Best Selling Books by David Marquez

Tony Stark est à un tournant de sa vie. Avec sa nouvelle armure et de nouveaux alliés (dont Victor Von Fatalis !) le célèbre justicier va affronter Madame Masque. Iron Man est de retour plus en forme que jamais !

In the six months since the multipronged power struggle between Hydra, Leviathan, and Nick Fury blossomed into an all-out war on three fronts, each side has suffered extensive casualties. Trying anything he can to stop Hydra''s and Leviathan''s war on each other and the world, Fury, the battle-hardened leader of the Secret Warriors, finds as night falls and Seattle explodes that "anything" may mean some of the grittiest life-and-death choices his Warriors have ever seen him make.

While there have been many recently developed Elastic Network Models (ENM) to calculate the fluctuation dynamics of proteins, e.g., Gaussian Network Model (GNM), Anisotropic Network Model (ANM), Distance Network Model (DNM), the concept of loading these models to study the molecular mechanics and constitutive behavior of structural proteins has remained relatively untouched, until very recently. This work entails using the ANM as the framework for developing a finite element model of a 9-monomer strand of actin. Critical input parameters to the model, such as the cutoff radius, r[subscript c], and spring constant, k, are generated by matching the all-atom steered molecular dynamics (SMD) residue displacements to that of the ANM. The parameters yielding the best match between the SMD and structural ENM (SENM) simulations will then be input into the finite element model (FEM) for a more in depth analysis. The finite element model incorporates a 9-monomer strand of actin. The F-actin strand is subjected axial and torsional loads comparable to those seen in vivo. Key areas of interest in the protein are examined, such as the nucleotide binding pocket (NBP) and the DNase I binding loop, to demonstrate how loading affects the protein''s conformation. Local residue displacements are tracked in an effort to garner a better understanding of how various loads are transmitted through F-actin during key events. Insights and conclusions are discussed along with the implications of this work.

This report explains the process carried out to use an automatic gear change applied to a bicycle. To do this, a preliminary investigation of the nowadays used systems in this discipline has been done. It is explained the evolution that the bicycle has lived to compare the old gearshift systems with the nowadays systems, which are completely electronic. The objective was to modify one of these electronic changes to make it work automatically. But the price and the complexity of these devices led to rule out this option. So it was decided to modify a classic change gear (by cable) to get an automatic change. To achieve the bicycle change gears automatically, it has been necessary to use sensors, a microcontroller and a motor capable of regulating the tension of the cable of the gear change, that is to say that the motor change gears. Three sensors have been used to take measurements of speed, pedalling strength and pedalling rate. These sensors have been employed to make different test to analyse the results. Taking into account these results, it was deduced that must be given many pedalling in rises. Meanwhile, in a flat terrain, is important the number of pedalling but also the rate to maintain the inertia. The study has not been done downgrades because only an eighth speed set was used. The microcontroller has been programmed taking into account these results. It chose the gear in order to obtain the maximum efficiency. Arduino Mega 2560 has been used, because a great storage and a great number of ports have been required. Two servomotors get the information from the microcontroller in order to regulate the position of the gear changes. These engines have been programed to turn a specific degree. Depend on the gear that you want to use, engines will turn the grades that the microcontroller have programed. The theoretical case has also been solved successfully. The prototype has demonstrated that sensors accumulate a lot of errors. However, servo engines support the worst and bad effect, because they are not prepared to hold weight. As a result, its operation is not effective. Finally, the prototype has been installed on a bicycle that makes measurements and process data in an accurate way in spite of the gear changes have to be done manually, due to the servo engines are not prepared for this function.