The conservative physiology of the immune system

Current immunological opinion disdains the necessity to define global interconnections between lymphocytes and regards natural autoantibodies and autoreactive T cells as intrinsically pathogenic. Immunological theories address the recognition of foreignness by independent clones of lymphocytes, not the relations among lymphocytes or between lymphocytes and the organism. However, although extremely variable in cellular/molecular composition, the immune system preserves as invariant a set of essential relations among its components and constantly enacts contacts with the organism of which it is a component. These invariant relations are reflected, for example, in the life-long stability of profiles of reactivity of immunoglobulins formed by normal organisms (natural antibodies). Oral contacts with dietary proteins and the intestinal microbiota also result in steady states that lack the progressive quality of secondary-type reactivity. Autoreactivity (natural autoantibody and autoreactive T cell formation) is also stable and lacks the progressive quality of clonal expansion. Specific immune responses, currently regarded as the fundament of the operation of the immune system, may actually result from transient interruptions in this stable connectivity among lymphocytes. More permanent deficits in interconnectivity result in oligoclonal expansions of T lymphocytes, as seen in Omenn's syndrome and in the experimental transplantation of a suboptimal diversity of syngeneic T cells to immunodeficient hosts, which also have pathogenic consequences. Contrary to theories that forbid autoreactivity as potentially pathogenic, the physiology of the immune system is conservative and autoreactive. Pathology derives from failures of these conservative mechanisms.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

A carbohydrate-based mechanism of species recognition in sea urchin fertilization

In the present review, we describe a systematic study of the sulfated polysaccharides from marine invertebrates, which led to the discovery of a carbohydrate-based mechanism of sperm-egg recognition during sea urchin fertilization. We have described unique polymers present in these organisms, especially sulfated fucose-rich compounds found in the egg jelly coat of sea urchins. The polysaccharides have simple, linear structures consisting of repeating units of oligosaccharides. They differ among the various species of sea urchins in specific patterns of sulfation and/or position of the glycosidic linkage within their repeating units. These polysaccharides show species specificity in inducing the acrosome reaction in sea urchin sperm, providing a clear-cut example of a signal transduction event regulated by sulfated polysaccharides. This distinct carbohydrate-mediated mechanism of sperm-egg recognition coexists with the bindin-protein system. Possibly, the genes involved in the biosynthesis of these sulfated fucans did not evolve in concordance with evolutionary distance but underwent a dramatic change near the tip of the Strongylocentrotid tree. Overall, we established a direct causal link between the molecular structure of a sulfated polysaccharide and a cellular physiological event - the induction of the sperm acrosome reaction in sea urchins. Small structural changes modulate an entire system of sperm-egg recognition and species-specific fertilization in sea urchins. We demonstrated that sulfated polysaccharides - in addition to their known function in cell proliferation, development, coagulation, and viral infection - mediate fertilization, and respond to evolutionary mechanisms that lead to species diversity.

Observations of Acoustic Emission in Power Semiconductors

Industrial, electrical power generation, and transportation systems, to name but a few, rely heavily on power electronics to control and convert electrical power. Each of these systems, when encountering an unexpected failure, can cause significant financial losses, or even an emergency. A condition monitoring system would help to alleviate these concerns, but for the time being, there is no generally accepted and widely adopted method for power electronics. Acoustic emission is used as a failure precursor in many applications, but it has not been studied in power electronics so far. In this doctoral dissertation, observations of acoustic emission in power semiconductor components are presented. The acoustic emissions are caused by the switching operation and failure of power transistors. Three types of acoustic emission are observed. Furthermore, aspects related to the measurement and detection of acoustic phenomena are discussed. These include sensor performance and mechanical construction of experimental setups. The results presented in this dissertation are the outset of a research program where it will be determined whether an acoustic-emission-based condition monitoring method can be developed.

Design and implementation of machine vision system for the mobile assembly robot

The review of intelligent machines shows that the demand for new ways of helping people in perception of the real world is becoming higher and higher every year. This thesis provides information about design and implementation of machine vision for mobile assembly robot. The work has been done as a part of LUT project in Laboratory of Intelligent Machines. The aim of this work is to create a working vision system. The qualitative and quantitative research were done to complete this task. In the first part, the author presents the theoretical background of such things as digital camera work principles, wireless transmission basics, creation of live stream, methods used for pattern recognition. Formulas, dependencies and previous research related to the topic are shown. In the second part, the equipment used for the project is described. There is information about the brands, models, capabilities and also requirements needed for implementation. Although, the author gives a description of LabVIEW software, its add-ons and OpenCV which are used in the project. Furthermore, one can find results in further section of considered thesis. They mainly represented by screenshots from cameras, working station and photos of the system. The key result of this thesis is vision system created for the needs of mobile assembly robot. Therefore, it is possible to see graphically what was done on examples. Future research in this field includes optimization of the pattern recognition algorithm. This will give less response time for recognizing objects. Presented by author system can be used also for further activities which include artificial intelligence usage.

Clinician-Perceived Bridges and Barriers to Parental Implementation of Picture Exchange Communication System (PECS): An evaluation.

Picture Exchange Communication System (PECS) is an augmentative and alternative communicative system that improves communication and decreases problem behaviors in children with Developmental Disabilities and Autism. The mediator model is a validated approach that clinicians use to train parents to perform evidence-based interventions. Parental non-adherence to treatment recommendations is a documented problem. This qualitative study investigated clinician-perceived factors that influence parental adherence to PECS recommendations. Three focus groups (n=8) were conducted with Speech Language Pathologists and Behavior Therapists experienced in providing parents with PECS recommendations. Constant comparison analysis was used. In general, clinicians believed that PECS was complex to implement. Thirty-one bridges were identified to overcome complexity. Twenty-two barriers and 6 other factors also impacted parental adherence. Strategies to address these factors were proposed based on a review of the literature. Future research will be performed to validate these findings using parents and a larger sample size.

Speech - Beaver Bill, 21 February 1975

A speech by Sean O'Sullivan, given in the House of Commons, "For the Recognition of the Beaver as a Symbol of the Sovereignty of the Dominion of Canada".

Ontogénèse et spécificité de la voix humaine

La voix est un stimulus auditif omniprésent dans notre environnement sonore. Elle permet non seulement la parole, mais serait aussi l’équivalent d’un visage auditif transmettant notamment des informations identitaires et affectives importantes. Notre capacité à discriminer et reconnaître des voix est socialement et biologiquement importante et elle figure parmi les fonctions les plus importantes du système auditif humain. La présente thèse s’intéressait à l’ontogénèse et à la spécificité de la réponse corticale à la voix humaine et avait pour but trois objectifs : (1) mettre sur pied un protocole électrophysiologique permettant de mesurer objectivement le traitement de la familiarité de la voix chez le sujet adulte; (2) déterminer si ce même protocole pouvait aussi objectiver chez le nouveau-né de 24 heures un traitement préférentiel d’une voix familière, notamment la voix de la mère; et (3) mettre à l’épreuve la robustesse d’une mesure électrophysiologique, notamment la Fronto-Temporal Positivity to Voices, s’intéressant à la discrimination pré-attentionnelle entre des stimuli vocaux et non-vocaux. Les résultats découlant des trois études expérimentales qui composent cette thèse ont permis (1) d’identifier des composantes électrophysiologiques (Mismatch Negativity et P3a) sensibles au traitement de la familiarité d’une voix; (2) de mettre en lumière un patron d’activation corticale singulier à la voix de la mère chez le nouveau-né, fournissant le premier indice neurophysiologique de l’acquisition du langage, processus particulièrement lié à l’interaction mère-enfant; et (3) de confirmer l’aspect pré-attentionnel de la distinction entre une voix et un stimulus non-vocal tout en accentuant la sélectivité et la sensibilité de la réponse corticale réservée au traitement de la voix.

Excitabilité du système miroir : une étude de stimulation magnétique transcrânienne sur le chant et le langage

La perception de mouvements est associée à une augmentation de l’excitabilité du cortex moteur humain. Ce système appelé « miroir » sous-tendrait notre habileté à comprendre les gestes posés par une tierce personne puisqu’il est impliqué dans la reconnaissance, la compréhension et l’imitation de ces gestes. Dans cette étude, nous examinons de quelle façon ce système miroir s’implique et se latéralise dans la perception du chant et de la parole. Une stimulation magnétique transcrânienne (TMS) à impulsion unique a été appliquée sur la représentation de la bouche du cortex moteur de 11 participants. La réponse motrice engendrée a été mesurée sous la forme de potentiels évoqués moteurs (PÉMs), enregistrés à partir du muscle de la bouche. Ceux-ci ont été comparés lors de la perception de chant et de parole, dans chaque hémisphère cérébral. Afin d’examiner l’activation de ce système moteur dans le temps, les impulsions de la TMS ont été envoyées aléatoirement à l’intérieur de 7 fenêtres temporelles (500-3500 ms). Les stimuli pour la tâche de perception du chant correspondaient à des vidéos de 4 secondes dans lesquelles une chanteuse produisait un intervalle ascendant de deux notes que les participants devaient juger comme correspondant ou non à un intervalle écrit. Pour la tâche de perception de la parole, les participants regardaient des vidéos de 4 secondes montrant une personne expliquant un proverbe et devaient juger si cette explication correspondait bien à un proverbe écrit. Les résultats de cette étude montrent que les amplitudes des PÉMs recueillis dans la tâche de perception de chant étaient plus grandes après stimulation de l’hémisphère droit que de l’hémisphère gauche, surtout lorsque l’impulsion était envoyée entre 1000 et 1500 ms. Aucun effet significatif n’est ressorti de la condition de perception de la parole. Ces résultats suggèrent que le système miroir de l’hémisphère droit s’active davantage après une présentation motrice audio-visuelle, en comparaison de l’hémisphère gauche.

Recognition of Facial Expressions with Autoencoders and Convolutional-Nets

Les humains communiquent via différents types de canaux: les mots, la voix, les gestes du corps, des émotions, etc. Pour cette raison, un ordinateur doit percevoir ces divers canaux de communication pour pouvoir interagir intelligemment avec les humains, par exemple en faisant usage de microphones et de webcams. Dans cette thèse, nous nous intéressons à déterminer les émotions humaines à partir d’images ou de vidéo de visages afin d’ensuite utiliser ces informations dans différents domaines d’applications. Ce mémoire débute par une brève introduction à l'apprentissage machine en s’attardant aux modèles et algorithmes que nous avons utilisés tels que les perceptrons multicouches, réseaux de neurones à convolution et autoencodeurs. Elle présente ensuite les résultats de l'application de ces modèles sur plusieurs ensembles de données d'expressions et émotions faciales. Nous nous concentrons sur l'étude des différents types d’autoencodeurs (autoencodeur débruitant, autoencodeur contractant, etc) afin de révéler certaines de leurs limitations, comme la possibilité d'obtenir de la coadaptation entre les filtres ou encore d’obtenir une courbe spectrale trop lisse, et étudions de nouvelles idées pour répondre à ces problèmes. Nous proposons également une nouvelle approche pour surmonter une limite des autoencodeurs traditionnellement entrainés de façon purement non-supervisée, c'est-à-dire sans utiliser aucune connaissance de la tâche que nous voulons finalement résoudre (comme la prévision des étiquettes de classe) en développant un nouveau critère d'apprentissage semi-supervisé qui exploite un faible nombre de données étiquetées en combinaison avec une grande quantité de données non-étiquetées afin d'apprendre une représentation adaptée à la tâche de classification, et d'obtenir une meilleure performance de classification. Finalement, nous décrivons le fonctionnement général de notre système de détection d'émotions et proposons de nouvelles idées pouvant mener à de futurs travaux.

Recognition of hepatitis C virus RNA by toll like receptors 7 and 8 : implications for the initiation of innate immune response

Le virus de l’hépatite C (VHC) est un virus à ARN simple brin positif (ssARN) qui se replique dans le foie. Deux cents millions de personnes sont infectées par le virus dans le monde et environ 80% d’entre elles progresseront vers un stade chronique de l’infection. Les thérapies anti-virales actuelles comme l’interféron (IFN) ou la ribavirin sont de plus en plus utilisées mais ne sont efficaces que dans la moitié des individus traités et sont souvent accompagnées d’une toxicité ou d’effets secondaires indésirables. Le système immunitaire inné est essentiel au contrôle des infections virales. Les réponses immunitaires innées sont activées suite à la reconnaissance par les Pathogen Recognition Receptors (PRRs), de motifs macromoléculaires dérivés du virus appelés Pathogen-Associated Molecular Patterns (PAMPs). Bien que l'activation du système immunitaire par l'ARN ou les protéines du VHC ait été largement étudiée, très peu de choses sont actuellement connues concernant la détection du virus par le système immunitaire inné. Et même si l’on peut très rapidement déceler des réponses immunes in vivo après infection par le VHC, l’augmentation progressive et continue de la charge virale met en évidence une incapacité du système immunitaire à contrôler l’infection virale. Une meilleure compréhension des mécanismes d’activation du système immunitaire par le VHC semble, par conséquent, essentielle au développement de stratégies antivirales plus efficaces. Dans le présent travail nous montrons, dans un modèle de cellule primaire, que le génome ARN du VHC contient des séquences riches en GU capables de stimuler spécifiquement les récepteurs de type Toll (TLR) 7 et 8. Cette stimulation a pour conséquence la maturation des cellules dendritiques plasmacytoïdes (pDCs), le production d’interféron de type I (IFN) ainsi que l’induction de chémokines et cytokines inflammatoires par les différentes types de cellules présentatrices d’antigènes (APCs). Les cytokines produites après stimulation de monocytes ou de pDCs par ces séquences ssARN virales, inhibent la production du virus de façon dépendante de l’IFN. En revanche, les cytokines produites après stimulation de cellules dendritiques myéloïdes (mDCs) ou de macrophages par ces mêmes séquences n’ont pas d’effet inhibiteur sur la production virale car les séquences ssARN virales n’induisent pas la production d’IFN par ces cellules. Les cytokines produites après stimulation des TLR 7/8 ont également pour effet de diminuer, de façon indépendante de l’IFN, l’expression du récepteur au VHC (CD81) sur la lignée cellulaire Huh7.5, ce qui pourrait avoir pour conséquence de restreindre l’infection par le VHC. Quoiqu’il en soit, même si les récepteurs au VHC comme le CD81 sont largement exprimés à la surface de différentes sous populations lymphocytaires, les DCs et les monocytes ne répondent pas aux VHC, Nos résultats indiquent que seuls les macrophages sont capables de reconnaître le VHC et de produire des cytokines inflammatoires en réponse à ce dernier. La reconnaissance du VHC par les macrophages est liée à l’expression membranaire de DC-SIGN et l’engagement des TLR 7/8 qui en résulte. Comme d’autres agonistes du TLR 7/8, le VHC stimule la production de cytokines inflammatoires (TNF-α, IL-8, IL-6 et IL-1b) mais n’induit pas la production d’interféron-beta par les macrophages. De manière attendue, la production de cytokines par des macrophages stimulés par les ligands du TLR 7/8 ou les séquences ssARN virales n’inhibent pas la réplication virale. Nos résultats mettent en évidence la capacité des séquences ssARN dérivées du VHC à stimuler les TLR 7/8 dans différentes populations de DC et à initier une réponse immunitaire innée qui aboutit à la suppression de la réplication virale de façon dépendante de l’IFN. Quoiqu’il en soit, le VHC est capable d’échapper à sa reconnaissance par les monocytes et les DCs qui ont le potentiel pour produire de l’IFN et inhiber la réplication virale après engagement des TLR 7/8. Les macrophages possèdent quant à eux la capacité de reconnaître le VHC grâce en partie à l’expression de DC-SIGN à leur surface, mais n’inhibent pas la réplication du virus car ils ne produisent pas d’IFN. L’échappement du VHC aux défenses antivirales pourrait ainsi expliquer l’échec du système immunitaire inné à contrôler l’infection par le VHC. De plus, la production de cytokines inflammatoires observée après stimulation in vitro des macrophages par le VHC suggère leur potentielle contribution dans l’inflammation que l’on retrouve chez les individus infectés par le VHC.

Studies on Rubber Composition as Passive Acoustic Materials in Underwater Electro Acoustic Tranducer Technology and Their aging Characteristic

The research work has been in the area of compounding and characterization of rubbers for use in under water electro acoustic transducers. The study also covers specific material system such as encapsulation materials, baffle material, seal material, etc. Life prediction techniques of under water rubbers in general have been established with reference to more than one functional property. Ranges of passive materials, besides the active sensing material go into the construction of underwater electro acoustic transducers. Reliability of the transducer is critically dependent on these passive materials. Rubbers are a major class of passive materials. The present work concentrates on these materials. Conventional rubbers are inadequate to meet many of the stringent function specific requirements. There exists a large gap of information in the rubber technology of underwater rubbers, particularly relating to underwater electro acoustic transducers. This study is towards filling up the gaps of information in this crucial area. Water intake into rubber is considered as the single most important issue for the long-term performance of rubbers, especially Neoprene. In this study, the cause and effects of a range of parameters affecting the water absorption by diffusion and permeation have been investigated.

Speech Analysis using Modern Techniques of Nonlinear Dynamics

Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.

Permutation Entropy Based Analysis of Complex Signals for Characterising Change in System Dynamics

Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.

Studies on rubber compositions as passive acoustic materials in underwater electro acoustic transducer technology-and their aging characteristics

Rubber has become an indispensable material in Ocean technology. Rubber components play critical roles such as sealing, damping, environmental protection, electrical insulation etc. in most under water engineering applications. Technology driven innovations in electro acoustic transducers and other sophisticated end uses have enabled quantum jump in the quality and reliability of rubber components. Under water electro acoustic transducers use rubbers as a critical material in their construction. Work in this field has lead to highly reliable and high performance materials which has enhanced service life of transducers to the extent of 1015 years. Present work concentrates on these materials. Conventional rubbers are inadequate to meet many of the stringent functional of the requirements. There exists large gap of information in the rubber technology of under water rubbers, particularly in the context of under water electro acoustic transducers. Present study is towards filling up the gaps of information in this crucial area. The research work has been in the area of compounding and characterisation of rubbers for use in under water electro acoustic transducers. The study also covers specific material system such as encapsulation material, baffle material, seal material, etc. Life prediction techniques of under water rubbers in general has been established with reference to more than one functional property. This thesis is divided into 6 chapters.