Locked-in planar rotational motion for satellites moving in a gravity gradient field is examined using both analytical and numerical techniques. It is shown that rotational locks at spin rates of n/2 (where n is an integer) satellite rotations per orbit revolution exist for specific combinations of satellite inertia properties and orbital eccentricity. For nearly axial symmetric satellites, the maximum and minimum instantaneous rates which permit the satellite to remain in a particular rotational lock are found analytically by applying the averaging techniques of Kryloff and Bogolinboff and that of Symon. For these cases, it is found that the strength of the higher rotational locks (n > 3) are greater than the strength of the n = 2 or 1/1 rotational lock for proper combinations of lock number, n, and orbital eccentricity. Comparison of the results for the case of the planet Mercury are shown to be in good agreement with both observations of the planet and the 2 numerical calculations of Liu. Numerical results were obtained for representative values throughout the range of satellite inertia properties. Periodic solutions of periods 2π and 4 π are found and their variational stability investigated by Floquet analysis. The results which are presented on stability charts show that for satellites that deviate appreciably from axial symmetry, the stable periodic solutions occur at eccentricities which tend to increase as the absolute value of the lock number |n| increases. Estimates of the strength of these rotational locks are found by applying the phase space technique of Brereton and Modi. For nearly axially symmetric satellites, the results of this technique agreed favorably with the analytical results. Rotational locks for satellites that are not nearly axial symmetric were found in general to be considerably weaker than the more frequently investigated 1/1 lock. / Ph. D.

Unsymmetrical discotic liquid crystals based on hexaazatriphenylene(HAT) have not been published until today.We have used tetrahydoxyquinone as the starting material to synthesis unsymmetrical discotic liquid crystals based on HAT and investigate their properties of liquid crystal.

The bacterial RNA binding protein Hfq is a key component for bacterial sRNA mediated riboregulation of mRNA expression. A kinetic and thermodynamic analysis of Hfq binding to its sRNA targets DsrA, RprA, and OxyS, and to its mRNA target rpoS was carried out. The ability of Hfq to significantly enhance the stability of the DsrA-rpoS and RprA-rpoS complex was demonstrated, and the entire untranslated leader region of rpoS was shown to be important for Hfq binding and in Hfq facilitated sRNA-mRNA duplex formation. Hfq was not shown to enhance OxyS binding to rpoS. DsrA and OxyS were shown to bind mostly to the proximal surface region of Hfq, while RprA bound to both proximal and distal surface regions. The rpoS leader region was shown to possess at least two distinct Hfq binding sites, with one site binding the proximal region and the other to the distal region of Hfq. These sites were shown to be important for Hfq to stimulate DsrA-rpoS binding. The outer-circumference region and the C-terminal tail of Hfq does not play a major role in binding DsrA, RprA, OxyS and rpoS, and in stimulating DsrA-rpoS binding. Evidence was obtained implicating Hfq to bind DsrA, RprA, OxyS, and oligo rA18 in a 1:1 protein to RNA stoichiometry. Binding properties of Hfq to E. coli genomic DNA were examined. Double stranded DNA was shown to bind mostly on the distal surface region and the C-terminal tail of Hfq with an affinity 10 fold less than Hfq targeted RNA. Single stranded DNA binds Hfq more tightly than double stranded DNA and binding seems to be sequence specific. Evidence indicates Hfq binds certain sequences of the E. coli genome.

Dans le cortex visuel primaire du chat (aires 17 et 18), les neurones répondant aux orientations présentes dans l’environnement (comme le contour des objets) sont organisés en colonnes perpendiculaires à la surface du cortex. Il a précédemment été montré qu'un changement drastique des orientations présentes dans l’environnement change la réponse des neurones. Par exemple, un neurone répondant à des orientations horizontales pourra répondre, après apprentissage d'un nouvel environnement, à des orientations obliques. Nous avons voulu, dans cette thèse, suivre les changements de propriétés de populations entières de neurones suite à ce type d'apprentissage. A cet effet, nous avons utilisé la technique d'imagerie optique des signaux intrinsèques, qui permet de mesurer l'activité d'une surface de cortex en utilisant le signal BOLD (blood-oxygen-level dependent). Cette thèse s'articule sur trois axes : l'effet de l'apprentissage au niveau local, l'effet de l’apprentissage à l'échelle de l'aire cérébrale, et la modélisation de l’apprentissage. Dans la première partie, nous avons comparé les changements d’orientations des neurones en fonction du gradient d’orientation local. Ce gradient est fort quand deux neurones voisins ont des orientations très différentes, et faible quand leurs orientations sont semblables. Les résultats montrent que plus les neurones sont entourés de neurones aux orientations différentes, plus l'apprentissage change leur réponse à l’orientation. Ceci suggère que les connexions locales ont une influence déterminante sur l'ampleur de l’apprentissage. Dans la deuxième partie, nous avons comparé le changement d’orientation des neurones des aires 17 et 18 avant et après apprentissage. Les résultats ne sont pas notablement différents entre les aires 17 et 18. On peut toutefois noter que les changements d’orientations dans l’aire 18 ont des amplitudes plus variables que dans l’aire 17. Ceci peut provenir du fait que l’aire 18 reçoit des afférences plus variées que l’aire 17, notamment une afférence directe des cellules Y du CGLd (Corps Genouillé Latéral dorsal). Dans la troisième partie, nous avons modélisé l'apprentissage expérimentalement observé à l'aide de réseaux de neurones utilisant un apprentissage Hebbien (cartes auto-organisatrices). Nous avons montré que le « feedback » des aires supérieures vers le cortex visuel primaire était souhaitable pour la conservation de la sélectivité à l'orientation des neurones. De manière générale, cette thèse montre l'importance des connexions locales dans la plasticité neuronale. Notamment, elles garantissent un apprentissage homéostatique, c'est-à- dire conservant la représentativité des orientations au niveau du cortex. De manière complémentaire, elle montre également l’importance des aires supérieures dans le maintient à long terme des orientations apprises par les neurones lors de l'apprentissage. / In the cat primary visual cortex (areas 17 and 18), neurons responding to orientations in the environment (such as the outline of objects) are organized in columns perpendicular to the cortical surface. It was previously shown that a drastic change in orientations in the environment changes the response of neurons. For example, a neuron responding to a horizontal orientation will respond, after learning a new environment, to an oblique orientation. In this thesis, we seek to follow the changes of properties of large populations of neurons due to this type of learning. To this end, we used the intrinsic signals optical imaging technique, which measures the activity of a cortical surface using the BOLD (blood-oxygen-level dependent) signal. This thesis follows three axes: the effect of learning at the local level, the effect of learning at the visual area scale, and the modeling of learning. In the first part, we compared the changes in orientation of neurons according to the local gradient of orientation. This gradient is strong when two neighboring neurons have very different orientations, and weak when their orientations are similar. The obtained relation between the gradient and the magnitude of change in orientation shows that when neurons are increasingly surrounded by neurons with different orientations, they change their response to orientation to a greater extent. This suggests that local connections have a decisive influence on the extent of learning. In the second part, we followed the change in the orientation of neurons in the areas 17 and 18, before and after learning. The results are not significantly different between area 17 and area 18. However, it is noteworthy that orientation changes in area 18 are more variable in amplitude than in area 17. This may be because area 18 receives more diverse inputs than area 17, including a direct input from dLGN (dorsal Lateral Geniculate Nucleus) Y cells. In the third part, we modeled the experimentally observed learning with neural networks using a Hebbian learning rule (networks are self-organizing maps). We have shown that feedback from higher areas to the primary visual cortex was desirable for the neurons orientation selectivity conservation. Overall, this thesis shows the importance of local connections in neuronal plasticity. In particular, they guarantee a homeostatic learning, i.e. maintaining the representativeness of orientations in the cortex. In a complementary manner, it also shows the importance of the superior areas in the conservation of learned orientations.