Design, realization, and characterization of complex reaction networks in dynamic mechanically interlocked molecules

The experimental projects discussed in this thesis are all related to the field of artificial molecular machines, specifically to systems composed of pseudorotaxane and rotaxane architectures. The characterization of the peculiar properties of these mechano-molecules is frequently associated with the analysis and elucidation of complex reaction networks; this latter aspect represents the main focus and central thread tying my thesis work. In each chapter, a specific project is described as summarized below: the focus of the first chapter is the realization and characterization of a prototype model of a photoactivated molecular transporter based on a pseudorotaxane architecture; in the second chapter is reported the design, synthesis, and characterization of a [2]rotaxane endowed with a dibenzylammonium station and a novel photochromic unit that acts as a recognition site for a DB24C8 crown ether macrocycle; in the last chapter is described the synthesis and characterization of a [3]rotaxane in which the relative number of rings and stations can be changed on command.

The frozen elephant trunk technique for the treatment of complex aortic arch and descending thoracic aorta pathologies: long term outcomes and distal reintervention

Background: The frozen elephant trunk(FET) technique is one of the last evolution in the treatment of complex pathologies of the aortic arch and the descending thoracic aorta.Materials and methods: Between January 2007 and March 2021, a total of 396 patients underwent total aortic arch replacements with the FET technique in our centre.The main indications were thoracic aortic aneurysm(n=104,28.2%), chronic aortic dissection(n=224,53.4%) and acute aortic dissection(n=68, 18.4%). We divided the population in two groups according the position of the distal anastomosis (zone 2 vs zone 3) and the length of the stent graft (< 150 mm vs > 150 mm): conservative group (Zone 2 anastomosis + stent length < 150mm, n. 140 pts) and aggressive group (zone 3 anastomosis + stent length > 150mm, n. 141). Results: The overall 30-day mortality rate was 13%(48/369); the risk factor analysis showed that an aggressive approach was neither a risk factor for major complication (permanent dialysis, tracheostomy, bowel malperfusion and permanent paraplegia) neither for 30-day mortality. The survival rate at 1, 5,10 and 15 years was 87.7%,75%,61.3% and 58.4% respectively. During the follow up, an aortic reintervention was performed in 122 patients (38%), 5 patients received a non-aortic cardiac surgery. Freedom from aortic reintervention at 1-,5- and 10-year was 77%,54% and 44% respectively. The freedom from aortic reintervention was higher in the ‘aggressive’ group (62.5%vs40.0% at 5 years, log-rank=0.056). An aggressive approach was not protective for aortic reintervention at follow up and for death at follow up. Conclusions: The FET technique represents a feasible and efficient option in the treatment of complex thoracic aortic pathologies. An aortic reintervention after FET is very common and the decision-making approach should consider and balance the higher risk of an aggressive approach in terms of post-operative complication versus the higher risk of a second aortic reintervention at follow-up.

Dissolution parameters for sodium diclofenac-containing hypromellose matrix tablet

Sodium diclofenac (SD) release from dosage forms has been studied under different conditions. However, no dissolution method that is discriminatory enough to reflect slight changes in formulation or manufacturing process, and which could be effectively correlated with the biological properties of the dosage form, has been reported. This study sought to develop three different formulae of SD-containing matrix tablets and to determine the effect of agitation speed in its dissolution profiles. F1, F2 and F3 formulations were developed using hypromellose (10, 20 and 30%, respectively for F1, F2 and F3) and other conventional excipients. Dissolution tests were carried out in phosphate buffer pH 6.8 at 37 degrees C using apparatus 11 at 50, 75 or 100 rpm. Dissolution efficiency (DE), T(50) and T(90) were determined and plotted as functions of the variables agitation speed and hypromellose concentration. Regarding DE, F2 showed more sensitivity to variations in agitation speed than F1 and F3. Increasing hypromellose concentration reduced DE values, independent of agitation speed. Analysis of T(50) and T(90) suggests that F1 is less sensitive to variations in agitation speed than F2 and F3. Most discriminatory dissolution conditions were observed at 50 rpm. Results suggest that the comparison of dissolution performance of SD matrix tablets should take into account polymer concentration and agitation conditions. (C) 2009 Published by Elsevier B.V.

Monge assignment games

Un juego de asignación se define por una matriz A; donde cada fila representa un comprador y cada columna un vendedor. Si el comprador i se empareja a un vendedor j; el mercado produce aij unidades de utilidad. Estudiamos los juegos de asignación de Monge, es decir, aquellos juegos bilaterales de asignación en los cuales la matriz satisface la propiedad de Monge. Estas matrices pueden caracterizarse por el hecho de que en cualquier submatriz 2x2 un emparejamiento óptimo está situado en la diagonal principal. Para mercados cuadrados, describimos sus núcleos utilizando sólo la parte central tridiagonal de elementos de la matriz. Obtenemos una fórmula cerrada para el reparto óptimo de los compradores dentro del núcleo y para el reparto óptimo de los vendedores dentro del núcleo. Analizamos también los mercados no cuadrados reduciéndolos a matrices cuadradas apropiadas.

Sequential decisions in allocation problems

[eng] In the context of cooperative TU-games, and given an order of players, we consider the problem of distributing the worth of the grand coalition as a sequentia decision problem. In each step of process, upper and lower bounds for the payoff of the players are required related to successive reduced games. Sequentially compatible payoffs are defined as those allocation vectors that meet these recursive bounds. The core of the game is reinterpreted as a set of sequentally compatible payoffs when the Davis-Maschler reduced game is considered (Th.1). Independently of the reduction, the core turns out to be the intersections of the family of the sets of sequentially compatible payoffs corresponding to the different possible orderings (Th.2), so it is in some sense order-independent. Finally, we analyze advantagenous properties for the first player

Sequential decisions in allocation problems

[eng] In the context of cooperative TU-games, and given an order of players, we consider the problem of distributing the worth of the grand coalition as a sequentia decision problem. In each step of process, upper and lower bounds for the payoff of the players are required related to successive reduced games. Sequentially compatible payoffs are defined as those allocation vectors that meet these recursive bounds. The core of the game is reinterpreted as a set of sequentally compatible payoffs when the Davis-Maschler reduced game is considered (Th.1). Independently of the reduction, the core turns out to be the intersections of the family of the sets of sequentially compatible payoffs corresponding to the different possible orderings (Th.2), so it is in some sense order-independent. Finally, we analyze advantagenous properties for the first player

Monge assignment games

Un juego de asignación se define por una matriz A; donde cada fila representa un comprador y cada columna un vendedor. Si el comprador i se empareja a un vendedor j; el mercado produce aij unidades de utilidad. Estudiamos los juegos de asignación de Monge, es decir, aquellos juegos bilaterales de asignación en los cuales la matriz satisface la propiedad de Monge. Estas matrices pueden caracterizarse por el hecho de que en cualquier submatriz 2x2 un emparejamiento óptimo está situado en la diagonal principal. Para mercados cuadrados, describimos sus núcleos utilizando sólo la parte central tridiagonal de elementos de la matriz. Obtenemos una fórmula cerrada para el reparto óptimo de los compradores dentro del núcleo y para el reparto óptimo de los vendedores dentro del núcleo. Analizamos también los mercados no cuadrados reduciéndolos a matrices cuadradas apropiadas.

Analog neural nonderivative optimizers

Continuous-time neural networks for solving convex nonlinear unconstrained;programming problems without using gradient information of the objective function are proposed and analyzed. Thus, the proposed networks are nonderivative optimizers. First, networks for optimizing objective functions of one variable are discussed. Then, an existing one-dimensional optimizer is analyzed, and a new line search optimizer is proposed. It is shown that the proposed optimizer network is robust in the sense that it has disturbance rejection property. The network can be implemented easily in hardware using standard circuit elements. The one-dimensional net is used as a building block in multidimensional networks for optimizing objective functions of several variables. The multidimensional nets implement a continuous version of the coordinate descent method.

Non-planar double-box, massive and massless pentabox Feynman integrals in the negative-dimensional approach

The negative-dimensional integration method is a technique which can be applied, with success, in usual covariant gauge calculations. We consider three two-loop diagrams: the scalar massless non-planar double-box with six propagators and the scalar pentabox in two cases, where six virtual particles have the same mass, and in the case all of them are massless. Our results are given in terms of hypergeometric functions of Mandelstam variables and also for arbitrary exponents of propagators and dimension D.

epsilon-Expansion for nonplanar six-propagators double boxes

We present calculations for a nonplanar double box with four massless, massive external, and internal legs propagators. The results are expressed for arbitrary exponents of propagators and dimension in terms of Lauricella's hypergeometric functions of three variables and hypergeometric-like multiple series.

Analog nonderivative optimizers

Analog networks for solving convex nonlinear unconstrained programming problems without using gradient information of the objective function are proposed. The one-dimensional net can be used as a building block in multi-dimensional networks for optimizing objective functions of several variables.

Correspondence between the one-loop three-point vertex and the Y and Delta electric resistor networks

Different mathematical methods have been applied to obtain the analytic result for the massless triangle Feynman diagram yielding a sum of four linearly independent (LI) hypergeometric functions of two variables F-4. This result is not physically acceptable when it is embedded in higher loops, because all four hypergeometric functions in the triangle result have the same region of convergence and further integration means going outside those regions of convergence. We could go outside those regions by using the well-known analytic continuation formulas obeyed by the F-4, but there are at least two ways we can do this. Which is the correct one? Whichever continuation one uses, it reduces a number of F-4 from four to three. This reduction in the number of hypergeometric functions can be understood by taking into account the fundamental physical constraint imposed by the conservation of momenta flowing along the three legs of the diagram. With this, the number of overall LI functions that enter the most general solution must reduce accordingly. It remains to determine which set of three LI solutions needs to be taken. To determine the exact structure and content of the analytic solution for the three-point function that can be embedded in higher loops, we use the analogy that exists between Feynman diagrams and electric circuit networks, in which the electric current flowing in the network plays the role of the momentum flowing in the lines of a Feynman diagram. This analogy is employed to define exactly which three out of the four hypergeometric functions are relevant to the analytic solution for the Feynman diagram. The analogy is built based on the equivalence between electric resistance circuit networks of types Y and Delta in which flows a conserved current. The equivalence is established via the theorem of minimum energy dissipation within circuits having these structures.

Algoritmos para mineria de datos con redes de neuronas

Este trabajo propone una serie de algoritmos con el objetivo de extraer información de conjuntos de datos con redes de neuronas. Se estudian dichos algoritmos con redes de neuronas Enhenced Neural Networks (ENN), debido a que esta arquitectura tiene algunas ventajas cuando se aproximan funciones mediante redes neuronales. En la red ENN los pesos de la matriz principal varián con cada patrón, por lo que se comete un error menor en la aproximación. Las redes de neuronas ENN reúnen la información en los pesos de su red auxiliar, se propone un método para obtener información de la red a través de dichos pesos en formas de reglas y asignando un factor de certeza de dichas reglas. La red ENN obtiene un error cuadrático medio menor que el error teórico de una aproximación matemática por ejemplo mediante polinomios de Taylor. Se muestra como una red ENN, entrenada a partir un conjunto de patrones obtenido de una función de variables reales, sus pesos asociados tienen unas relaciones similares a las que se veri_can con las variables independientes con dicha función de variables reales. Las redes de neuronas ENN aproximan polinomios, se extrae conocimiento de un conjunto de datos de forma similar a la regresión estadística, resolviendo de forma más adecuada el problema de multicolionalidad en caso de existir. Las relaciones a partir de los pesos asociados de la matriz de la red auxiliar se obtienen similares a los coeficientes de una regresión para el mismo conjunto numérico. Una red ENN entrenada a partir de un conjunto de datos de una función boolena extrae el conocimiento a partir de los pesos asociados, y la influencia de las variables de la regla lógica de la función booleana, queda reejada en esos pesos asociados a la red auxiliar de la red ENN. Se plantea una red de base radial (RBF) para la clasificación y predicción en problemas forestales y agrícolas, obteniendo mejores resultados que con el modelo de regresión y otros métodos. Los resultados con una red RBF mejoran al método de regresión si existe colinealidad entre los datos que se dispone y no son muy numerosos. También se detecta que variables tienen más importancia en virtud de la variable pronóstico. Obteniendo el error cuadrático medio con redes RBF menor que con otros métodos, en particular que con el modelo de regresión. Abstract A series of algorithms is proposed in this study aiming at the goal of producing information about data groups with a neural network. These algorithms are studied with Enheced Neural Networks (ENN), owing to the fact that this structure shows sever advantages when the functions are approximated by neural networks. Main matrix weights in th ENN vary on each pattern; so, a smaller error is produced when approximating. The neural network ENN joins the weight information contained in their auxiliary network. Thus, a method to obtain information on the network through those weights is proposed by means of rules adding a certainty factor. The net ENN obtains a mean squared error smaller than the theorical one emerging from a mathematical aproximation such as, for example, by means of Taylor's polynomials. This study also shows how in a neural network ENN trained from a set of patterns obtained through a function of real variables, its associated weights have relationships similar to those ones tested by means of the independent variables connected with such functions of real variables. The neural network ENN approximates polynomials through it information about a set of data may be obtained in a similar way than through statistical regression, solving in this way possible problems of multicollinearity in a more suitable way. Relationships emerging from the associated weights in the auxiliary network matrix obtained are similar to the coeficients corresponding to a regression for the same numerical set. A net ENN trained from a boolean function data set obtains its information from its associated weights. The inuence of the variables of the boolean function logical rule are reected on those weights associated to the net auxiliar of the ENN. A radial basis neural networks (RBF) for the classification and prediction of forest and agricultural problems is proposed. This scheme obtains better results than the ones obtained by means of regression and other methods. The outputs with a net RBF better the regression method if the collineality with the available data and their amount is not very large. Detection of which variables are more important basing on the forecast variable can also be achieved, obtaining a mean squared error smaller that the ones obtained through other methods, in special the one produced by the regression pattern.

Serie di Fourier e altre rappresentazioni analitiche delle funzioni di una variabile reale.

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