Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Selection methods regulate evolution of cooperation in digital evolution.

A key, yet often neglected, component of digital evolution and evolutionary models is the 'selection method' which assigns fitness (number of offspring) to individuals based on their performance scores (efficiency in performing tasks). Here, we study with formal analysis and numerical experiments the evolution of cooperation under the five most common selection methods (proportionate, rank, truncation-proportionate, truncation-uniform and tournament). We consider related individuals engaging in a Prisoner's Dilemma game where individuals can either cooperate or defect. A cooperator pays a cost, whereas its partner receives a benefit, which affect their performance scores. These performance scores are translated into fitness by one of the five selection methods. We show that cooperation is positively associated with the relatedness between individuals under all selection methods. By contrast, the change in the performance benefit of cooperation affects the populations' average level of cooperation only under the proportionate methods. We also demonstrate that the truncation and tournament methods may introduce negative frequency-dependence and lead to the evolution of polymorphic populations. Using the example of the evolution of cooperation, we show that the choice of selection method, though it is often marginalized, can considerably affect the evolutionary dynamics.

Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Transition to parenthood: The role of social interaction and endogenous networks

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdepen- dencies across individuals' transition to parenthood and its timing we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics regarding age, intended education and parity. Agents endogenously form their network based on social closeness. Network members then may influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social inter- actions can explain the shift of first-birth probabilities in Austria over the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

Cooperation between the transcription factors p63 and IRF6 is essential to prevent cleft palate in mice.

Cleft palate is a common congenital disorder that affects up to 1 in 2,500 live human births and results in considerable morbidity to affected individuals and their families. The etiology of cleft palate is complex, with both genetic and environmental factors implicated. Mutations in the transcription factor-encoding genes p63 and interferon regulatory factor 6 (IRF6) have individually been identified as causes of cleft palate; however, a relationship between the key transcription factors p63 and IRF6 has not been determined. Here, we used both mouse models and human primary keratinocytes from patients with cleft palate to demonstrate that IRF6 and p63 interact epistatically during development of the secondary palate. Mice simultaneously carrying a heterozygous deletion of p63 and the Irf6 knockin mutation R84C, which causes cleft palate in humans, displayed ectodermal abnormalities that led to cleft palate. Furthermore, we showed that p63 transactivated IRF6 by binding to an upstream enhancer element; genetic variation within this enhancer element is associated with increased susceptibility to cleft lip. Our findings therefore identify p63 as a key regulatory molecule during palate development and provide a mechanism for the cooperative role of p63 and IRF6 in orofacial development in mice and humans.

Modelling non-industrial private forest landowners' strategic decision making by using logistic regression and neural networks: case of predicting the choice of forest taxation basis

Summary

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Communication in networks with hierarchical branching

We present a simple model of communication in networks with hierarchical branching. We analyze the behavior of the model from the viewpoint of critical systems under different situations. For certain values of the parameters, a continuous phase transition between a sparse and a congested regime is observed and accurately described by an order parameter and the power spectra. At the critical point the behavior of the model is totally independent of the number of hierarchical levels. Also scaling properties are observed when the size of the system varies. The presence of noise in the communication is shown to break the transition. The analytical results are a useful guide to forecasting the main features of real networks.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Absence of epidemic threshold in scale free networks with degree correlations

Random scale-free networks have the peculiar property of being prone to the spreading of infections. Here we provide for the susceptible-infected-susceptible model an exact result showing that a scale-free degree distribution with diverging second moment is a sufficient condition to have null epidemic threshold in unstructured networks with either assortative or disassortative mixing. Degree correlations result therefore irrelevant for the epidemic spreading picture in these scale-free networks. The present result is related to the divergence of the average nearest neighbors degree, enforced by the degree detailed balance condition.

Synchronization reveals topological scales in complex networks

We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well-defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology, and spectral graph analysis.

Affaires de patrons, usages de la frontière : géographie des réseaux marchands entre Niger, Bénin et Nigéria

Résumé L'objectif de la thèse est de comprendre le mode d'organisation économique spécifique aux petits centres urbains qui composent les espaces frontaliers sahéliens, en s'interrogeant sur leur concurrence ou leur complémentarité éventuelle à l'intérieur d'un régime de spatialité particulier. En s'appuyant sur l'exemple du carrefour économique de Gaya-Malanville-Kamba situé à la frontière entre le Niger, le Bénin et le Nigeria, il questionne le rôle de la ville-frontière ainsi que le jeu des acteurs marchands localement dominants, à partir de quatre grandes interrogations : Quelles sont les spécificités de l'Afrique sahélienne qui obligent à renouveler les approches géographiques de l'espace marchand? Quels sont les facteurs déterminants de l'activité économique frontalière? Les formes d'organisation de l'espace qui concourent à la structuration de l'économie sont-elles concurrentes ou coopératives? Les logiques économiques frontalières sont-elles compatibles avec l'orientation des programmes de développement adoptés par les pays sahéliens et leurs partenaires bi- ou multilatéraux? Dans une première partie, un modèle territorial de l'Afrique sahélienne permet de rendre compte de la prédominance des logiques circulatoires sur les logiques productives, une propriété essentielle de toute organisation économique confrontée à l'instabilité climatique. Dans une seconde partie, l'étude considère les facteurs déterminants de l'activité économique frontalière que sont le degré d'enclavement des territoires, la libre circulation des biens et des personnes, les relations concurrentielles ou coopératives qui lient les marchés ainsi que les liens clientélistes qui unissent patron et obligés. Une troisième partie est consacrée aux productions agricoles de tente organisées sous forme de coopératives paysannes ou d'initiatives privées. Une quatrième partie s'intéresse aux réseaux de l'import-export et du commerce de détail qui bénéficient de l'augmentation des besoins engendrée par l'urbanisation sahélienne. L'économie spatiale qui résulte de ces flux est organisée selon deux logiques distinctes : d'une part, les opportunités relatives à la production agricole conduisent certains investisseurs à intensifier l'irrigation pour satisfaire la demande des marchés urbains, d'autre part, les acteurs du capitalisme marchand, actifs dans l'import-export et la vente de détail, développent des réseaux informels et mobiles qui se jouent des différentiels nationaux. Les activités commerciales des villes-marchés connaissent alors des fluctuations liées aux entreprises productives et circulatoires de ces patrons, lesquelles concourent à l'organisation territoriale générale de l>Afrique sahélienne. Ces logiques évoluent dans un contexte fortement marqué par les politiques des institutions financières internationales, des agences bilatérales de coopération et des ONGs. Celles-ci se donnent pour ambition de transformer les économies, les systèmes politiques et les organisations sociales sahéliennes, en faisant la promotion du libéralisme, de la bonne gouvernance et de la société civile. Ces axes directeurs, qui constituent le champ de bataille contemporain du développement, forment un ensemble dans lequel la spécificité sahélienne notamment frontalière est rarement prise en compte. C'est pourquoi l'étude conclut en faveur d'un renouvellement des politiques de développement appliquées aux espaces frontaliers. Trois grands axes d'intervention peuvent alors être dégagés, lesquels permettent de réconcilier des acteurs et des logiques longtemps dissociés: ceux des espaces séparés par une limite administrative, ceux de la sphère urbaine et rurale et ceux du capitalisme marchand et de l'investissement agricole, en renforçant la coopération économique transfrontalière, en prenant en considération les interactions croissantes entre villes et campagnes et en appuyant les activités marchandes. Abstract: Urbanisation in West Africa is recent and fast. If only 10 % of the total population was living in urban areas in 1950, this proportion reached 40 % in 2000 and will be estimated to 60 % in 2025. Small and intermediate cities, located between the countryside and large metropolis, are particularly concerned with this process. They are nowadays considered as efficient vectors of local economic development because of fiscal or monetary disparities between states, which enable businessmen to develop particular skills based on local urban networks. The majority of theses networks are informal and extremely flexible, like in the Gaya - Malanville - Kamba region, located between Niger, Benin and Nigeria. Evidence show that this economic space is characterised by high potentialities (climatic and hydrological conditions, location on main economic West African axis) and few constraints (remoteness of some potentially high productive areas). In this context, this PhD deals with the economic relationships between the three market cities. Focusing on the links that unite the businessmen of the local markets - called patron; - it reveals the extreme flexibility of their strategies as well as the deeply informal nature of their activities. Through the analysis of examples taken from the commerce of agricultural products, import and export flows and detail activities, it studies the changes that have taken place in the city centres of Gaya, Malanville and Kamba. Meanwhile, this research shows how these cities represent a border economical area based on rival and complementary connections. In the first Part, it was necessary to reconsider the usual spatial analysis devoted to the question of economic centrality. As a matter of fact, the organisation of West African economic spaces is very flexible and mobile. Centrality is always precarious because of seasonal or temporary reasons. This is why the first chapters are devoted to the study of the specificity of the Sahelian territoriality. Two main elements are relevant: first the population diversity and second, the urban-rural linkages. In the second part, the study considers three main factors on which the cross-border economic networks are dependent: enclosure that prevents goods to reach the markets, administrative constraints that limit free trade between states and cities and the concurrent or complementary relationships between markets. A third part deals with the clientelist ties engaged between the patrons and their clients with the hypothesis that these relationships are based on reciprocity and inequality. A fourth part is devoted to' the study of the spatial organisation of commercial goods across the borders, as far as the agriculture commercial products, the import-export merchandises and the retail products are concerned. This leads to the conclusion that the economic activity is directly linked to urban growth. However, the study notices that there is a lack of efficient policies dealing with strengthening the business sector and improving the cross-border cooperation. This particularity allows us to favour new local development approaches, which would take into account the important potential of private economical actors. In the same time, the commercial flows should be regulated with the help of public policies, as long as they are specifically adapted to the problems that these areas have to deal with.

Self-similarity of complex networks and hidden metric spaces

We demonstrate that the self-similarity of some scale-free networks with respect to a simple degree-thresholding renormalization scheme finds a natural interpretation in the assumption that network nodes exist in hidden metric spaces. Clustering, i.e., cycles of length three, plays a crucial role in this framework as a topological reflection of the triangle inequality in the hidden geometry. We prove that a class of hidden variable models with underlying metric spaces are able to accurately reproduce the self-similarity properties that we measured in the real networks. Our findings indicate that hidden geometries underlying these real networks are a plausible explanation for their observed topologies and, in particular, for their self-similarity with respect to the degree-based renormalization.

Percolation and epidemic thresholds in clustered networks

We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant connected component, it cannot restore a finite percolation threshold. In turn, this implies the absence of an epidemic threshold in this class of networks, thus extending this result to a wide variety of real scale-free networks which shows a high level of transitivity. Our findings are in good agreement with numerical simulations.