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Dans un marché en permanente progression et pour répondre aux besoins des brasseurs en malt de qualité, la maîtrise du procédé de maltage est indispensable. La qualité du malt est fortement dépendante des conditions opératoires, en particulier des conditions de trempe, mais également de la qualité de la matière première : l'orge. Dans cette étude, nous avons établi des modèles polynomiaux qui mettent en relation les conditions opératoires et la qualité du malt. Ces modèles ont été couplés à nos algorithmes génétiques et nous ont permis de déterminer les conditions optimales de maltage, soit pour atteindre une qualité ciblée de malt (friabilité), soit pour permettre un maltage à faible teneur en eau (pour réduire la consommation en eau et maîtriser les coûts environnementaux de production) tout en conservant une qualité acceptable de malt. Cependant, la variabilité de la matière première est un facteur limitant de notre approche. Les modèles établis sont en effet très sensibles à l'espèce d'orge (printemps, hiver) ou encore à la variété d'orge utilisée. Les modèles sont surtout très dépendants de l'année de récolte. Les variations observées sur les propriétés d'une année de récolte à une autre sont mal caractérisées et ne sont donc pas intégrées dans nos modèles. Elles empêchent ainsi de capitaliser l'information expérimentale au cours du temps. Certaines propriétés structurelles de l'orge (porosité, dureté) ont été envisagées comme nouveaux facteurs pour mieux caractériser la matière première mais ils n'ont pas permis d'expliquer les variations observés en malterie.Afin de caractériser la matière première, 394 échantillons d'orge issus de 3 années de récolte différentes 2009-2010-2011 ont été analysés par spectroscopie MIR. Les analyses ACP ont confirmé l'effet notable des années de récolte, des espèces, des variétés voire des lieux de culture sur les propriétés de l'orge. Une régression PLS a permis, pour certaines années et pour certaines espèces, de prédire les teneurs en protéines et en béta-glucanes de l'orge à partir des spectres MIR. Cependant, ces résultats, pourtant prometteurs, se heurtent toujours à la variabilité. Ces nouveaux modèles PLS peuvent toutefois être exploités pour mettre en place des stratégies de pilotage du procédé de maltage à partir de mesures spectroscopiques MIR / In a continuously growing market and in order to meet the needs of Brewers in high quality malt, control of the malting process is a great challenge. Malt quality is highly dependent on the malting process operating conditions, especially on the steeping conditions, but also the quality of the raw material: barley. In this study, we established polynomial models that relate the operating conditions and the malt quality. These models have been coupled with our genetic algorithms to determine the optimal steeping conditions, either to obtain a targeted quality of malt (friability), or to allow a malting at low water content while maintaining acceptable quality of malt (to reduce water consumption and control the environmental costs of malt production). However, the variability of the raw material is a limiting factor for our approach. Established models are very sensitive to the species (spring and winter barley) or to the barley variety. The models are especially highly dependent on the crop year. Variations on the properties of a crop from one to another year are poorly characterized and are not incorporated in our models. They thus prevent us to capitalize experimental information over time. Some structural properties of barley (porosity, hardness) were considered as new factors to better characterize barley but they did not explain the observed variations.To characterize barley, 394 samples from 3 years of different crops 2009-2010-2011 were analysed by MIR spectroscopy. ACP analyses have confirmed the significant effect of the crop-years, species, varieties and sometimes of places of harvest on the properties of barley. A PLS regression allowed, for some years and for some species, to predict content of protein and beta-glucans of barley using MIR spectra. These results thus still face product variability, however, these new PLS models are very promising and could be exploited to implement control strategies in malting process using MIR spectroscopic measurements

Os avanços tecnológicos apontam para uma renovação da infraestrutura atual de comunicações ópticas, de modo a torná-la adequada à operação dentro dos novos paradigmas das redes, em que a elasticidade e eficiência espectrais se aliam à alta capacidade de transmissão. Sob o ponto de vista do planejamento de uma operadora de telecomunicação, é desejável que a substituição de equipamentos ocorra de forma mais gradual e que a operação da infraestrutura atual seja otimizada para acomodar a demanda por alta capacidade sem requerer a construção de uma infraestrutura completamente nova. Neste contexto, esta tese investiga estratégias de otimização combinando técnicas que utilizam múltiplas taxas de transmissão (MLR &#8211 Mixed Line Rate) e múltiplos formatos de modulação (MMF &#8211 Multiple Modulation Formats) com foco em um cenário condizente a realidade brasileira, com taxa de transmissão de 10 Gbit/s modulados com a técnica não retorna a zero (NRZ &#8211 non return to zero), migrando para taxa de 40 e/ou 100 Gbit/s. São analisados os benefícios proporcionados com o uso de redes MLR-MMF em comparação com a substituição da rede legada por apenas uma taxa (SLR &#8211 single line rate). A infraestrutura da camada física considerada é uniforme e pode transportar sinais de 10/40/100 Gbit/s, apenas os tipos de transponders são diferentes. Para analisar o desempenho da rede descrita é proposto um modelo de integração entre as ferramentas MatLab e OptiSystem. A primeira é utilizada para definir a rota e a segunda para simular a propagação do sinal óptico na fibra ao longo da rota escolhida. Os valores de taxa de erro de bit (BER &#8211 Bit Error Rate) e a relação sinal ruído óptica (OSNR &#8211 Optical Signal Noise Rate) são armazenados em um banco de dados para uso posterior. Dessa forma diversas topologias podem ser analisadas. Em uma rede real esse tipo de informação pode ser obtido por meio de técnicas de monitoramento óptico (OPM &#8211 Optical Performance Monitoring). Por esse motivo, também são investigados e testados experimentalmente dois métodos de monitoramento da OSNR: i) anulamento da polarização para obter OSNR e ii) monitor multiparâmetro baseado em modulação da polarização em baixa frequência. A partir das análises, concluiu-se que o uso de redes MLR-MMF pode ser uma alternativa para equilibrar o consumo energético e a probabilidade de bloqueio (PB). A opção por esse tipo de rede ajuda na economia energética e mantém a PB em níveis aceitáveis. Além disso, o uso de monitoramento óptico auxilia na obtenção de informações usadas para controlar e gerenciar eficientemente recursos de rede cumprindo os requisitos de qualidade de serviço. / Technological advances point out to an upgrade on the current optical communication infrastructure in order to adequate it to the new networks paradigms, where elasticity and spectral efficiency are associated to the high capacity transmission. From the perspective of a telecom operator planning, it is desirable that the equipment replacement occurs as gradually as possible and that the operation of the current infrastructure is optimized to accommodate the demand for high capacity without requiring the build-upof a completely new infrastructure. In this context, this thesis investigates optimization strategies combining MLR (mixed line rate) and MMF (multiple modulation formats) techniques focusing on a scenario similar to the Brazilian reality, with a transmission rate of 10 Gbit/s NRZ modulated, switching to a rate of 40 and/or 100 Gbit/s. The benefits provided by the use of MMF-MLR network (non return to zero)s compared to the replacing based on a legacy network by only one rate (SLR single line rate) are discussed. The infrastructure of the physical layer is considered uniform and can carry signals 10/40/100 Gbit/s, only the transponder configurations are different. To analyze the network performance we proposed an integration of MATLAB and OptiSystem tools. The first is used to define the route and the second to simulate the propagation of the optical signal in the fiber along the chosen route. The BER and OSNR values are stored in a database for later use. In this way several topologies can be analyzed. In a real network such information may be obtained by optical monitoring techniques (OPM). For this reason, two methods for monitoring OSNR are also investigated: i) the polarization nulling and ii) multiparameter monitor based on modulation of polarization at low frequency. From the analysis it was concluded that the use of MMF-MLR schemes can be an alternative to balance the energy consumption and the blocking probability (BP). The option for this type of network saves energy and helps maintaining BP within acceptable levels. Furthermore, the use of optical monitoring allows the gathering of information used to control and efficiently manage network resources meeting the requirements for quality of service.

Os avanços tecnológicos apontam para uma renovação da infraestrutura atual de comunicações ópticas, de modo a torná-la adequada à operação dentro dos novos paradigmas das redes, em que a elasticidade e eficiência espectrais se aliam à alta capacidade de transmissão. Sob o ponto de vista do planejamento de uma operadora de telecomunicação, é desejável que a substituição de equipamentos ocorra de forma mais gradual e que a operação da infraestrutura atual seja otimizada para acomodar a demanda por alta capacidade sem requerer a construção de uma infraestrutura completamente nova. Neste contexto, esta tese investiga estratégias de otimização combinando técnicas que utilizam múltiplas taxas de transmissão (MLR &#8211 Mixed Line Rate) e múltiplos formatos de modulação (MMF &#8211 Multiple Modulation Formats) com foco em um cenário condizente a realidade brasileira, com taxa de transmissão de 10 Gbit/s modulados com a técnica não retorna a zero (NRZ &#8211 non return to zero), migrando para taxa de 40 e/ou 100 Gbit/s. São analisados os benefícios proporcionados com o uso de redes MLR-MMF em comparação com a substituição da rede legada por apenas uma taxa (SLR &#8211 single line rate). A infraestrutura da camada física considerada é uniforme e pode transportar sinais de 10/40/100 Gbit/s, apenas os tipos de transponders são diferentes. Para analisar o desempenho da rede descrita é proposto um modelo de integração entre as ferramentas MatLab e OptiSystem. A primeira é utilizada para definir a rota e a segunda para simular a propagação do sinal óptico na fibra ao longo da rota escolhida. Os valores de taxa de erro de bit (BER &#8211 Bit Error Rate) e a relação sinal ruído óptica (OSNR &#8211 Optical Signal Noise Rate) são armazenados em um banco de dados para uso posterior. Dessa forma diversas topologias podem ser analisadas. Em uma rede real esse tipo de informação pode ser obtido por meio de técnicas de monitoramento óptico (OPM &#8211 Optical Performance Monitoring). Por esse motivo, também são investigados e testados experimentalmente dois métodos de monitoramento da OSNR: i) anulamento da polarização para obter OSNR e ii) monitor multiparâmetro baseado em modulação da polarização em baixa frequência. A partir das análises, concluiu-se que o uso de redes MLR-MMF pode ser uma alternativa para equilibrar o consumo energético e a probabilidade de bloqueio (PB). A opção por esse tipo de rede ajuda na economia energética e mantém a PB em níveis aceitáveis. Além disso, o uso de monitoramento óptico auxilia na obtenção de informações usadas para controlar e gerenciar eficientemente recursos de rede cumprindo os requisitos de qualidade de serviço. / Technological advances point out to an upgrade on the current optical communication infrastructure in order to adequate it to the new networks paradigms, where elasticity and spectral efficiency are associated to the high capacity transmission. From the perspective of a telecom operator planning, it is desirable that the equipment replacement occurs as gradually as possible and that the operation of the current infrastructure is optimized to accommodate the demand for high capacity without requiring the build-upof a completely new infrastructure. In this context, this thesis investigates optimization strategies combining MLR (mixed line rate) and MMF (multiple modulation formats) techniques focusing on a scenario similar to the Brazilian reality, with a transmission rate of 10 Gbit/s NRZ modulated, switching to a rate of 40 and/or 100 Gbit/s. The benefits provided by the use of MMF-MLR network (non return to zero)s compared to the replacing based on a legacy network by only one rate (SLR single line rate) are discussed. The infrastructure of the physical layer is considered uniform and can carry signals 10/40/100 Gbit/s, only the transponder configurations are different. To analyze the network performance we proposed an integration of MATLAB and OptiSystem tools. The first is used to define the route and the second to simulate the propagation of the optical signal in the fiber along the chosen route. The BER and OSNR values are stored in a database for later use. In this way several topologies can be analyzed. In a real network such information may be obtained by optical monitoring techniques (OPM). For this reason, two methods for monitoring OSNR are also investigated: i) the polarization nulling and ii) multiparameter monitor based on modulation of polarization at low frequency. From the analysis it was concluded that the use of MMF-MLR schemes can be an alternative to balance the energy consumption and the blocking probability (BP). The option for this type of network saves energy and helps maintaining BP within acceptable levels. Furthermore, the use of optical monitoring allows the gathering of information used to control and efficiently manage network resources meeting the requirements for quality of service.

Idag finns mängder av företag i olika branscher, stora som små, som vill förutsäga sin försäljning. Det kan bland annat bero på att de vill veta hur stort antal produkter de skall köpa in eller tillverka, och även vilka produkter som bör investeras i över andra. Vilka varor som är bra att investera i på kort sikt och vilka som är bra på lång sikt. Tidigare har detta gjorts med intuition och statistik, de flesta vet att skidjackor inte säljer så bra på sommaren, eller att strandprylar inte säljer bra under vintern. Det här är ett simpelt exempel, men hur blir det när komplexiteten ökar, och det finns ett stort antal produkter och butiker? Med hjälp av maskininlärning kan ett sånt här problem hanteras. En maskininlärningsalgoritm appliceras på en tidsserie, som är en datamängd med ett antal ordnade observationer vid olika tidpunkter under en viss tidsperiod. I den här studiens fall är detta försäljning av olika produkter som säljs i olika butiker och försäljningen ska prediceras på månadsbasis. Tidsserien som behandlas är ett dataset från Kaggle.com som kallas för “Predict Future Sales”. Algoritmerna som används i för den här studien för att hantera detta tidsserieproblem är XGBoost, MLP och MLR. XGBoost, MLR och MLP har i tidigare forskning gett bra resultat på liknande problem, där bland annat bilförsäljning, tillgänglighet och efterfrågan på taxibilar och bitcoin-priser legat i fokus. Samtliga algoritmer presterade bra utifrån de evalueringsmått som användes för studierna, och den här studien använder samma evalueringsmått. Algoritmernas prestation beskrivs enligt så kallade evalueringsmått, dessa är R², MAE, RMSE och MSE. Det är dessa mått som används i resultat- och diskussionskapitlen för att beskriva hur väl algoritmerna presterar. Den huvudsakliga forskningsfrågan för studien lyder därför enligt följande: Vilken av algoritmerna MLP, XGBoost och MLR kommer att prestera bäst enligt R², MAE, RMSE och MSE på tidsserien “Predict Future Sales”. Tidsserien behandlas med ett känt tillvägagångssätt inom området som kallas CRISP-DM, där metodens olika steg följs. Dessa steg innebär bland annat dataförståelse, dataförberedelse och modellering. Denna metod är vad som i slutändan leder till resultatet, där resultatet från de olika modellerna som skapats genom CRISP-DM presenteras. I slutändan var det MLP som fick bäst resultat enligt mätvärdena, följt av MLR och XGBoost. MLP fick en RMSE på 0.863, MLR på 1.233 och XGBoost på 1.262 / Today, there are a lot of companies in different industries, large and small, that want to predict their sales. This may be due, among other things, to the fact that they want to know how many products they should buy or manufacture, and also which products should be invested in over others. In the past, this has been done with intuition and statistics. Most people know that ski jackets do not sell so well in the summer, or that beach products do not sell well during the winter. This is a simple example, but what happens when complexity increases, and there are a large number of products and stores? With the help of machine learning, a problem like this can be managed easier. A machine learning algorithm is applied to a time series, which is a set of data with several ordered observations at different times during a certain time period. In the case of this study, it is the sales of different products sold in different stores, and sales are to be predicted on a monthly basis. The time series in question is a dataset from Kaggle.com called "Predict Future Sales". The algorithms used in this study to handle this time series problem are XGBoost, MLP and MLR. XGBoost, MLR and MLP. These have in previous research performed well on similar problems, where, among other things, car sales, availability and demand for taxis and bitcoin prices were in focus. All algorithms performed well based on the evaluation metrics used by the studies, and this study uses the same evaluation metrics. The algorithms' performances are described according to so-called evaluation metrics, these are R², MAE, RMSE and MSE. These measures are used in the results and discussion chapters to describe how well the algorithms perform. The main research question for the study is therefore as follows: Which of the algorithms MLP, XGBoost and MLR will perform best according to R², MAE, RMSE and MSE on the time series "Predict Future Sales". The time series is treated with a known approach called CRISP-DM, where the methods are followed in different steps. These steps include, among other things, data understanding, data preparation and modeling. This method is what ultimately leads to the results, where the results from the various models created by CRISP-DM are presented. In the end, it was the MLP algorithm that got the best results according to the measured values, followed by MLR and XGBoost. MLP got an RMSE of 0.863, MLR of 1,233 and XGBoost of 1,262

This master's thesis deals with the identification of the material flow curve from record of tensile test of smooth cylindrical specimen. First, necessary theory background is presented. Basic terms of incremental theory of plasticity, tensile test procedure and processing its outputs are described. Furthermore, possibilities of mathematical expression of the elastic-plastic material constitutive law, thus mathematical expression of the material flow curve itself. Mechanism of ductile damage of material is explained briefly as well. Overview of recent methods of the flow curve identification is given, focused on cases, when the stress distribution in a specimen is not uniaxial. That is either kind of analytic correction of basic formulas derived for uniaxial stress state, or application of mathematical optimization techniques combined with numerical simulation of the tensile test. Also unusual method of neural network is mentioned. For 8 given materials, the flow curve identification was performed using different methods. Namely by analytic correction, optimization, sequential identification and neural network. Algorithms of the last two methods were modified. Based on assessment of obtained results, application field and adjusting the parameters of single algorithms was recommended. It showed up, that an effective way to the accurate and credible results is the combination of different methods during flow curve identification procedure.

This thesis looks at how accurately one can model accents in jazz solos, more specifically the sound level. Further understanding the structure of jazz solos can give a way of pedagogically presenting differences within music styles and even between performers. Some studies have tried to model perceived accents in different music styles. In other words, model how listeners perceive some tones as somehow accentuated and more important than others. Other studies have looked at how the sound level correlates to other attributes of the tone. But to our knowledge, no other studies have been made modeling actual accents within jazz solos, nor have other studies had such a big amount of training data. The training data used is a set of 456 solos from the Weimar Jazz Database. This is a database containing tone data and metadata from monophonic solos performed with multiple instruments. The features used for the training algorithms are features obtained from the software Director Musices created at the Royal Institute of Technology in Sweden; features obtained from the software "melfeature" created at the University of Music Franz Liszt Weimar in Germany; and features built upon tone data or solo metadata from the Weimar Jazz Database. A comparison between these is made. Three learning algorithms are used, Multiple Linear Regression (MLR), Support Vector Regression (SVR), and eXtreme Gradient Boosting (XGBoost). The first two are simpler regression models while the last is an award-winning tree boosting algorithm. The tests resulted in eXtreme Gradient Boosting (XGBoost) having the highest accuracy when combining all the available features minus some features that were removed since they did not improve the accuracy. The accuracy was around 27% with a high standard deviation. This tells that there was quite some difference when predicting the different solos, some had an accuracy of about 67% while others did not predict one tone correctly in the entire solo. But as a general model, the accuracy is too low for actual practical use. Either the methods were not the optimal ones or jazz solos differ too much to find a general pattern. / Detta examensarbete undersöker hur väl man kan modellera accenter i jazz-solos, mer specifikt ljudnivån. En bredare förståelse för strukturen i jazzsolos kan ge ett sätt att pedagogiskt presentera skillnaderna mellan olika musikstilar och även mellan olika artister. Andra studier har försökt modellera uppfattade accenter inom olika musik-stilar. Det vill säga, modellera hur åhörare upplever vissa toner som accentuerade och viktigare än andra. Andra studier har undersökt hur ljudnivån är korrelerad till andra attribut hos tonen. Men såvitt vi vet, så finns det inga andra studier som modellerar faktiska accenter inom jazzsolos, eller som haft samma stora mängd träningsdata. Träningsdatan som använts är ett set av 456 solos tagna från Weimar Jazz Database. Databasen innehåller data på toner och metadata från monofoniska solos genomförda med olika instrument. Särdragen som använts för tränings-algoritmerna är särdrag erhållna från mjukvaran Director Musices skapad på Kungliga Tekniska Högskolan i Sverige; särdrag erhållna från mjukvaran ”melfeature” skapad på University of Music Franz Liszt Weimar i Tyskland; och särdrag skapade utifrån datat i Weimar Jazz Database. En jämförelse mellan dessa har också gjorts. Tre inlärningsalgoritmer har använts, Multiple Linear Regression (MLR), Support Vector Regression (SVR), och eXtreme Gradient Boosting (XGBoost). De första två är enklare regressionsalgoritmer, medan den senare är en prisbelönt trädförstärkningsalgoritm. Testen resulterade i att eXtreme Gradient Boosting (XGBoost) skapade en modell med högst noggrannhet givet alla tillgängliga särdrag som träningsdata minus vissa särdrag som tagits bort då de inte förbättrar noggrannheten. Den erhållna noggrannheten låg på runt 27% med en hög standardavvikelse. Detta pekar på att det finns stora skillnader mellan att förutsäga ljudnivån mellan de olika solin. Vissa solin gav en noggrannhet på runt 67% medan andra erhöll inte en endaste ljudnivå korrekt i hela solot. Men som en generell modell är noggrannheten för låg för att användas i praktiken. Antingen är de valda metoderna inte de bästa, eller så är jazzsolin för olika för att hitta ett generellt mönster som går att förutsäga.

Orthotropic steel deck has been widely used over the decades especially on long-span bridges due to its light weight and fast construction. However fatigue cracking problems on the welds have been observed in many countries. Rib-to-deck welds need special care since they are directly under wheel loads, which cause large local stress variations and stress reversals. Currently the only requirement by AASHTO bridge code is that the rib-to-deck welds need to be fabricated as one-sided partial penetration welds with minimum penetration of 80% into the rib wall thickness. However considering the thin rib plate thickness, it is very difficult to achieve this penetration without a "melt-through" or "blow-through" defect. Large cost has been caused for the repair. However recent research has found that the fatigue performance of the rib-to-deck weld is not directly related to its penetration. Other factors contribute to the fatigue performance as well. Therefore, alternative requirements which are more cost-effective and rational are desired. The objective of this research is to provide recommendations to the design and fabrication of rib-to-deck welds by investigating their fatigue performance with different weld dimensions, penetrations, and welding processes. Fatigue tests were performed to 95 full-scale single-rib deck segments in 8 specimen series fabricated with different welding processes and root gap openness. Specimens were tested under cyclic loads till failure. Three failure modes were observed on both weld toes and the weld root. Test results showed that the fatigue performance was more affected by other factors such as failure mode, R-ratio and root gap openness, rather than the weld penetration. The failure cycles were recorded for the following S-N curve analysis. Finite element analysis was performed to determine the stress state on the fatigue cracking locations. Special considerations were made for the application of hot-spot stress methodology, which post-processes the FEA results to calculate the stress values at cracking locations with the structural configuration taken into account. The hot-spot stress range values were derived and adjusted accounting for the fabrication and test error. Hot-spot S-N curves were established for each specimen series. Statistical analyses were performed to study in depth the effect of weld dimensions and test scenarios. Multiple linear regression (MLR) was performed to investigate the effects of different weld dimensions; and multi-way analysis of covariance (Multi-way ANCOVA) for the effects of specimen series, failure mode, R-ratio and weld root gap. It was found that the weld toe size was more relevant to the fatigue performance, other than the weld penetration. The failure mode and R-ratio were very influential on the fatigue performance. Recommendations to the weld geometry were proposed based on the MLR model fitting. S-N data were re-categorized based on ANCOVA results and the lower-bound S-N curve was established. AASHTO C curve was recommended for the deck design. / Master of Science

La réaction du greffon contre l’hôte (GvH) est responsable d’un grand taux de morbidité et de mortalité chez les patients recevant des greffes de cellules souches (GCSH) allogéniques. Dans ce contexte, les cellules T régulatrices sont largement étudiées et semblent avoir un grand potentiel d’utilisation dans le domaine de la thérapie cellulaire de la GvH. Parmi les populations cellulaires T régulatrices, les lymphocytes T CD4-CD8- TCRαβ+ « Doubles-Négatifs » (DN), qui ne représentent que 1-3% des lymphocytes T, ont été décrits. Ces cellules ont des propriétés inhibitrices de la réponse immunitaire qui s’avèrent spécifiques aux antigènes auxquels elles ont préalablement été exposées. La répression de la réponse immunitaire par les cellules T DN régulatrices semble être un mécanisme important impliqué dans l’induction de la tolérance aux allo-antigènes. De plus, ces cellules confèrent une tolérance immunitaire dans des modèles de greffes allogéniques et xénogéniques. En effet, ces cellules ont la capacité d’inhiber la réaction contre un allo-antigène auquel elles ont été exposées, sans inhiber la réaction contre un allo-antigène inconnu. Les cellules T DN ont été isolées et caractérisées chez l’homme où elles ont la capacité d’interagir avec des cellules présentatrices d’antigènes (APCs) par un contact cellulaire, comme chez la souris. Cependant, leur capacité immunomodulatrice reste inconnue chez l’humain. Notre objectif consistait donc principalement à étudier le rôle et le mécanisme d’action des cellules T DN régulatrices humaines in vitro, en étudiant leur capacité à inhiber une réaction lymphocytaire mixte (MLR). Nous avons montré que les cellules T DN stimulées par un allo-antigène donné inhibent des cellules syngéniques effectrices dirigées contre ce même alloantigène mais n’inhibent pas des cellules syngéniques effectrices dirigées contre un autre alloantigène, démontrant ainsi la spécificité aux antigènes de ces cellules. De plus, les T DN non stimulées par un allo-antigène n’ont pas de rôle inhibiteur. Cependant, durant cette inhibition, nous n’observons pas de modulation de l’expression des marqueurs d’activation et d’induction de l’apoptose. Afin d’étudier le mécanisme d’action des cellules T DN, nous avons mesuré l’expression intracellulaire de la granzyme B. Les résultats démontrent que les cellules T DN stimulées expriment un niveau significativement plus élevé de granzyme B que les cellules T DN non-stimulées par l’allo-antigène. Ceci suggère que l’immunosuppression induite par les cellules T DN stimulées pourrait passer par la voie granzyme B. Le mécanisme utilisé par ces cellules reste à être confirmé par nos futures expériences. / Graft-versus-Host Disease (GvHD) is a major cause of morbidity and mortality in patients receiving an allogeneic Hematopoietic Stem Cell Transplantation (HSCT). Many regulatory T cell populations have been studied and shown to have immunosuppressive properties in GvHD. Among these populations, Double Negative CD4-CD8-TCRαβ+ regulatory T cells (DN T) have been described. These cells represent 1-3% of all T cell lymphocytes and are known to have antigen-specific inhibitory functions of the immune response. The suppression of an immune response by DN T cells seems to be an important mechanism involved in the induction of tolerance to allo-antigens. Moreover, these cells also confer immune tolerance in models of allogeneic and xenogenic grafts. DN T cells have the ability to suppress syngeneic T CD4+ and T CD8+ cells in an antigen-specific manner. Therefore, these DN T cells can inhibit the reaction caused by syngeneic effector cells against a specific alloantigen to which they have been previously exposed. However, they cannot inhibit a reaction directed against an unknown alloantigen. Human DN T cells have been isolated and characterized as cells that have the capacity to interact with APCs by cell-to-cell contact, just like in mice. However, their immunomodulatory properties are still unknown in humans. The goal of our project was to study the role and immunomodulatory functions of human DN T cells in Mixed Lymphocyte Reactions (MLR). The MLRs have allowed us to demonstrate that DN T cells, after having been stimulated by an allo-antigen, have an antigen-specific inhibitory function towards the syngeneic effector cells reacting against the same alloantigen that they have been exposed to. Interestingly, they do not inhibit the reaction of these effector cells against an unknown alloantigen. However, stimulated DN T cells did not modulate the expression of the activation markers expressed by the effector cells and did not give a death signal to these cells either. Moreover, we also wanted to study how DN T cells have an immunosuppressive activity. Therefore, we compared the expression of Granzyme B in stimulated versus non-stimulated cells. Our results suggest that DN T cells may use the Granzyme B pathway to immunosuppress the effector cells. In conclusion, our results demonstrate that DN T cells have an antigen-specific inhibitory function. The mechanism used by these DN T cells remains to be confirmed with our future experiments.

Les résultats basés sur les mesures d'ondes 'électromagnétiques effectuées par le satellite DEMETER sont présentés. Nous nous concentrons sur deux phénomènes différents : 1) les effets liés à l'activité sismique 2) les 'émissions avec des structures fréquentielles linéaires. 1) Nous présentons une étude statistique de l'intensité des ondes électromagnétiques observées à proximité des tremblements de terre. Nous montrons que pendant la nuit il y a une diminution statistiquement significative de l'intensité des ondes peu avant le choc principal. 2) Nous présentons une étude systématique des événements ayant des structures fréquentielles linéaires. Un ensemble d'événements statistiquement significatif a 'été obtenu en utilisant une procédure automatique ainsi qu'une inspection visuelle des données. Tous les événements sont entièrement analysés et classifiés. Dans la gamme EBF (ou toutes les six composantes électromagnétiques sont mesurées pendant le mode Burst), une analyse détaillée des ondes a été faite.