Titan is a unique moon in the solar system as it is the only one with a thick atmo- sphere, and surface lakes and seas. Observations made by the Cassini/Huygens probe showed the potential of a subsurface ocean hidden below the outer crust made of ice. This thesis analyzes the heat transfer through the crust of Titan to understand the long term evolution of the ocean. We developed a finite element model of the heat transfer through a thickening ice crust and investigated the effect of viscosity, internal heat flux, and ammonia concentration in the ocean. While other explanations cannot be ruled out, it was found high values of viscosity and possible ammonia presence could keep the ocean liquid for long periods. 1

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This thesis studies the monohydrate, dihydrate and in some cases, trihydrate of five carboxylic acids, namely acetic acid, propanoic acid, T-difluoroacetic acid, Gdifluoroacetic acid and trifluoacetic acid using the technique of Fourier tranform microwave spectroscopy. The rotational and centrifugal distortion constants of these hydrates were determined with high accuracy. Ab initio calculations were also performed to locate the different conformational minima of the hydrates and to optimize their structures. Comparison of the ab initio predicted rotational and centrifugal distortion constants with the experimentally observed values allows us to determine the structures of the global minimum conformations of the various hydrates without ambiguity. Hydrogen-bonded ring structures are found to be the predominant feature in all observed hydrates. In this structural arrangement, all the hydrogen bonds formed are located in the same ring, and the cooperativity effect between them significantly strengthens each hydrogen bond, as suggested by the sharp increase of their binding energies in the larger hydrates. The fine and hyperfine splittings observed in the specrum were also successfully analyzed, which allows information on the dynamics of the intramolecular large amplitude tunnelling motions to be extracted explicitly. In the final part of this thesis, the equilibrium constants for the formation of monohydrates of the different carboxylic acids involved in this thesis, together with that of formic acid whose microwave spectrum has been analyzed elsewhere, were calculated to approximately derive their abundances under typical atmospheric conditions. It was found that about 2% of FMA, ACA and PPA will complex with one H2O molecule to form monohydrates in the low troposphere, while for TFA, the value increases to about 15%, mainly as a result of the larger binding energy of TFA–(H2O) due to fluorination on the end group.

La connaissance de la dynamique interne du noyau d’une cellule vivante semble essentielle pour la compréhension du fonctionnement des cellules eucaryotes. Ainsi, depuis plus d'une quinzaine d’année, de nombreuses études ont été menées pour sonder cette dynamique. Le projet de recherche de cette thèse s’est inscrit dans cette problématique. Nous avons monté une expérience originale de diffusion dynamique de la lumière pour sonder la dynamique interne du noyau d’une cellule. Le principe est simple, nous faisons passer un faisceau laser à travers le noyau d’une cellule et nous détectons les variations temporelles de l’intensité lumineuse diffusée. Les signaux obtenus sont complexes, non stationnaires, avec plusieurs échelles de temps. Une partie importante du travail de thèse a consisté à trouver une manière fiable de les analyser pour en extraire la dynamique interne du noyau ; nous arrivons à sonder cette dynamique sur quasiment 7 ordres de grandeurs (10-5 – 40 s). En utilisant ce montage et les techniques de traitement du signal qu’on a développé, nous avons étudié la dynamique interne du noyau de cellules issues de deux lignées humaines (SHEP et HeLa) au cours de leur cycle cellulaire. Nous observons des différences notables entre les phases G1, S et G2 et nous pouvons voir les gammes de temps affectées par le changement de phase du cycle cellulaire. Ensuite, nous avons étudié la dynamique du noyau de cellules (SHEP et HeLa), en phase G1, en présence d’une drogue cytobloquante dans le milieu de culture. Nous avons aussi étudié l’effet de la température. Pour des cellules en phase G1, nous avons baissé la température de 37°C à 25° C. Nous avons pu suivre l’évolution de la dynamique lors du refroidissement et à 25°C. Enfin, nous avons étudié la dynamique du noyau des cellules SHEP et HELA fixées. / The knowledge of the internal dynamics of a living cell nucleus appears essential for the comprehension of the activity of eukaryotic cells. Therefore, for the last fifteen years, many studies have been conducted to probe this dynamics. The research project of this thesis is a part of this issue. We set up an original experience of dynamic light scattering to probe the internal dynamics of a cell nucleus. The principle is simple, we pass a laser beam through the nucleus of a cell and we detect the temporal variations of the scattered light intensity. The signals obtained are complex, non-stationary, with different time scales. An important part of the thesis was to find a reliable way to analyze them to extract the internal dynamic of the nucleus; we can probe this dynamic on almost 7 orders of magnitude (10-5 – 40 s). By using this experience and the signal procession techniques that we developed, we studied the internal dynamics of the nucleus of two human cell lines (HELA and SHEP) in their cell cycle. We observe significant differences between the G1 phase, S and G2 and we can see the time ranges affected by phase change of the cell cycle. Next, we have studied nucleus dynamics of cells (SHEP and HELA), in the G phase, in the presence of cytobloquante drug in the culture environment. We also studied the effect of temperature. For cell in G1 phase, we lowered the temperature of 37°C to 25° C. We were able to follow the changing dynamics during the cooling and at 25°C. Finally, we have studied nucleus dynamics of fixed SHEP and HELA cells.

Autonomous vehicles rely on sensors for a clear understanding of the environment and in a heavy duty truck, the sensors are placed at multiple locations like the cabin, chassis and the trailer in order to increase the field of view and reduce the blind spot area. Usually, these sensors perform best when they are stationary relative to the ground, hence large and fast movements, which are quite common in a truck, may lead to performance reduction, erroneous data or in the worst case, a sensor failure. This enforces a need to validate the sensors before using them for making life-critical decisions. This thesis proposes Domain Adaptation as one of the strategies to co-validate Inertial Measurement Unit (IMU) sensors. The proposed Generative Adversarial Network (GAN) based framework predicts the data of one IMU using other IMUs in the truck by implicitly learning the internal dynamics. This prediction model along with other sensor fusion strategies would be used by the supervising system to validate the IMUs in real-time. Through data collected from real-world experiments, it is shown that the proposed framework is able to accurately transform raw IMU sequences across domains. A further comparison is made between Long Short Term Memory (LSTM) and WaveNet based architectures to show the superiority of WaveNets in terms of performance and computational efficiency. / Autonoma fordon förlitar sig på sensorer för att skapa en bild av omgivningen. På en tung lastbil placeras sensorerna på multipla ställen, till exempel på hytten, chassiet och på trailern för att öka siktfältet och för att minska blinda områden. Vanligtvis presterar sensorerna som bäst när de är stationära i förhållande till marken, därför kan stora och snabba rörelser, som är vanliga på en lastbil, leda till nedsatt prestanda, felaktig data och i värsta fall fallerande sensorer. På grund av detta så finns det ett stort behov av att validera sensordata innan det används för kritiskt beslutsfattande. Den här avhandlingen föreslår domänadaption som en av de strategier för att samvalidera Tröghetsmätningssensorer (IMU-sensorer). Det föreslagna Generative Adversarial Network (GAN) baserade ramverket förutspår en Tröghetssensors data genom att implicit lära sig den interna dynamiken från andra Tröghetssensorer som är monterade på lastbilen. Den här prediktionsmodellen kombinerat med andra sensorfusionsstrategier kan användas av kontrollsystemet för att i realtid validera Tröghetssensorerna. Med hjälp av data insamlat från verkliga experiment visas det att det föreslagna ramverket klarar av att med hög noggrannhet konvertera obehandlade Tröghetssensor-sekvenser mellan domäner. Ytterligare en undersökning mellan Long Short Term Memory (LSTM) och WaveNet-baserade arkitekturer görs för att visa överlägsenheten i WaveNets när det gäller prestanda och beräkningseffektivitet.