Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

The structural nature of perceptual experiences

Intuitively, we think of perception as providing us with direct cognitive access to physical objects and their properties. But this common sense picture of perception becomes problematic when we notice that perception is not always veridical. In fact, reflection on illusions and hallucinations seems to indicate that perception cannot be what it intuitively appears to be. This clash between intuition and reflection is what generates the puzzle of perception. The task and enterprise of unravelling this puzzle took, and still takes, centre stage in the philosophy of perception. The goal of my dissertation is to make a contribution to this enterprise by formulating and defending a new structural approach to perception and perceptual consciousness. The argument for my structural approach is developed in several steps. Firstly, I develop an empirically inspired causal argument against naïve and direct realist conceptions of perceptual consciousness. Basically, the argument says that perception and hallucination can have the same proximal causes and must thus belong to the same mental kind. I emphasise that this insight gives us good reasons to abandon what we are instinctively driven to believe - namely that perception is directly about the outside physical world. The causal argument essentially highlights that the information that the subject acquires in perceiving a worldly object is always indirect. To put it another way, the argument shows that what we, as perceivers, are immediately aware of, is not an aspect of the world but an aspect of our sensory response to it. A view like this is traditionally known as a Representative Theory of Perception. As a second step, emphasis is put on the task of defending and promoting a new structural version of the Representative Theory of Perception; one that is immune to some major objections that have been standardly levelled at other Representative Theories of Perception. As part of this defence and promotion, I argue that it is only the structural features of perceptual experiences that are fit to represent the empirical world. This line of thought is backed up by a detailed study of the intriguing phenomenon of synaesthesia. More precisely, I concentrate on empirical cases of synaesthetic experiences and argue that some of them provide support for a structural approach to perception. The general picture that emerges in this dissertation is a new perspective on perceptual consciousness that is structural through and through.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Structure du temps de travail des infirmières de santé publique: effets de l'âge des patients, de la nature des prestations fournies et du lieu du contact. [Structure of work times of public health nurses: effect of the age of patients, nature of care given and location of contact].

In the framework of health services research sponsored by the Swiss National Science Foundation, a research was undertaken of the activity of the large majority of the public health nurses working in the Swiss cantons of Vaud and Fribourg (total population 700,000). During one week, 130 nurses gathered, with a specially devised instrument, data on 4165 patient visits. Studying the duration of the contacts, one has distinguished contact duration per se (DC), duration of the travel time preceding the contact (DD), and total duration in relation with the contact (DTC-addition of the first two). It was noted that the three durations increased significantly with patient age (as regard travel time, this is explained by the higher proportion of home visits in higher age groups, as compared with visits at a health center). Examined according to location of the visit, contact duration per se (without travel) is higher for visits at home and in nursing homes than for those taking place at a health center. Looked at in respect to the care given (technical care, or basic nursing care, or both simultaneously), our data show that the provision of basic nursing care (alone or with technical care) doubles contact duration (from 20 to 42-45'). The analyses according to patient age shows that, at an advanced age (beyond 80 years particularly), there is an important increase of the visits where both types of care are given. However, contact duration per se shows a significant raise with age only for the group "technical care only"; it can be demonstrated that this is due to the fact that older patients require more complex technical acts (e.g., bladder care, as compared with simpler acts such as injection). A model of the relationships between patient age and contact duration is proposed: it is because of the increase in the proportions of home visits, of visits including basic nursing care, and of more complex technical acts that older persons require more of the working time of public health nurses.

Le rôle des études universitaires et de la nature de la procédure sur les opinions envers les politiques de discrimination positive

RésuméCette thèse s'intéresse à l'impact du niveau d'éducation sur les attitudes envers les mesures de discrimination positive en faveur de la promotion professionnelle des femmes. La littérature consacrée à cette relation présente des résultats inconsistants : certains travaux ne montrent que l'éducation n'a pas d'effet sur l'accueil réservé aux mesures positives, tandis que d'autres suggèrent que cette relation pourrait être influencée par la nature des mesures positives. Nos attentes s'appuient sur les thèses de l'effet libérateur et de l'effet reproducteur de l'éducation. Les études réalisées dans le cadre de cette thèse, menées auprès de cadres, d'employés et d'étudiants résidant en Suisse et en Albanie, mettent en évidence un lien négatif entre le nombre d'années d'études et l'acceptation des mesures positives. Toutefois, cet effet apparaît essentiellement dans le cas de la mesure favorisant l'appartenance groupale des candidates par rapport à leurs caractéristiques personnelles, et non pas dans le cas de la mesure s'appuyant sur les compétences et le mérite des candidates. Nos études mettent en évidence les mécanismes qui génèrent ces opinions : l'orientation à la dominance sociale, l'adhésion aux principes méritocratiques, la reconnaissance de la discrimination subie par les femmes et le sentiment de menace généré par la mise en place des mesures de discrimination positive. Ces études examinent également la perception plus ou moins stéréotypée des bénéficiaires des mesures positives et de leur vulnérabilité aux conduites d'auto-handicap. Dans l'ensemble, les résultats corroborent davantage la thèse de l'effet reproducteur de l'éducation que celle de l'effet libérateur de l'éducation.

Evidence for transcript networks composed of chimeric RNAs in human cells.

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.

Repeated Pre-Syncope from Increased Inspired CO2 in a Background of Severe Hypoxia.

We describe a case of experimentally induced pre-syncope in a healthy young man when exposed to increased inspired CO2 in a background of hypoxia. Acute severe hypoxia (FIO2=0.10) was tolerated, but adding CO2 to the inspirate caused pre-syncope symptoms accompanied by hypotension and large reductions in both mean and diastolic middle cerebral artery velocity, while systolic flow velocity was maintained. The mismatch of cerebral perfusion pressure and vascular tone caused unique retrograde cerebral blood flow at the end of systole and a reduction in cerebral tissue oxygenation. We speculate that this occurrence of pre-syncope was due to hypoxia-induced inhibition of brain regions responsible for compensatory sympathetic activity to relative hypercapnia.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI.

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

Les symbioses agro-industrielles en Afrique de l'Ouest : évaluation du potentiel d'une nouvelle stratégie pour un développement durable

RésuméCette thèse traite de l'utilisation des concepts de Symbiose Industrielle dans les pays en développement et étudie le potentiel de cette stratégie pour stimuler un développement régional durable dans les zones rurales d'Afrique de l'Ouest. En particulier, lorsqu'une Symbiose Industrielle est instaurée entre une usine et sa population alentour, des outils d'évaluation sont nécessaires pour garantir que le projet permette d'atteindre un réel développement durable. Les outils existants, développés dans les pays industrialisés, ne sont cependant pas complètement adaptés pour l'évaluation de projets dans les pays en développement. En effet, les outils sont porteurs d'hypothèses implicites propres au contexte socio-économique dans lequel ils ont été conçus.L'objectif de cette thèse est de développer un cadre méthodologique pour l'évaluation de la durabilité de projets de Symbiose Industrielle dans les pays en développement.Pour ce faire, je m'appuie sur une étude de cas de la mise en place d'une Symbiose Industrielle au nord du Nigéria, à laquelle j'ai participé en tant qu'observatrice dès 2007. AshakaCem, une usine productrice de ciment du groupe Lafarge, doit faire face à de nombreuses tensions avec la population rurale alentour. L'entreprise a donc décidé d'adopter une nouvelle méthode inspirée des concepts de Symbiose Industrielle. Le projet consiste à remplacer jusqu'à 10% du carburant fossile utilisé pour la cuisson de la matière crue (calcaire et additifs) par de la biomasse produite par les paysans locaux. Pour ne pas compromettre la fragile sécurité alimentaire régionale, des techniques de lutte contre l'érosion et de fertilisation naturelle des sols sont enseignées aux paysans, qui peuvent ainsi utiliser la culture de biomasse pour améliorer leurs cultures vivrières. A travers cette Symbiose Industrielle, l'entreprise poursuit des objectifs sociaux (poser les bases nécessaires à un développement régional), mais également environnementaux (réduire ses émissions de CO2 globales) et économiques (réduire ses coûts énergétiques). Elle s'ancre ainsi dans une perspective de développement durable qui est conditionnelle à la réalisation du projet.A travers l'observation de cette Symbiose et par la connaissance des outils existants je constate qu'une évaluation de la durabilité de projets dans les pays en développement nécessite l'utilisation de critères d'évaluation propres à chaque projet. En effet, dans ce contexte, l'emploi de critères génériques apporte une évaluation trop éloignée des besoins et de la réalité locale. C'est pourquoi, en m'inspirant des outils internationalement reconnus comme l'Analyse du Cycle de Vie ou la Global Reporting Initiative, je définis dans cette thèse un cadre méthodologique qui peut, lui, être identique pour tous les projets. Cette stratégie suit six étapes, qui se réalisent de manière itérative pour permettre une auto¬amélioration de la méthodologie d'évaluation et du projet lui-même. Au cours de ces étapes, les besoins et objectifs en termes sociaux, économiques et environnementaux des différents acteurs sont déterminés, puis regroupés, hiérarchisés et formulés sous forme de critères à évaluer. Des indicateurs quantitatifs ou qualitatifs sont ensuite définis pour chacun de ces critères. Une des spécificités de cette stratégie est de définir une échelle d'évaluation en cinq graduations, identique pour chaque indicateur, témoignant d'un objectif totalement atteint (++) ou pas du tout atteint (--).L'application de ce cadre méthodologique à la Symbiose nigériane a permis de déterminer quatre critères économiques, quatre critères socio-économiques et six critères environnementaux à évaluer. Pour les caractériser, 22 indicateurs ont été définis. L'évaluation de ces indicateurs a permis de montrer que le projet élaboré atteint les objectifs de durabilité fixés pour la majorité des critères. Quatre indicateurs ont un résultat neutre (0), et un cinquième montre qu'un critère n'est pas atteint (--). Ces résultats s'expliquent par le fait que le projet n'en est encore qu'à sa phase pilote et n'a donc pas encore atteint la taille et la diffusion optimales. Un suivi sur plusieurs années permettra de garantir que ces manques seront comblés.Le cadre méthodologique que j'ai développé dans cette thèse est un outil d'évaluation participatif qui pourra être utilisé dans un contexte plus large que celui des pays en développement. Son caractère générique en fait un très bon outil pour la définition de critères et indicateurs de suivi de projet en terme de développement durable.SummaryThis thesis examines the use of industrial symbiosis in developing countries and studies its potential to stimulate sustainable regional development in rural areas across Western Africa. In particular, when industrial symbiosis is instituted between a factory and the surrounding population, evaluation tools are required to ensure the project achieves truly sustainable development. Existing tools developed in industrialized countries are not entirely suited to assessing projects in developing countries. Indeed, the implicit hypotheses behind such tools reflect the socioeconomic context in which they were designed. The goal of this thesis is to develop a methodological framework for evaluating the sustainability of industrial symbiosis projects in developing countries.To accomplish this, I followed a case study about the implementation of industrial symbiosis in northern Nigeria by participating as an observer since 2007. AshakaCem, a cement works of Lafarge group, must confront many issues associated with violence committed by the local rural population. Thus, the company decided to adopt a new approach inspired by the concepts of industrial symbiosis.The project involves replacing up to 10% of the fossil fuel used to heat limestone with biomass produced by local farmers. To avoid jeopardizing the fragile security of regional food supplies, farmers are taught ways to combat erosion and naturally fertilize the soil. They can then use biomass cultivation to improve their subsistence crops. Through this industrial symbiosis, AshakaCem follows social objectives (to lay the necessary foundations for regional development), but also environmental ones (to reduce its overall CO2 emissions) and economical ones (to reduce its energy costs). The company is firmly rooted in a view of sustainable development that is conditional upon the project's execution.By observing this symbiosis and by being familiar with existing tools, I note that assessing the sustainability of projects in developing countries requires using evaluation criteria that are specific to each project. Indeed, using generic criteria results in an assessment that is too far removed from what is needed and from the local reality. Thus, by drawing inspiration from such internationally known tools as Life Cycle Analysis and the Global Reporting Initiative, I define a generic methodological framework for the participative establishment of an evaluation methodology specific to each project.The strategy follows six phases that are fulfilled iteratively so as to improve the evaluation methodology and the project itself as it moves forward. During these phases, the social, economic, and environmental needs and objectives of the stakeholders are identified, grouped, ranked, and expressed as criteria for evaluation. Quantitative or qualitative indicators are then defined for each of these criteria. One of the characteristics of this strategy is to define a five-point evaluation scale, the same for each indicator, to reflect a goal that was completely reached (++) or not reached at all (--).Applying the methodological framework to the Nigerian symbiosis yielded four economic criteria, four socioeconomic criteria, and six environmental criteria to assess. A total of 22 indicators were defined to characterize the criteria. Evaluating these indicators made it possible to show that the project meets the sustainability goals set for the majority of criteria. Four indicators had a neutral result (0); a fifth showed that one criterion had not been met (--). These results can be explained by the fact that the project is still only in its pilot phase and, therefore, still has not reached its optimum size and scope. Following up over several years will make it possible to ensure these gaps will be filled.The methodological framework presented in this thesis is a highly effective tool that can be used in a broader context than developing countries. Its generic nature makes it a very good tool for defining criteria and follow-up indicators for sustainable development.