Intervención del Estado, propiedad y control en las empresas gestoras del monopolio de tabacos de España, 1887-1998

Editada en la Fundación Empresa PúblicaA diferencia de los dos grandes monopolios europeos de tabacos —el francés y el italiano—, que fueron gestionados casi siempre por el Estado, en España la gestión de este monopolio ha sido arrendada durante más de un siglo a dos empresas muy relacionadas entre sí: la Compañía Arrendataria de Tabacos (1887-1945) y Tabacalera (1945-1998). Este trabajo trata de explicar la permanencia de esta gestión arrendada analizando el tipo de empresas que fueron desde el punto de vista de la regulación a la que estuvieron sometidas por el Estado, de la estructura de su propiedad y del control de su gestión así como utilizando algunos elementos de las teorías de la agencia y de la regulación positiva.Unlike two big European tobacco monopolies —the French monopoly and the Italian one—, which almost always were managed by the State, the management of Spanish tobacco monopoly was leased out for over a century to two companies very related: the Compañía Arrendataria de Tabacos (1887-1945) and Tabacalera (1945-1998). This paper provides an explanation of this situation analysing the kind of companies they were from the standpoint of State regulation, ownership structure and management control and also using some principles of the Agency's Theory and the Economic Regulation's Theory.Publicad

Barcos, carbón y mineral de hierro. Los vapores de Sota y Aznar y los orígenes de la moderna flota mercante de Bilbao, 1889-1900

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Reduction of the KP Hierarchy

This thesis will delve into the Kadomtsev-Petviashvili equation or KP equation and it\u27s hierarchy. More specifically, the solition theory around it. To do so, we first explore the soliton theory for the Korteweg de-Vries equation or KdV equation by analysing it through the inverse scattering transform method and presenting it\u27s soliton solutions. Second, we will introduce, Hirota\u27s bilinear form, and understand its main idea. Third, introduce Sato Theory, and use it to formulate the KP hierarchy, via using pseudo-differential operators, presenting the lax operator, the dressing operator, Sato’s equation, and the zero curvature equation (Zakharov-Shabat Equation). Fourth, find the general solution and one-soliton solution to the KP hierarchy and perform a 2-reduction and 3-reduction on the KP hierarchy. Finally, use Hirota\u27s bilinear method (direct method) to find the multiple solition solutions for the KP hierarchy

Leonor Ludlow (dir.) y María Eugenia Vázquez Semadeni (coord.) (2010), 200 emprendedores mexicanos. La construcción de una nación, vol. i: Siglo xix, vol. ii: Siglo xx, LID Editorial Mexicana, México, 750 y 755 pp., respectivamente.

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In defense of the difficult

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Range-only SLAM schemes exploiting robot-sensor network cooperation

Simultaneous localization and mapping (SLAM) is a key problem in robotics. A robot with no previous knowledge of the environment builds a map of this environment and localizes itself in that map. Range-only SLAM is a particularization of the SLAM problem which only uses the information provided by range sensors. This PhD Thesis describes the design, integration, evaluation and validation of a set of schemes for accurate and e_cient range-only simultaneous localization and mapping exploiting the cooperation between robots and sensor networks. This PhD Thesis proposes a general architecture for range-only simultaneous localization and mapping (RO-SLAM) with cooperation between robots and sensor networks. The adopted architecture has two main characteristics. First, it exploits the sensing, computational and communication capabilities of sensor network nodes. Both, the robot and the beacons actively participate in the execution of the RO-SLAM _lter. Second, it integrates not only robot-beacon measurements but also range measurements between two di_erent beacons, the so-called inter-beacon measurements. Most reported RO-SLAM methods are executed in a centralized manner in the robot. In these methods all tasks in RO-SLAM are executed in the robot, including measurement gathering, integration of measurements in RO-SLAM and the Prediction stage. These fully centralized RO-SLAM methods require high computational burden in the robot and have very poor scalability. This PhD Thesis proposes three di_erent schemes that works under the aforementioned architecture. These schemes exploit the advantages of cooperation between robots and sensor networks and intend to minimize the drawbacks of this cooperation. The _rst scheme proposed in this PhD Thesis is a RO-SLAM scheme with dynamically con_gurable measurement gathering. Integrating inter-beacon measurements in RO-SLAM signi_cantly improves map estimation but involves high consumption of resources, such as the energy required to gather and transmit measurements, the bandwidth required by the measurement collection protocol and the computational burden necessary to integrate the larger number of measurements. The objective of this scheme is to reduce the increment in resource consumption resulting from the integration of inter-beacon measurements by adopting a centralized mechanism running in the robot that adapts measurement gathering. The second scheme of this PhD Thesis consists in a distributed RO-SLAM scheme based on the Sparse Extended Information Filter (SEIF). This scheme reduces the increment in resource consumption resulting from the integration of inter-beacon measurements by adopting a distributed SLAM _lter in which each beacon is responsible for gathering its measurements to the robot and to other beacons and computing the SLAM Update stage in order to integrate its measurements in SLAM. Moreover, it inherits the scalability of the SEIF. The third scheme of this PhD Thesis is a resource-constrained RO-SLAM scheme based on the distributed SEIF previously presented. This scheme includes the two mechanisms developed in the previous contributions {measurement gathering control and distribution of RO-SLAM Update stage between beacons{ in order to reduce the increment in resource consumption resulting from the integration of inter-beacon measurements. This scheme exploits robot-beacon cooperation to improve SLAM accuracy and e_ciency while meeting a given resource consumption bound. The resource consumption bound is expressed in terms of the maximum number of measurements that can be integrated in SLAM per iteration. The sensing channel capacity used, the beacon energy consumed or the computational capacity employed, among others, are proportional to the number of measurements that are gathered and integrated in SLAM. The performance of the proposed schemes have been analyzed and compared with each other and with existing works. The proposed schemes are validated in real experiments with aerial robots. This PhD Thesis proves that the cooperation between robots and sensor networks provides many advantages to solve the RO-SLAM problem. Resource consumption is an important constraint in sensor networks. The proposed architecture allows the exploitation of the cooperation advantages. On the other hand, the proposed schemes give solutions to the resource limitation without degrading performance