An Interval Intelligent-based Approach for Fault Detection and Modelling

Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

Nanomotors: new strategies of (bio)sensing based on motion

Nanomotors are nanoscale devices capable of converting energy into movement and forces. Among them, self-propelled nanomotors offer considerable promise for developing new and novel bioanalytical and biosensing strategies based on the direct isolation of target biomolecules or changes in their movement in the presence of target analytes. The mainachievements of this project consists on the development of receptor-functionalized nanomotors that offer direct and rapid target detection, isolation and transport from raw biological samples without preparatory and washing steps. For example, microtube engines functionalized with aptamer, antibody, lectin and enzymes receptors were used for the direct isolation of analytes of biomedical interest, including proteins and whole cells, among others. A target protein was also isolated from a complex sample by using an antigen-functionalized microengine navigating into the reservoirs of a lab-on-a-chip device. The new nanomotorbased target biomarkers detection strategy not only offers highly sensitive, rapid, simple and low cost alternative for the isolation and transport of target molecules, but also represents a new dimension of analytical information based on motion. The recognition events can be easily visualized by optical microscope (without any sophisticated analytical instrument) to reveal the target presence and concentration. The use of artificial nanomachines has shown not only to be useful for (bio)recognition and (bio)transport but also for detection of environmental contamination and remediation. In this context, micromotors modified with superhydrophobic layer demonstrated that effectively interacted, captured, transported and removed oil droplets from oil contaminated samples. Finally, a unique micromotor-based strategy for water-quality testing, that mimics live-fish water-quality testing, based on changes in the propulsion behavior of artificial biocatalytic microswimmers in the presence of aquatic pollutants was also developed. The attractive features of the new micromachine-based target isolation and signal transduction protocols developed in this project offer numerous potential applications in biomedical diagnostics, environmental monitoring, and forensic analysis.

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.

Reputation based on punishment rather than generosity allows for evolution of cooperation in sizable groups

Cooperation among unrelated individuals can arise if decisions to help others can be based on reputation. While working for dyadic interactions, reputation-use in social dilemmas involving many individuals (e.g. public goods games) becomes increasingly difficult as groups become larger and errors more frequent. Reputation is therefore believed to have played a minor role for the evolution of cooperation in collective action dilemmas such as those faced by early humans. Here, we show in computer simulations that a reputation system based on punitive actions can overcome these problems and, compared to reputation system based on generous actions, (i) is more likely to lead to the evolution of cooperation in sizable groups, (ii) more effectively sustains cooperation within larger groups, and (iii) is more robust to errors in reputation assessment. Punishment and punishment reputation could therefore have played crucial roles in the evolution of cooperation within larger groups of humans.

Electrical neuroimaging of memory discrimination based on single-trial multisensory learning.

Multisensory experiences influence subsequent memory performance and brain responses. Studies have thus far concentrated on semantically congruent pairings, leaving unresolved the influence of stimulus pairing and memory sub-types. Here, we paired images with unique, meaningless sounds during a continuous recognition task to determine if purely episodic, single-trial multisensory experiences can incidentally impact subsequent visual object discrimination. Psychophysics and electrical neuroimaging analyses of visual evoked potentials (VEPs) compared responses to repeated images either paired or not with a meaningless sound during initial encounters. Recognition accuracy was significantly impaired for images initially presented as multisensory pairs and could not be explained in terms of differential attention or transfer of effects from encoding to retrieval. VEP modulations occurred at 100-130ms and 270-310ms and stemmed from topographic differences indicative of network configuration changes within the brain. Distributed source estimations localized the earlier effect to regions of the right posterior temporal gyrus (STG) and the later effect to regions of the middle temporal gyrus (MTG). Responses in these regions were stronger for images previously encountered as multisensory pairs. Only the later effect correlated with performance such that greater MTG activity in response to repeated visual stimuli was linked with greater performance decrements. The present findings suggest that brain networks involved in this discrimination may critically depend on whether multisensory events facilitate or impair later visual memory performance. More generally, the data support models whereby effects of multisensory interactions persist to incidentally affect subsequent behavior as well as visual processing during its initial stages.

Activity and exploratory behavior after lesions of the medial entorhinal cortex in the woodmouse (Apodemus sylvaticus).

The effects of bilateral electrolytic lesions of the entorhinal cortex were studied in male adult woodmice. Experiments were designed to allow separate analysis of the basal activity level and exploratory behavior. Activity recording was conducted in three situations: (a) 24-hr wheel running in the home cage pre- and postoperatively; (b) 24-hr activity composition in a large enclosure over 4 days, 5 to 9 days postoperatively; and (c) sequence and duration of visits in a residential plus maze 11 to 14 days postoperatively. Medial entorhinal cortex lesion involving the para- and presubiculum increased the 24-hr amount of movements in the enclosure (b) without increasing wheel running in any situation (a or b). This lesion also enhanced the locomotor reactivity to being introduced into the plus maze and impaired exploratory behavior. This last effect was equally apparent when the whole situation was new or when part of the familiar maze was modified. Lesioned woodmice did notice the new element but did not show active focalization of their behavior on that element. Data showed that lesion induced hyperactivity and changes of exploratory behavior were not necessarily associated. Novelty detection was performed but it is not clear now on what information this discrimination was based.

Revenue management under general discrete choice model of consumer behavior

Customer choice behavior, such as 'buy-up' and 'buy-down', is an importantphe-nomenon in a wide range of industries. Yet there are few models ormethodologies available to exploit this phenomenon within yield managementsystems. We make some progress on filling this void. Specifically, wedevelop a model of yield management in which the buyers' behavior ismodeled explicitly using a multi-nomial logit model of demand. Thecontrol problem is to decide which subset of fare classes to offer ateach point in time. The set of open fare classes then affects the purchaseprobabilities for each class. We formulate a dynamic program todetermine the optimal control policy and show that it reduces to a dynamicnested allocation policy. Thus, the optimal choice-based policy caneasily be implemented in reservation systems that use nested allocationcontrols. We also develop an estimation procedure for our model based onthe expectation-maximization (EM) method that jointly estimates arrivalrates and choice model parameters when no-purchase outcomes areunobservable. Numerical results show that this combined optimization-estimation approach may significantly improve revenue performancerelative to traditional leg-based models that do not account for choicebehavior.

Economic rationality and ethical behavior

This paper argues that economic rationality and ethical behavior cannotbe reduced one to the other, casting doubts on the validity of formulaslike 'profit is ethical' or 'ethics pays'. In order to express ethicaldilemmas as opposing economic interest with ethical concerns, we proposea model of rational behavior that combines these two irreducible dimensions in an open but not arbitrary manner. Behaviors that are neither ethicalnor profitable are considered irrational (non-arbitrariness). However,behaviors that are profitable but unethical, and behaviors that are ethicalbut not profitable, are all treated as rational (openness). Combiningethical concerns with economic interest, ethical business is in turn anoptimal form of rationality between venality and sacrifice.Because every one prefers to communicate that he acts ethically, ethicalbusiness remains ambiguous until some economic interest is actuallysacrificed. We argue however that ethical business has an interest indemonstrating its consistency between communication and behavior by atransparent attitude. On the other hand, venal behaviors must remainconfidential to hide the corresponding lack of consistency. Thisdiscursive approach based on transparency and confidentiality helpsto further distinguish between ethical and unethical business behaviors.

A Hull and White formula for a general stochastic volatility jump-diffusion model with applications to the study of the short-time behavior of the implied volatility

In this paper, generalizing results in Alòs, León and Vives (2007b), we see that the dependence of jumps in the volatility under a jump-diffusion stochastic volatility model, has no effect on the short-time behaviour of the at-the-money implied volatility skew, although the corresponding Hull and White formula depends on the jumps. Towards this end, we use Malliavin calculus techniques for Lévy processes based on Løkka (2004), Petrou (2006), and Solé, Utzet and Vives (2007).

A simple model of multiple equilibria based on risk

This paper shows how risk may aggravate fluctuations in economies with imperfect insurance and multiple assets. A two period job matching model is studied, in which risk averse agents act both as workers and as entrepreneurs. They choose between two types of investment: one type is riskless, while the other is a risky activity that creates jobs.Equilibrium is unique under full insurance. If investment is fully insured but unemployment risk is uninsured, then precautionary saving behavior dampens output fluctuations. However, if both investment and employment are uninsured, then an increase in unemployment gives agents an incentive to shift investment away from the risky asset, further increasing unemployment. This positive feedback may lead to multiple Pareto ranked equilibria. An overlapping generations version of the model may exhibit poverty traps or persistent multiplicity. Greater insurance is doubly beneficial in this context since it can both prevent multiplicity and promote risky investment.

Sexual behavior of the digger wasp Sphex ingens Smith (Hymenoptera, Sphecidae)

A species' mating system depends on its spatial distribution and temporal availability of mating opportunities, as well as on the resources that create these opportunities. In addition, for many species, courtship is driven by specific behaviors that precede and follow copulation. Although Sphex ingens is a taxonomically well known species of digger wasp, its ecology and behavior remain poorly known. Hence, we analyzed patterns and trends of sexual behavior, in order to understand whether courtship can persist in a polygamous mating system. We monitored by video wasp populations in Ilha Grande, southeastern Brazil. Based on the observed behaviors, we calculated stochastic probabilities with a Markov chain to infer on behavioral trends. We recorded four behavioral phases based on 19,196 behavioral acts observed in 224 copulation attempts. There were no significant differences in common behavioral acts between males and females. The copulation patterns, conflicts, and trends observed in S. ingens clearly show the influence of sexual selection in its promiscuous mating system.

Evaluation of an online, case-based interactive approach to teaching pathophysiology

Rapport de synthèse : L'article qui fait l'objet de ma thèse évalue une nouvelle approche pédagogique pour l'apprentissage de certains chapitres de physiopathologie. Le dispositif pédagogique se base sur l'alternance d'apprentissage ex-cathedra et de l'utilisation d'un site web comprenant des vignettes cliniques. Lors de la consultation de ces-dernières, l'étudiant est invité à demander des examens de laboratoire dont il pourrait justifier la pertinence selon le cas clinique étudié. La nouveauté du procédé réside dans le fait que, préalablement à son cours ex-cathedra, l'enseignant peut consulter les statistiques de demandes de laboratoire et ainsi orienter son cours selon les éléments mal compris par les étudiants. A la suite du cours ex-cathedra, les étudiants peuvent consulter sur internet la vignette clinique complète avec des explications. A l'issue de tout le cours, une évaluation auprès des étudiants a été conduite. Le procédé a été mis en place durant deux années consécutives et l'article en discute notamment les résultats. Nous avons pu conclure que cette méthode innovatrice d'enseignement amène les étudiants à mieux se préparer pour les cours ex-cathedra tout en permettant à l'enseignant d'identifier plus précisément quelles thématiques étaient difficiles pour les étudiants et donc d'ajuster au mieux son cours. Mon travail de thèse a consisté à créer ce dispositif d'apprentissage, à créer l'application web des vignettes cliniques et à l'implanter durant deux années consécutives. J'ai ensuite analysé les données des évaluations et écrit l'article que j'ai présenté à la revue 'Medical Teacher'. Après quelques corrections et précisions demandées par le comité de lecture, l'article a été accepté et publié. Ce travail a débouché sur une seconde version de l'application web qui est actuellement utilisée lors du module 3.1 de 3è année à l'Ecole de Médecine à Lausanne. Summary : Since the early days of sexual selection, our understanding of the selective forces acting on males and females during reproduction has increased remarkably. However, despite a long tradition of experimental and theoretical work in this field and relentless effort, numerous questions remain unanswered and many results are conflicting. Moreover, the interface between sexual selection and conservation biology has to date received little attention, despite existing evidence for its importance. In the present thesis, I first used an empirical approach to test various sexual selection hypotheses in a population of whitefish of central Switzerland. This precise population is characterized by a high prevalence of gonadal alterations in males. In particular, I challenged the hypothesis that whitefish males displaying peculiar gonadal features are of lower genetic quality than other seemingly normal males. Additionally, I also worked on identifying important determinant of sperm behavior. During a second theoretical part of my work, which is part of a larger project on the evolution of female mate preferences in harvested fish populations, I developed an individual-based simulation model to estimate how different mate discrimination costs affect the demographical behavior of fish populations and the evolutionary trajectories of female mate preferences. This latter work provided me with some insight on a recently published article addressing the importance of sexual selection for harvesting-induced evolution. I built upon this insight in a short perspective paper. In parallel, I let some methodological questions drive my thoughts, and wrote an essay about possible synergies between the biological, the philosophical and the statistical approach to biological questions.

Decoding stimulus-related information from single-trial EEG responses based on voltage topographies

Neuroimaging studies typically compare experimental conditions using average brain responses, thereby overlooking the stimulus-related information conveyed by distributed spatio-temporal patterns of single-trial responses. Here, we take advantage of this rich information at a single-trial level to decode stimulus-related signals in two event-related potential (ERP) studies. Our method models the statistical distribution of the voltage topographies with a Gaussian Mixture Model (GMM), which reduces the dataset to a number of representative voltage topographies. The degree of presence of these topographies across trials at specific latencies is then used to classify experimental conditions. We tested the algorithm using a cross-validation procedure in two independent EEG datasets. In the first ERP study, we classified left- versus right-hemifield checkerboard stimuli for upper and lower visual hemifields. In a second ERP study, when functional differences cannot be assumed, we classified initial versus repeated presentations of visual objects. With minimal a priori information, the GMM model provides neurophysiologically interpretable features - vis à vis voltage topographies - as well as dynamic information about brain function. This method can in principle be applied to any ERP dataset testing the functional relevance of specific time periods for stimulus processing, the predictability of subject's behavior and cognitive states, and the discrimination between healthy and clinical populations.

Time-scale and other invariants of integrative mechanical behavior in living cells.

In dealing with systems as complex as the cytoskeleton, we need organizing principles or, short of that, an empirical framework into which these systems fit. We report here unexpected invariants of cytoskeletal behavior that comprise such an empirical framework. We measured elastic and frictional moduli of a variety of cell types over a wide range of time scales and using a variety of biological interventions. In all instances elastic stresses dominated at frequencies below 300 Hz, increased only weakly with frequency, and followed a power law; no characteristic time scale was evident. Frictional stresses paralleled the elastic behavior at frequencies below 10 Hz but approached a Newtonian viscous behavior at higher frequencies. Surprisingly, all data could be collapsed onto master curves, the existence of which implies that elastic and frictional stresses share a common underlying mechanism. Taken together, these findings define an unanticipated integrative framework for studying protein interactions within the complex microenvironment of the cell body, and appear to set limits on what can be predicted about integrated mechanical behavior of the matrix based solely on cytoskeletal constituents considered in isolation. Moreover, these observations are consistent with the hypothesis that the cytoskeleton of the living cell behaves as a soft glassy material, wherein cytoskeletal proteins modulate cell mechanical properties mainly by changing an effective temperature of the cytoskeletal matrix. If so, then the effective temperature becomes an easily quantified determinant of the ability of the cytoskeleton to deform, flow, and reorganize.

Ispol'zovanie metodov teorii vosstanovleniia v modeliakh optimal'nogo dobyvaniia pishchi [Restoration theory in models of optimal feeding behavior]

The method of stochastic dynamic programming is widely used in ecology of behavior, but has some imperfections because of use of temporal limits. The authors presented an alternative approach based on the methods of the theory of restoration. Suggested method uses cumulative energy reserves per time unit as a criterium, that leads to stationary cycles in the area of states. This approach allows to study the optimal feeding by analytic methods.