mutual relationships, information which is hard to obtain from the existing classification of openings. Moreover, we use the relatedness network to forecast the future openings players will start to play and we back-test these predictions, obtaining performances considerably higher than those of a random predictor. Finally, we use the Economic Fitness and Complexity algorithm to measure how difficult to play openings are and how skilled in openings players are. This study not only gives a new perspective on chess analysis but also opens the possibility of suggesting personalized opening recommendations using complex network theory.

For decades the number of scientific publications has been rapidly increasing, effectively out-dating knowledge at a tremendous rate. Only few scientific milestones remain relevant and continuously attract citations. Here we quantify how long scientific work remains being utilized, how long it takes before today's work is forgotten, and how milestone papers differ from those forgotten. To answer these questions, we study the complete temporal citation network of all American Physical Society journals. We quantify the probability of attracting citations for individual publications based on age and the number of citations they have received in the past. We capture both aspects, the forgetting and the tendency to cite already popular works, in a microscopic generative model for the dynamics of scientific citation networks. We find that the probability of citing a specific paper declines with age as a power law with an exponent of $\alpha \sim -1.4$. Whenever a paper in its early years can be characterized by a scaling exponent above a critical value, $\alpha_c$, the paper is likely to become "ever-lasting". We validate the model with out-of-sample predictions, with an accuracy of up to 90% (AUC $\sim 0.9$). The model also allows us to estimate an expected citation landscape of the future, predicting that 95% of papers cited in 2050 have yet to be published. The exponential growth of articles, combined with a power-law type of forgetting and papers receiving fewer and fewer citations on average, suggests a worrying tendency toward information overload and raises concerns about scientific publishing's long-term sustainability., Comment: 11 pages, 4 figures

In response to the COVID-19 pandemic, governments have implemented a wide range of non-pharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020., Measurement(s) time at medical intervention • medical intervention Technology Type(s) digital curation • content analysis strategy of existing information sources Factor Type(s) non-pharmaceutical intervention • date Sample Characteristic - Location global Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12668792

Taylor&rsquo, s law quantifies the scaling properties of the fluctuations of the number of innovations occurring in open systems. Urn-based modeling schemes have already proven to be effective in modeling this complex behaviour. Here, we present analytical estimations of Taylor&rsquo, s law exponents in such models, by leveraging on their representation in terms of triangular urn models. We also highlight the correspondence of these models with Poisson&ndash, Dirichlet processes and demonstrate how a non-trivial Taylor&rsquo, s law exponent is a kind of universal feature in systems related to human activities. We base this result on the analysis of four collections of data generated by human activity: (i) written language (from a Gutenberg corpus), (ii) an online music website (Last.fm), (iii) Twitter hashtags, (iv) an online collaborative tagging system (Del.icio.us). While Taylor&rsquo, s law observed in the last two datasets agrees with the plain model predictions, we need to introduce a generalization to fully characterize the behaviour of the first two datasets, where temporal correlations are possibly more relevant. We suggest that Taylor&rsquo, s law is a fundamental complement to Zipf&rsquo, s and Heaps&rsquo, laws in unveiling the complex dynamical processes underlying the evolution of systems featuring innovation.

Rediscovering a new function for something can be just as important as the discovery itself. In 1982, Stephen Jay Gould and Elisabeth Vrba named this phenomenon Exaptation to describe a radical shift in the function of a specific trait during biological evolution. While exaptation is thought to be a fundamental mechanism for generating adaptive innovations, diversity, and sophisticated features, relatively little effort has been made to quantify exaptation outside the topic of biological evolution. We think that this concept provides a useful framework for characterising the emergence of innovations in science. This chapter explores the notion that exaptation arises from the usage of scientific ideas in domains other than the area that they were originally applied to. In particular, we adopt a normalised entropy and an inverse participation ratio as observables that reveal and quantify the concept of exaptation. We identify distinctive patterns of exaptation and expose specific examples of papers that display those patterns. Our approach represents a first step towards the quantification of exaptation phenomena in the context of scientific evolution.

Railways are a key infrastructure for any modern country. The reliability and resilience of this peculiar transportation system may be challenged by different shocks such as disruptions, strikes and adverse weather conditions. These events compromise the correct functioning of the system and trigger the spreading of delays into the railway network on a daily basis. Despite their importance, a general theoretical understanding of the underlying causes of these disruptions is still lacking. In this work, we analyse the Italian and German railway networks by leveraging on the train schedules and actual delay data retrieved during the year 2015. We use {these} data to infer simple statistical laws ruling the emergence of localized delays in different areas of the network and we model the spreading of these delays throughout the network by exploiting a framework inspired by epidemic spreading models. Our model offers a fast and easy tool for the preliminary assessment of the {effectiveness of} traffic handling policies, and of the railway {network} criticalities., Comment: 32 pages (with appendix), 28 Figures (with appendix), 2 Tables

We present a new metric estimating fitness of countries and complexity of products by exploiting a non-linear non-homogeneous map applied to the publicly available information on the goods exported by a country. The non homogeneous terms guarantee both convergence and stability. After a suitable rescaling of the relevant quantities, the non homogeneous terms are eventually set to zero so that this new metric is parameter free. This new map almost reproduces the results of the original homogeneous metrics already defined in literature and allows for an approximate analytic solution in case of actual binarized matrices based on the Revealed Comparative Advantage (RCA) indicator. This solution is connected with a new quantity describing the neighborhood of nodes in bipartite graphs, representing in this work the relations between countries and exported products. Moreover, we define the new indicator of country net-efficiency quantifying how a country efficiently invests in capabilities able to generate innovative complex high quality products. Eventually, we demonstrate analytically the local convergence of the algorithm involved., 12 pages, 8 figures

Recently, social phenomena have received a lot of attention not only from social scientists, but also from physicists, mathematicians and computer scientists, in the emerging interdisciplinary field of complex system science. Opinion dynamics is one of the processes studied, since opinions are the drivers of human behaviour, and play a crucial role in many global challenges that our complex world and societies are facing: global financial crises, global pandemics, growth of cities, urbanisation and migration patterns, and last but not least important, climate change and environmental sustainability and protection. Opinion formation is a complex process affected by the interplay of different elements, including the individual predisposition, the influence of positive and negative peer interaction (social networks playing a crucial role in this respect), the information each individual is exposed to, and many others. Several models inspired from those in use in physics have been developed to encompass many of these elements, and to allow for the identification of the mechanisms involved in the opinion formation process and the understanding of their role, with the practical aim of simulating opinion formation and spreading under various conditions. These modelling schemes range from binary simple models such as the voter model, to multi-dimensional continuous approaches. Here, we provide a review of recent methods, focusing on models employing both peer interaction and external information, and emphasising the role that less studied mechanisms, such as disagreement, has in driving the opinion dynamics. Due to the important role that external information (mainly in the form of mass media broadcast) can have in enhancing awareness of social issues, a special emphasis will be devoted to study different forms it can take, investigating their effectiveness in driving the opinion formation at the population level. The review shows that, although a large number of approaches exist, some mechanisms such as the effect of multiple external information sources could largely benefit from further studies. Additionally, model validation with real data, which are starting to become available, is still largely lacking and should in our opinion be the main ambition of future investigations.

Creative industries constantly strive for fame and popularity. Though highly desirable, popularity is not the only achievement artistic creations might ever acquire. Leaving a longstanding mark in the global production and influencing future works is an even more important achievement, usually acknowledged by experts and scholars. ‘Significant’ or ‘influential’ works are not always well known to the public or have sometimes been long forgotten by the vast majority. In this paper, we focus on the duality between what is successful and what is significant in the musical context. To this end, we consider a user-generated set of tags collected through an online music platform, whose evolving co-occurrence network mirrors the growing conceptual space underlying music production. We define a set of general metrics aiming at characterizing music albums throughout history, and their relationships with the overall musical production. We show how these metrics allow to classify albums according to their current popularity or their belonging to expert-made lists of important albums. In this way, we provide the scientific community and the public at large with quantitative tools to tell apart popular albums from culturally or aesthetically relevant artworks. The generality of the methodology presented here lends itself to be used in all those fields where innovation and creativity are in play.

This book introduces and reviews recent advances in the field in a comprehensive and non-technical way by focusing on the potential of emerging citizen-science and social-computation frameworks, coupled with the latest theoretical and modeling tools developed by physicists, mathematicians, computer and social scientists to analyse, interpret and visualize complex data sets. There is overwhelming evidence that the current organisation of our economies and societies is seriously damaging biological ecosystems and human living conditions in the short term, with potentially catastrophic effects in the long term. The need to re-organise the daily activities with the greatest impact energy consumption, transport, housing towards a more efficient and sustainable development model has recently been raised in the public debate on several global, environmental issues. Above all, this requires the mismatch between global, societal and individual needs to be addressed. Recent advances in Information and Communication Technologies (ICT) can trigger important transitions at the individual and collective level to achieve this aim. Based on the findings of the collaborative research network EveryAware the following developments among the emerging ICT technologies are discussed in depth in this volume: Participatory sensing where ICT development is pushed to the level where it can support informed action at the hyperlocal scale, providing capabilities for environmental monitoring, data aggregation and mining, as well as information presentation and sharing. Web gaming, social computing and internet-mediated collaboration where the Web will continue to acquire the status of an infrastructure for social computing, allowing users cognitive abilities to be coordinated in online communities, and steering the collective action towards predefined goals. Collective awareness and decision-making where the access to both personal and community data, collected by users, processed with suitable analysis tools, and re-presented in an appropriate format by usable communication interfaces leads to a bottom-up development of collective social strategies.

The emergence of awareness is deeply connected to the process of learning. In fact, by learning that high sound levels may harm one's health, that noise levels that we estimate as innocuous may be dangerous, that there exist an alternative path we can walk to go to work and minimize our exposure to air pollution, etc., citizens will be able to understand the environment around them and act consequently to go toward a more sustainable world.

In the last few years the Web has progressively acquired the status of an infrastructure for social computation that allows researchers to coordinate the cognitive abilities of human agents, so to steer the collective user activity towards predefined goals. This general trend is also triggering the adoption of web-games as an alternative laboratory to run experiments in the social sciences and whenever the contribution of human beings can be effectively used for research purposes. Web-games introduce a playful aspect in scientific experiments with the result of increasing participation of people and of keeping their attention steady in time. The aim of this chapter is to suggest a general purpose web-based platform scheme for web-gaming and social computation. This platform will simplify the realization of web-games and will act as a repository of different scientific experiments, thus realizing a sort of showcase that stimulates users' curiosity and helps researchers in recruiting volunteers. A platform built by following these criteria has been developed within the EveryAware project, the Experimental Tribe (XTribe) platform, which is operational and ready to be used. Finally, a sample web-game hosted by the XTribe platform will be presented with the aim of reporting the results, in terms of participation and motivation, of two different player recruiting strategies.

The understanding and the characterization of individual mobility patterns in urban environments is important in order to improve liveability and planning of big cities. In relatively recent times, the availability of data regarding human movements have fostered the emergence of a new branch of social studies, with the aim to unveil and study those patterns thanks to data collected by means of geolocalization technologies. In this paper we analyze a large dataset of GPS tracks of cars collected in Rome (Italy). Dividing the drivers in classes according to the number of trips they perform in a day, we show that the sequence of the traveled space connecting two consecutive stops shows a precise behavior so that the shortest trips are performed at the middle of the sequence, when the longest occur at the beginning and at the end when drivers head back home. We show that this behavior is consistent with the idea of an optimization process in which the total travel time is minimized, under the effect of spatial constraints so that the starting points is on the border of the space in which the dynamics takes place.

Novelties are part of our daily lives. We constantly adopt new technologies, conceive new ideas, meet new people, and experiment with new situations. Occasionally, we as individual, in a complicated cognitive and sometimes fortuitous process, come up with something that is not only new to us, but to our entire society so that what is a personal novelty can turn into an innovation at a global level. Innovations occur throughout social, biological, and technological systems and, though we perceive them as a very natural ingredient of our human experience, little is known about the processes determining their emergence. Still the statistical occurrence of innovations shows striking regularities that represent a starting point to get a deeper insight in the whole phenomenology. This paper represents a small step in that direction, focusing on reviewing the scientific attempts to effectively model the emergence of the new and its regularities, with an emphasis on more recent contributions: from the plain Simon's model tracing back to the 1950s, to the newest model of Polya's urn with triggering of one novelty by another. What seems to be key in the successful modeling schemes proposed so far is the idea of looking at evolution as a path in a complex space, physical, conceptual, biological, and technological, whose structure and topology get continuously reshaped and expanded by the occurrence of the new. Mathematically, it is very interesting to look at the consequences of the interplay between the "actual" and the "possible" and this is the aim of this short review.

The dynamics of political votes has been widely studied, both for its practical interest and as a paradigm of the dynamics of mass opinions and collective phenomena, where theoretical predictions can be easily tested. However, the vote outcome is often influenced by many factors beyond the bare opinion on the candidate, and in most cases it is bound to a single preference. The voter perception of the political space is still to be elucidated. We here propose a web experiment (laPENSOcosì) where we explicitly investigate participants' opinions on political entities (parties, coalitions, individual candidates) of the Italian political scene. As a main result, we show that the political perception follows a Weber-Fechner-like law, i.e., when ranking political entities according to the user expressed preferences, the perceived distance of the user from a given entity scales as the logarithm of this rank.

none 13 The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments. h Martin Becker;Saverio Caminiti;Donato Fiorella;Louise Francis;Pietro Gravino;Mordechai (Muki) Haklay;Andreas Hotho;Vittorio Loreto;Juergen Mueller;Ferdinando Ricchiuti;Vito D. P. Servedio;Alina Sirbu;Francesca Tria Martin Becker;Saverio Caminiti;Donato Fiorella;Louise Francis;Pietro Gravino;Mordechai (Muki) Haklay;Andreas Hotho;Vittorio Loreto;Juergen Mueller;Ferdinando Ricchiuti;Vito D. P. Servedio;Alina Sirbu;Francesca Tria

Zipf&rsquo, s, Heaps&rsquo, and Taylor&rsquo, s laws are ubiquitous in many different systems where innovation processes are at play. Together, they represent a compelling set of stylized facts regarding the overall statistics, the innovation rate and the scaling of fluctuations for systems as diverse as written texts and cities, ecological systems and stock markets. Many modeling schemes have been proposed in literature to explain those laws, but only recently a modeling framework has been introduced that accounts for the emergence of those laws without deducing the emergence of one of the laws from the others or without ad hoc assumptions. This modeling framework is based on the concept of adjacent possible space and its key feature of being dynamically restructured while its boundaries get explored, i.e., conditional to the occurrence of novel events. Here, we illustrate this approach and show how this simple modeling framework, instantiated through a modified P&oacute, lya&rsquo, s urn model, is able to reproduce Zipf&rsquo, s laws within a unique self-consistent scheme. In addition, the same modeling scheme embraces other less common evolutionary laws (Hoppe&rsquo, s model and Dirichlet processes) as particular cases.

Opinion formation is an important element of social dynamics. It has been widely studied in the last years with tools from physics, mathematics and computer science. Here, a continuous model of opinion dynamics for multiple possible choices is analysed. Its main features are the inclusion of disagreement and possibility of modulating information, both from one and multiple sources. The interest is in identifying the effect of the initial cohesion of the population, the interplay between cohesion and information extremism, and the effect of using multiple sources of information that can influence the system. Final consensus, especially with external information, depends highly on these factors, as numerical simulations show. When no information is present, consensus or segregation is determined by the initial cohesion of the population. Interestingly, when only one source of information is present, consensus can be obtained, in general, only when this is extremely mild, i.e. there is not a single opinion strongly promoted, or in the special case of a large initial cohesion and low information exposure. On the contrary, when multiple information sources are allowed, consensus can emerge with an information source even when this is not extremely mild, i.e. it carries a strong message, for a large range of initial conditions., 20 pages, 11 figures

Air Transportation represents a very interesting example of a complex techno-social system whose importance has considerably grown in time and whose management requires a careful understanding of the subtle interplay between technological infrastructure and human behavior. Despite the competition with other transportation systems, a growth of air traffic is still foreseen in Europe for the next years. The increase of traffic load could bring the current Air Traffic Network above its capacity limits so that safety standards and performances might not be guaranteed anymore. Lacking the possibility of a direct investigation of this scenario, we resort to computer simulations in order to quantify the disruptive potential of an increase in traffic load. To this end we model the Air Transportation system as a complex dynamical network of flights controlled by humans who have to solve potentially dangerous conflicts by redirecting aircraft trajectories. The model is driven and validated through historical data of flight schedules in a European national airspace. While correctly reproducing actual statistics of the Air Transportation system, e.g., the distribution of delays, the model allows for theoretical predictions. Upon an increase of the traffic load injected in the system, the model predicts a transition from a phase in which all conflicts can be successfully resolved, to a phase in which many conflicts cannot be resolved anymore. We highlight how the current flight density of the Air Transportation system is well below the transition, provided that controllers make use of a special re-routing procedure. While the congestion transition displays a universal scaling behavior, its threshold depends on the conflict solving strategy adopted. Finally, the generality of the modeling scheme introduced makes it a flexible general tool to simulate and control Air Transportation systems in realistic and synthetic scenarios.

The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution., Comment: 17 pages, 6 figures, 1 supplementary file

Each sphere of knowledge and information could be depicted as a complex mesh of correlated items. By properly exploiting these connections, innovative and more efficient navigation strategies could be defined, possibly leading to a faster learning process and an enduring retention of information. In this work we investigate how the topological structure embedding the items to be learned can affect the efficiency of the learning dynamics. To this end we introduce a general class of algorithms that simulate the exploration of knowledge/information networks standing on well-established findings on educational scheduling, namely the spacing and lag effects. While constructing their learning schedules, individuals move along connections, periodically revisiting some concepts and sometimes jumping on very distant ones. In order to investigate the effect of networked information structures on the proposed learning dynamics we focused both on synthetic and real-world graphs such as subsections of Wikipedia and word-association graphs. We highlight the existence of optimal topological structures for the simulated learning dynamics whose efficiency is affected by the balance between hubs and the least connected items. Interestingly, the real-world graphs we considered lead naturally to almost optimal learning performances.

The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy) district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.

Contact languages are born out of the non-trivial interaction of two (or more) parent languages. Nowadays, the enhanced possibility of mobility and communication allows for a strong mixing of languages and cultures, thus raising the issue of whether there are any pure languages or cultures that are unaffected by contact with others. As with bacteria or viruses in biological evolution, the evolution of languages is marked by horizontal transmission; but to date no reliable quantitative tools to investigate these phenomena have been available. An interesting and well documented example of contact language is the emergence of creole languages, which originated in the contacts of European colonists and slaves during the 17th and 18th centuries in exogenous plantation colonies of especially the Atlantic and Indian Ocean. Here, we focus on the emergence of creole languages to demonstrate a dynamical process that mimics the process of creole formation in American and Caribbean plantation ecologies. Inspired by the Naming Game (NG), our modeling scheme incorporates demographic information about the colonial population in the framework of a non-trivial interaction network including three populations: Europeans, Mulattos/Creoles, and Bozal slaves. We show how this sole information makes it possible to discriminate territories that produced modern creoles from those that did not, with a surprising accuracy. The generality of our approach provides valuable insights for further studies on the emergence of languages in contact ecologies as well as to test specific hypotheses about the peopling and the population structures of the relevant territories. We submit that these tools could be relevant to addressing problems related to contact phenomena in many cultural domains: e.g., emergence of dialects, language competition and hybridization, globalization phenomena.

The electronic structure and magnetic properties of NpCoGa5 are investigated in the framework of relativistic density functional theory in the local spin density approximation (LSDA) with and without orbital polarization (OP) corrections. A detailed analysis of the Fermi surface is presented. Comparison of the calculated angular dependence of the de Haas-van Alphen frequencies with recent experimental data shows that LSDA reproduces the main features of the Fermi surface topology, while the spin and orbital moments of NpCoGa5 are less well described. The inclusion of OP corrections leads to a very good agreement between calculated and measured de Haas-van Alphen frequencies, but does not yield a significant improvement of the calculated magnetic properties. We predict that NpCoGa5 shows an intrinsic GMR effect at moderate magnetic field.

Photoemission experiments and theoretical calculations for the system Au-stepped W(1 1 2), have been done at submonolayer coverage region ranging from 0.1 to 0.9 monolayers, for different sample orientations relative to the photon polarization, i.e. parallel and perpendicular to the steps direction. Valence-band photoemission spectra of the Au/W(1 1 2) system demonstrate sharp angular dependent features at 4.5 and 0.3 eV binding energies when the photon polarization is parallel to the steps direction. Density functional theory calculations were performed for the Au/W(1 1 2) system with monolayer and half monolayer Au coverages in order to assign the origin of these features.

Erosion by flowing water is one of the major forces shaping the surface of Earth. Studies in the last decade have shown, in particular, that the drainage region of rivers, where water is collected, exhibits scale invariant features characterized by exponents that are the same for rivers around the world. Here we show that from the data obtained by the MOLA altimeter of the Mars Global Surveyor one can perform the same analysis for mountain sides on Mars. We then show that in some regions fluid erosion might have played a role in the present martian landscape.

We compare full potential LDA band calculations of the Fermi surfaces areas and band masses of MgB2 and ZrB2 previously reported and new dHvA data. Discrepancies in areas in MgB2 can be removed by a small shift of σ bands relative to π bands. Comparison of effective masses lead to orbit averaged el-ph coupling constants λσ=1.3 and λπ=0.5, whereas for ZrB2 only weak el-ph coupling with λ

In recent times, the research field of language dynamics has focused on the investigation of language evolution, dividing the work in three evolutive steps, according to the level of complexity: lexicon, categories and grammar. The Naming Game is a simple model capable of accounting for the emergence of a lexicon, intended as the set of words through which objects are named. We introduce a stochastic modification of the Naming Game model with the aim of characterizing the emergence of a new language as the result of the interaction of agents. We fix the initial phase by splitting the population in two sets speaking either language A or B. Whenever the result of the interaction of two individuals results in an agent able to speak both A and B, we introduce a finite probability that this state turns into a new idiom C, so to mimic a sort of hybridization process. We study the system in the space of parameters defining the interaction, and show that the proposed model displays a rich variety of behaviours, despite the simple mean field topology of interactions., 12 pages, 10 figures, presented at IWSOS 2013 Palma de Mallorca, the final publication will be available at LNCS http://www.springer.com/lncs

One new thing often leads to another. Such correlated novelties are a familiar part of daily life. They are also thought to be fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called "expanding the adjacent possible". The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (analogous to Heaps' law) and for the probability distribution on the space explored (analogous to Zipf's law), as well as signatures of the hypothesized process by which one novelty sets the stage for another. We test these predictions on four data sets of human activity: the edit events of Wikipedia pages, the emergence of tags in annotation systems, the sequence of words in texts, and listening to new songs in online music catalogues. By quantifying the dynamics of correlated novelties, our results provide a starting point for a deeper understanding of the ever-expanding adjacent possible and its role in biological, linguistic, cultural, and technological evolution.

Variations of the photoionization cross section of valence states as a function of interatomic distance are studied by means of atomic and solid-state density functional approaches and compared with photoemission data. In contrast to the free atom case, a series of Cooper minima is found for 4d, 5d, and 5f states in Pd, Ag, Au, and U metals. The discovered fundamental phenomenon is of high importance for the correct interpretation of photoemission data.

It is shown that the La $5p$ photoemission (PE) spectra consist of a superposition of two final states reflecting predominantly ${5p}^{5}{4f}^{0}$ and ${5p}^{5}{4f}^{1}$ character. In contrast to La $3d$ spectra, the ${4f}^{1}$-derived component appears at the high-binding-energy side of the ${4f}^{0}$-derived emission due to a weaker interaction between the photohole and the $4f$ electron. This splitting into two components is crucial for the quantitative understanding of the resonant behavior of the $5p$ states at the $4\stackrel{\ensuremath{\rightarrow}}{d}4f$ excitation threshold. In addition to the participator decay channel usually considered for the description of the resonant PE, a spectator decay channel must be taken into account that leads particularly to an enhancement of the ${4f}^{1}$ originating emission. The contributions of the spectator transitions are particularly important in the range of the so-called preresonances, e.g., at the ${}^{3}{P}_{1}$ and ${}^{3}{D}_{1}$ excitation thresholds.

A full application of relativistic spin-density functional theory in noncollinear treatment of the exchange and correlation field is given to open-shell atoms and ions of the carbon group. It is shown that the influence of noncollinearity is small as compared with self-interaction corrections. Unfortunately, the defect of the local spin-density approximation not to yield a source-free exchange and correlation field increases in noncollinear treatment. © 1999 John Wiley & Sons, Inc. J Comput Chem 20: 23–30, 1999

Nowadays Nuclear Magnetic Resonance diffusion (dNMR) measurements of water molecules in heterogeneous systems have broad applications in material science, biophysics and medicine. Up to now, microstructural rearrangement in media has been experimentally investigated by studying the diffusion coefficient (D(t)) behavior in the tortuosity limit. However, this method is not able to describe structural disorder and transitions in complex systems. Here we show that, according to the continuous time random walk framework, the dNMR measurable parameter alpha, quantifying the anomalous regime of D(t), provides a quantitative characterization of structural disorder and structural transition in heterogeneous systems. To demonstrate this, we compare a measurements obtained in random packed monodisperse micro-spheres with Molecular Dynamics simulations of disordered porous media and 3D Monte Carlo simulation of particles diffusion in these kind of systems. Experimental results agree well with simulations that correlate the most used parameters and functions characterizing the disorder in porous media.

In the last few years the Web has progressively acquired the status of an infrastructure for social computation that allows researchers to coordinate the cognitive abilities of human agents in on-line communities so to steer the collective user activity towards predefined goals. This general trend is also triggering the adoption of web-games as a very interesting laboratory to run experiments in the social sciences and whenever the contribution of human beings is crucially required for research purposes. Nowadays, while the number of on-line users has been steadily growing, there is still a need of systematization in the approach to the web as a laboratory. In this paper we present Experimental Tribe (XTribe in short), a novel general purpose web-based platform for web-gaming and social computation. Ready to use and already operational, XTribe aims at drastically reducing the effort required to develop and run web experiments. XTribe has been designed to speed up the implementation of those general aspects of web experiments that are independent of the specific experiment content. For example, XTribe takes care of user management by handling their registration and profiles and in case of multi-player games, it provides the necessary user grouping functionalities. XTribe also provides communication facilities to easily achieve both bidirectional and asynchronous communication. From a practical point of view, researchers are left with the only task of designing and implementing the game interface and logic of their experiment, on which they maintain full control. Moreover, XTribe acts as a repository of different scientific experiments, thus realizing a sort of showcase that stimulates users' curiosity, enhances their participation, and helps researchers in recruiting volunteers., Comment: 11 pages, 2 figures, 1 table, 2013 Third International Conference on Cloud and Green Computing (CGC), Sept. 30 2013-Oct. 2 2013, Karlsruhe, Germany

Folksonomies provide a rich source of data to study social patterns taking place on the World Wide Web. Here we study the temporal patterns of users' tagging activity. We show that the statistical properties of inter-arrival times between subsequent tagging events cannot be explained without taking into account correlation in users' behaviors. This shows that social interaction in collaborative tagging communities shapes the evolution of folksonomies. A consensus formation process involving the usage of a small number of tags for a given resources is observed through a numerical and analytical analysis of some well-known folksonomy datasets., 6 pages, 10 figures; Proceedings of the 20th ACM conference on Hypertext and hypermedia, 2009

We study the semantic assortativity in the social networks hosted by the Flickr folksonomy, based both on the contact data and on the group membership data provided by the users. The social network built this way are complex one. Besides, one observes a clear assortativity pattern, stronger than in a suitable null model adopted for a comparison. Nevertheless, such semantical similarity does not appear to develop during the community evolution, but is rather the result of a pre-existing shared background between users.

A distributed classification paradigm known as collaborative tagging has been widely adopted in new Web applications designed to manage and share online resources. Users of these applications organize resources (Web pages, digital photographs, academic papers) by associating with them freely chosen text labels, or tags. Here we leverage the social aspects of collaborative tagging and introduce a notion of resource distance based on the collective tagging activity of users. We collect data from a popular system and perform experiments showing that our definition of distance can be used to build a weighted network of resources with a detectable community structure. We show that this community structure clearly exposes the semantic relations among resources. The communities of resources that we observe are a genuinely emergent feature, resulting from the uncoordinated activity of a large number of users, and their detection paves the way for mapping emergent semantics in social tagging systems., Comment: 14 pages, 8 figures

Endothelial cells are responsible for the formation of the capillary blood vessel network. We describe a system of endothelial cells by means of two-dimensional molecular dynamics simulations of point-like particles. Cells' motion is governed by the gradient of the concentration of a chemical substance that they produce (chemotaxis). The typical time of degradation of the chemical substance introduces a characteristic length in the system. We show that point-like model cells form network resembling structures tuned by this characteristic length, before collapsing altogether. Successively, we improve the non-realistic point-like model cells by introducing an isotropic strong repulsive force between them and a velocity dependent force mimicking the observed peculiarity of endothelial cells to preserve the direction of their motion (persistence). This more realistic model does not show a clear network formation. We ascribe this partial fault in reproducing the experiments to the static geometry of our model cells that, in reality, change their shapes by elongating toward neighboring cells., Comment: 10 pages, 3 figures, 2 of which composite with 8 pictures each. Accepted on J.Stat.Mech. (2009). Appeared at the poster session of StatPhys23, Genoa, Italy, July 13 (2007)

The Yule-Simon model has been used as a tool to describe the growth of diverse systems, acquiring a paradigmatic character in many fields of research. Here we study a modified Yule-Simon model that takes into account the full history of the system by means of an hyperbolic memory kernel. We show how the memory kernel changes the properties of preferential attachment and provide an approximate analytical solution for the frequency distribution density as well as for the frequency-rank distribution., 7 pages, 5 figures; accepted for publication in Europhysics Letters