Macromolecular interactions play very important roles in regulation of all levels of biological processes. Aberrant macromolecular interactions often result in diseases. By applying a combination of spectroscopy, calorimetry, computation and other techniques, the protein-protein interactions in the system of the Shaw2 Kv channel and the protein-RNA interactions in West Nile virus RNA-cellular protein TIAR complex were explored. In the former system, the results shed light on the local structures of the key channel components and their potential interaction mediated by butanol, a general anesthetic. In the later studies, the binding modes of TIAR RRM2 to oligoU RNAs and West Nile virus RNAs were investigated. These findings provided insights into the basis of the specific cellular protein–viral RNA interaction and preliminary data for the development of strategies on how to interfere with virus replication

Multiple-input, multiple-output (MIMO) techniques have been proposed to meet the needs for higher data rates and lower delays in future wireless communication systems. The downlink capacity of multiuser MIMO systems is achieved when the system transmits to several users simultaneously. Frequently, many more users request service than the transmitter can simultaneously support. Thus, the transmitter requires a scheduling algorithm for the users, which must balance the goals of increasing throughput, reducing multiuser interference, lowering delays, ensuring fairness and quality of service (QoS), etc. In this thesis, we investigate the application of genetic algorithms (GAs) to perform scheduling in multiuser MIMO systems. GAs are a fast, suboptimal, low-complexity method of solving optimization problems, such as the maximization of a scheduling metric, and can handle arbitrary functions and QoS constraints. We first examine a system that transmits using capacity-achieving dirty paper coding (DPC). Our proposed GA structure both selects users and determines their encoding order for DPC, which affects the rates they receive. Our GA can also schedule users independently on different carriers of a multi-carrier system. We demonstrate that the GA performance is close to that of an optimal exhaustive search, but at a greatly reduced complexity. We further show that the GA convergence time can be significantly reduced by tuning the values of its parameters. While DPC is capacity-achieving, it is also very complex. Thus, we also investigate GA scheduling with two linear precoding schemes, block diagonalization and successive zero-forcing. We compare the complexity and performance of the GA with "greedy" scheduling algorithms, and find the GA is more complex, but performs better at higher signal-to-noise ratios (SNRs) and smaller user pool sizes. Both algorithms are near-optimal, yet much less complex than an exhaustive search. We also propose hybrid greedy-genetic algorithms to gain benefits from both types of algorithms. Lastly, we propose an improved method of optimizing the transmit covariance matrices for successive zero-forcing. Our algorithm significantly improves upon the performance of the existing method at medium to high SNRs, and, unlike the existing method, can maximize a weighted sum rate, which is important for fairness and QoS considerations. / Communications

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Cette thèse vise à élaborer de nouvelles stratégies de commande basées sur la commande prédictive pour le système de génération d’énergie éolienne. La topologie des systèmes de production éolienne basées sur le Générateur Asynchrone à Double Alimentation (GADA) qui convient à des plateformes de génération dans la gamme de puissance de 1.5 à 6 MW est abordée. Du point de vue technologique, le convertisseur à trois niveaux et clampé par le neutre (3L-NPC) est considéré comme une bonne solution pour une puissance élevée en raison de ses avantages: capacité à réduire la distorsion harmonique de la tension de sortie et du courant, et augmentation de la capacité du convertisseur grâce à une tension réduite appliquée à chaque semi-conducteur de puissance. Une description détaillée de la commande prédictive à ensemble de commande fini (FCS-MPC) avec un horizon de prédiction de deux pas est présentée pour deux boucles de régulation: celle liée au convertisseur connecté au réseau et celle du convertisseur connecté au GADA. Le principe de la commande repose sur l’utilisation d’un modèle de prédiction permettant de prédire le comportement du système pour chaque état de commutation du convertisseur. La minimisation d’une fonction de coût appropriée prédéfinie permet d’obtenir la commutation optimale à appliquer au convertisseur. La thèse étudie premièrement les problèmes liées à la compensation du temps de calcul de la commande et au choix et aux pondérations de la fonction de coût. Ensuite, le problème de stabilité de la commande FCS-MPC est abordé en considérant une fonction de Lyapunov dans la minimisation de la fonction de coût. Finalement, une étude sur la compensation des effets des temps morts du convertisseur est présentée. / This thesis aims to elaborate new control strategies based on Model Predictive control for wind energy generation system. We addressed the topology of doubly fed induction generator (DFIG) based wind generation systems which is suitable for generation platform power in the range in 1.5-6 MW. Furthermore, from the technological point of view, the three-level neutral-point clamped (3L-NPC) inverter configuration is considered a good solution for high power due to its advantages: capability to reduce the harmonic distortion of the output voltage and current, and increase the capacity of the converter thanks to a decreased voltage applied to each power semiconductor.In this thesis, we presented a detailed description of finite control set model predictive control (FCS-MPC) with two step horizon for two control schemes: grid and DFIG connected 3L-NPC inverter. The principle of the proposed control scheme is to use system model to predict the behaviour of the system for every switching states of the inverter. Then, the optimal switching state that minimizes an appropriate predefined cost function is selected and applied directly to the inverter.The study of issues such as delay compensation, computational burden and selection of weighting factor are also addressed in this thesis. In addition, the stability problem of FCS-MPC is solved by considering the control Lyapunov function in the design procedure. The latter study is focused on the compensation of dead-time effect of power converter.