Identification des corrélats neuronaux associés à la clôture perceptive des objets : une étude en potentiels évoqués

La capacité du système visuel humain à compléter une image partiellement dévoilée et à en dériver une forme globale à partir de ses fragments visibles incomplets est un phénomène qui suscite, jusqu’à nos jours, l’intérêt de nombreux scientifiques œuvrant dans différents milieux de recherche tels que l’informatique, l’ingénierie en intelligence artificielle, la perception et les neurosciences. Dans le cadre de la présente thèse, nous nous sommes intéressés spécifiquement sur les substrats neuronaux associés à ce phénomène de clôture perceptive. La thèse actuelle a donc pour objectif général d’explorer le décours spatio-temporel des corrélats neuronaux associés à la clôture perceptive au cours d’une tâche d’identification d’objets. Dans un premier temps, le premier article visera à caractériser la signature électrophysiologique liée à la clôture perceptive chez des personnes à développement typique dans le but de déterminer si les processus de clôture perceptive reflèteraient l’interaction itérative entre les mécanismes de bas et de haut-niveau et si ceux-ci seraient sollicités à une étape précoce ou tardive lors du traitement visuel de l’information. Dans un deuxième temps, le second article a pour objectif d’explorer le décours spatio-temporel des mécanismes neuronaux sous-tendant la clôture perceptive dans le but de déterminer si les processus de clôture perceptive des personnes présentant un trouble autistique se caractérisent par une signature idiosyncrasique des changements d’amplitude des potentiels évoqués (PÉs). En d’autres termes, nous cherchons à déterminer si la clôture perceptive en autisme est atypique et nécessiterait davantage la contribution des mécanismes de bas-niveau et/ou de haut-niveau. Les résultats du premier article indiquent que le phénomène de clôture perceptive est associé temporellement à l’occurrence de la composante de PÉs N80 et P160 tel que révélé par des différences significatives claires entre des objets et des versions méconnaissables brouillées. Nous proposons enfin que la clôture perceptive s’avère un processus de transition reflétant les interactions proactives entre les mécanismes neuronaux œuvrant à apparier l’input sensoriel fragmenté à une représentation d’objets en mémoire plausible. Les résultats du second article révèlent des effets précoces de fragmentation et d’identification obtenus au niveau de composantes de potentiels évoqués N80 et P160 et ce, en toute absence d’effets au niveau des composantes tardives pour les individus avec autisme de haut niveau et avec syndrome d’Asperger. Pour ces deux groupes du trouble du spectre autistique, les données électrophysiologiques suggèrent qu’il n’y aurait pas de pré-activation graduelle de l’activité des régions corticales, entre autres frontales, aux moments précédant et menant vers l’identification d’objets fragmentés. Pour les participants autistes et avec syndrome d’Asperger, les analyses statistiques démontrent d’ailleurs une plus importante activation au niveau des régions postérieures alors que les individus à développement typique démontrent une activation plus élevée au niveau antérieur. Ces résultats pourraient suggérer que les personnes du spectre autistique se fient davantage aux processus perceptifs de bas-niveau pour parvenir à compléter les images d’objets fragmentés. Ainsi, lorsque confrontés aux images d’objets partiellement visibles pouvant sembler ambiguës, les individus avec autisme pourraient démontrer plus de difficultés à générer de multiples prédictions au sujet de l’identité d’un objet qu’ils perçoivent. Les implications théoriques et cliniques, les limites et perspectives futures de ces résultats sont discutées.

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Pyocyanin (5-methyl-1-hydroxyphenazine) produced by Pseudomonas aeruginosa as antagonist to vibrios in aquaculture: overexpression, downstream process and toxicity

Pyocyanin is a versatile and multifunctional phenazine, widely used as a bio-control agent. Besides its toxicity in higher concentration, it has been applied as bio-control agents against many pathogens including the Vibrio spp. in aquaculture systems. The exact mechanism of the production of pyocyanin in Pseudomonas aeruginosa is well known, but the genetic modification of pyocyanin biosynthetic pathways in P. aeruginosa is not yet experimented to improve the yield of pyocyanin production. In this context, one of the aims of this work was to improve the yield of pyocyanin production in P. aeruginosa by way of increasing the copy number of pyocyanin pathway genes and their over expression. The specific aims of this work encompasses firstly, the identification of probiotic effect of P. aeruginosa isolated from various ecological niches, the overexpression of pyocyanin biosynthetic genes, development of an appropriate downstream process for large scale production of pyocyanin and its application in aquaculture industries. In addition, this work intends to examine the toxicity of pyocyanin on various developmental stages of tiger shrimp (Penaeus monodon), Artemia nauplii, microbial consortia of nitrifying bioreactors (Packed Bed Bioreactor, PBBR and Stringed Bed Suspended Bioreactor, SBSBR) and in vitro cell culture systems from invertebrates and vertebrates. The present study was undertaken with a vision to manage the pathogenic vibrios in aquaculture through eco-friendly and sustainable management strategies with the following objectives: Identification of Pseudomonas isolated from various ecological niches and its antagonism to pathogenic vibrios in aquaculture.,Saline dependent production of pyocyanin in Pseudomonas aeruginosa originated from different ecological niches and their selective application in aquaculture,Cloning and overexpression of Phz genes encoding phenazine biosynthetic pathway for the enhanced production of pyocyanin in Pseudomonas aeruginosa MCCB117,Development of an appropriate downstream process for large scale production of pyocyanin from PA-pUCP-Phz++; Structural elucidation and functional analysis of the purified compoundToxicity of pyocyanin on various biological systems.

Code clones in program test sequence identification

Code clones are portions of source code which are similar to the original program code. The presence of code clones is considered as a bad feature of software as the maintenance of software becomes difficult due to the presence of code clones. Methods for code clone detection have gained immense significance in the last few years as they play a significant role in engineering applications such as analysis of program code, program understanding, plagiarism detection, error detection, code compaction and many more similar tasks. Despite of all these facts, several features of code clones if properly utilized can make software development process easier. In this work, we have pointed out such a feature of code clones which highlight the relevance of code clones in test sequence identification. Here program slicing is used in code clone detection. In addition, a classification of code clones is presented and the benefit of using program slicing in code clone detection is also mentioned in this work.

Arbitrage Pricing Theory and Return Generating Process: A Macroeconomic Approach to Indian Stock Market

A study focusing on the identification of return generating factors and to the extent of their influence on share prices the outcome will be a tool for investment analysis in the hands of investors portfolio managers and mutual funds who are mostly concerned with changing share prices. Since the study takes into account the influence of macroeconomic variables on variations in share returns by using the outcome the government can frame out suitable policies on long term basis and that will help in nurturing a healthy economy and resultant stock market. As every company management tries to maximize the wealth of the share holders a clear idea about the return generating variables and their influence will help the management to frame various policies to maximize the wealth of the shareholders.

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance

The construction of national identity as a developmental process from childhood to adolescence in Catalonia

La idea que per entendre alguna cosa hem d'entendre el procés pel qual s'ha produït va ser assumida des de l'origen de l'estudi "La construcció de la identitat nacional com a procés de desenvolupament des de la infància a l'adolescència a Catalunya". Per tal d'estudiar el procés de desenvolupament relacionat amb la construcció de la identitat nacional, no és suficient considerar-lo en el seu context social, sinó que és necessari considerar la seva construcció social. Tres objectius principals van orientar el nostre estudi . Primer, indagar si els processos de categorització, identificació, coneixement, imatge, avaluació i afecte són també elements implicats en la construcció de la identitat nacional des de la infància a l'adolescència. Segon investigar el procés de desenvolupament d'aquests elements des dels 6 anys fins als 15 anys per contribuir amb dades a I'explicació sobre com es desenvolupa del coneixement social. Tres són les explicacions principals; la primera que es basa en processos cognitius d'inclusió-decentració; la segona, si aquest desenvolupament es dóna en cercles concèntrics des de I'interior (contextos quotidians) fins a l'exterior (amb intercanvis més amples i una educació formal envers la vida social); i la tercera, si el desenvolupament del coneixement social d'allò més immediat i directe es reorganitzat i adquireix nous significats per la integració dels elements més generals i abstractes. Tercer, donat el fet que el 50% de les famílies tenen el català com a llengua materna, hem estudiat la influència de la llengua o llengües utilitzades en el context familiar en el procés de construcció de la identitat nacional. Es va dissenyar una entrevista individual seguint una estructura amb les parts següents: identificació subjectiva i identificació nacional; coneixement dels països; estereotips, avaluació i sentiments, i entorn social. La mostra del present estudi va estar formada per 495 nens i adolescents de 6, 9, 12 i 15 anys d'edat. Es va utilitzar per cada grup un número similar de nens i nenes. La mostra es va dividir en tres grups segons la o les llengües utilitzades pel nen o nena en el seu context familiar. Tres van ser les categones lingüístiques utilitzades: castellà, nens que només utilitzin el castellà a casa; català, nens que només usen el català en el context familiar; i bilingües, nens que utilitzin tots dos idiomes a casa. Aquestes categories lingüístiques s'han utilitzat com a indicador dels contextos familiars. Dues conclusions principals es poden extreure d'aquest estudi. Primer, I'ús de categories nacionals no és una conseqüència del procés cognitiu d'inclusió-decentració ni en cercles concentrics (concret/abstracte). La idea d'un procés del món en paral·lel, d'un coneixement que integra simultàniament creences i sentiments de l'ambient concret o proper i de l'abstracte o llunyà pot explicar millor els nostres resultats. Els nens aprenen i pensen sobre la vida quotidara, les característiques de l'ambient, la informació circulant en el seu entom social i la importància o els diferents nivells de coneixement depenent del context. Els nens integren la informació que està circulant en el seu ambient i construeixen un món que necessàriament no ha de coincidir amb el món deis adults, però que els ajuda a comunicar-se i a entendre les situacions en les quals estan immersos. Els nens més joves són capaços d'utilitzar categories nacionals de manera similar als adolescents. Segon, la identitat nacional a Catalunya es construeix al voltant del nucli de la llengua parlada a casa. A través de tot I'estudi es pot veure un resultat consistent i reiterat. Els infants d'un entom familiar en què s'usa només el castellà s'identifiquen com a pertanyents a tots dos grups nacionals, Espanyol i Català. Els infants d'un entom familiar que utilitzen només el català s'identifiquen com a pertanyents només al grup Català. Aquestes identificacions guien com aquests nens avaluen i senten envers el propi grup nacional i els altres. A més, sembla que el context sòcio-polític és un vehicle important en la transmissió de les estructures de semblances i que I'estructura d'afecte es transmet principalment a través de I'entom familiar.

The role of fungi and bacteria on the organic matter decomposition process in streams: interaction and relevance in biofilms

L'objectiu d'aquest estudi és el d'investigar sobre l'ús de matèria orgànica per part dels fongs i bacteris que colonitzen diferents substrats bentònics en rius Mediterranis i analitzar l'efecte dels factors ambientals i antròpics sobre l'estabilitat estructural i funcional de les comunitats del biofilm. La metodologia emprada en aquest estudi consisteix en: i) anàlisi de la biomassa bacteriana i fúngica, ii) anàlisi de la composició de les comunitats bentòniques (identificació d'hifomicets aquàtics i anàlisi del 16S rDNA bacterià), i iii) anàlisi de l'activitat enzimàtica extracel·lular relacionada amb el reciclatge de matèria orgànica en rius.

Incentives and Barriers to the Adoption of Digital Terrestrial Television in Portugal: Perspectives of the stakeholders involved in the transition process

The success of the transition from analogical terrestrial television to digital terrestrial television – process also known as switch-over – requires the identification of barriers and drivers among the impacted population. Therefore, the study in which this article is based had as main purpose to understand exactly what are those barriers, in order to produce a valid contribution to the several decision makers, and to be able to contribute to a more inclusive television, accessible and transversal to the whole of the population. In that sense, one of the phases of the project consisted in several interviews to key stakeholders in the transition process, the results of which and subsequent recommendations are presented in this article.

Identification of resilience factors in rail engineering work

This paper discusses an ongoing project that aims at improving the potential for resilience of a system responsible for the planning of rail engineering work delivery. It focuses on the use of a human factors based approach as a way to achieve this end. In particular, the paper discusses the initial data collected by means of interviews and how this process gave way to a two fold goal: Understanding how the planning process works in reality and identifying any critical aspects of the system from a Resilience Engineering perspective. Given the nature of the process under study, information flows and communication issues have been given particular attention throughout the data collection and analysis stages. Initial data confirms that the planning process is greatly reliant on the capability of people using their knowledge and skills to communicate in a dynamic informational environment. Finally, the added value of the interviews is discussed from a human factors perspective and as a mean towards the aim of better understanding resilience in rail engineering planning.

Biologically motivated model for object detection and identification in real-world scenes

The classical computer vision methods can only weakly emulate some of the multi-level parallelisms in signal processing and information sharing that takes place in different parts of the primates’ visual system thus enabling it to accomplish many diverse functions of visual perception. One of the main functions of the primates’ vision is to detect and recognise objects in natural scenes despite all the linear and non-linear variations of the objects and their environment. The superior performance of the primates’ visual system compared to what machine vision systems have been able to achieve to date, motivates scientists and researchers to further explore this area in pursuit of more efficient vision systems inspired by natural models. In this paper building blocks for a hierarchical efficient object recognition model are proposed. Incorporating the attention-based processing would lead to a system that will process the visual data in a non-linear way focusing only on the regions of interest and hence reducing the time to achieve real-time performance. Further, it is suggested to modify the visual cortex model for recognizing objects by adding non-linearities in the ventral path consistent with earlier discoveries as reported by researchers in the neuro-physiology of vision.

Proteome analysis for identification of target proteins of genistein in primary human endothelial cells stressed with oxidized LDL or homocysteine

Background Epidemiological studies suggest that soy consumption contributes to the prevention of coronary heart disease. The proposed anti-atherogenic effects of soy appear to be carried by the soy isoflavones with genistein as the most abundant compound. Aim of the study To identify proteins or pathways by which genistein might exert its protective activities on atherosclerosis, we analyzed the proteomic response of primary human umbilical vein endothelial cells ( HUVEC) that were exposed to the pro-atherosclerotic stressors homocysteine or oxidized low-density lipoprotein (ox-LDL). Methods HUVEC were incubated with physiological concentrations of homocysteine or ox-LDL in the absence and presence of genistein at concentrations that can be reached in human plasma by a diet rich in soy products (2.5 muM) or by pharmacological intervention ( 25 muM). Proteins from HUVEC were separated by two-dimensional polyacrylamide gel electrophoresis and those that showed altered expression level upon genistein treatment were identified by peptide mass fingerprints derived from tryptic digests of the protein spots. Results Several proteins were found to be differentially affected by genistein. The most interesting proteins that were potently decreased by homocysteine treatment were annexin V and lamin A. Annexin V is an antithrombotic molecule and mutations in nuclear lamin A have been found to result in perturbations of plasma lipids associated with hypertension. Genistein at low and high concentrations reversed the stressor-induced decrease of these anti-atherogenic proteins. Ox-LDL treatment of HUVEC resulted in an increase in ubiquitin conjugating enzyme 12, a protein involved in foam cell formation. Treatment with genistein at both doses reversed this effect. Conclusions Proteome analysis allows the identification of potential interactions of dietary components in the molecular process of atherosclerosis and consequently provides a powerful tool to define biomarkers of response.

The automatic identification and prioritisation of criminal networks from police crime data

The identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

A robust nonlinear identification algorithm using PRESS statistic and forward regression

This letter introduces a new robust nonlinear identification algorithm using the Predicted REsidual Sums of Squares (PRESS) statistic and for-ward regression. The major contribution is to compute the PRESS statistic within a framework of a forward orthogonalization process and hence construct a model with a good generalization property. Based on the properties of the PRESS statistic the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation.