The rule of the Monk ; or, Rome in the nineteenth century.

Also published under title: Il governo del monaco.

Men in crisis; the revolutions of 1848.

The Revolution in France: Louis Philippe. Lamartine Louis Napoleon.--The Revolution in Italy: Italy after the Congress of Vienna. Mazzini and Garibaldi.--The Revolution in Germany: Karl Marx.--The Revolution in the Habsburg Monarchy: Metternich, Szechenyi, and Kossuth.--Repercussions in America.--Conclusion.--Bibliographical notes (p. 337-346)

Das Schwert Italiens.

Published also in an abbreviated edition (Zürich, 1863) with the same title.

L'Italie est-elle la terre des morts? /

La terre des morts.--G. Giusti.--Les Lombards.--Les Florentins.--A. da Brescia.--G. Leopardi.--L'histoire guelfe.--L'hisoire italienne.--Les Poerio.--La poésie populaire.--Le théâtre populaire.--Naples et la Sicile.--Un tour d'Italie.--F. D. Guerrazzi.--Garibaldi et Mazzini.--Les philosophes.--V. Gioberti.--Le Piémont.--Les Piémontais.

Della storia di Chiavari /

Reprint. Originally published: Genova : Tipografia Como, 1853.

Speranze e glorie; discorsi.

Per una distribuzione di premi.--Per l'inaugurazione d'un circolo universitario.--Per la quistione sociale.--Per il 1o maggio.--Per Giuseppe Garibaldi.--Per Felice Cavallotti.--Per Gustavo Modena.

Refugios de fuego de Austrocedrus chilensis y su función en la expansión del bosque sobre el matorral en el noroeste de la Patagonia

El fuego modula la dinámica de la vegetación, favoreciendo distintas estrategias de persistencia y recolonización. Especies de reproducción obligada por semilla dependen de características ambientales para persistir, como de refugios los cuales tienen atributos biofísicos que disminuyen la severidad del fuego, permitiendo su supervivencia y dispersión post-fuego. Mientras que hay especies que mediante órganos de reserva pueden persistir y rebrotar. El objetivo de esta tesis es desarrollar y validar un modelo conceptual de dinámica sucesional entre comunidades vegetales de distinta historia de vida en paisajes propensos al fuego. En el noroeste de Patagonia, matorrales rebrotantes y bosques de Austrocedrus chilensis (ciprés) responden diferencialmente al fuego generando un ciclo sucesional. Estudié características de remanentes de ciprés, su potencial de dispersión hacia la matriz y las interacciones entre rebrotantes y ciprés en el tiempo. Encontré que los remanentes de ciprés ocurren en refugios donde la alta relación roca/vegetación disminuiría la severidad del fuego. Los cipreses revelaron mayor crecimiento en refugios que en la matriz, aunque exhibieron severas reducciones durante años secos. Este compromiso entre supervivencia al fuego y vulnerabilidad a la sequía implicaría que la funcionalidad de los refugios podría reducirse ante incrementos en la severidad de estos eventos. La dispersión de semillas de ciprés desde refugios presentó un kernel de cola gorda, indicando posibilidad de dispersión a largas distancias y rápida expansión. Aunque el establecimiento de plántulas de ciprés incrementó ante la presencia de rebrotantes, el posterior crecimiento del ciprés estuvo suprimido por al menos 15 años hasta que superaron la competencia de las rebrotantes. Los refugios de fuego son clave para la persistencia y recolonización del ciprés, pero la competencia con las rebrotantes en la matriz estaría enlenteciendo el proceso sucesional, lo que podría aumentar la probabilidad de incendio y modificar el curso sucesional hacia un estadio dominado por rebrotantes.

Idiotypic Immune Networks in Mobile Robot Control

Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

The Application of a Dendric Cell Algorithm to a Robotic Classifier

The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.

Idiotypic Immune Networks in Mobile Robot Control

Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.

The Application of a Dendric Cell Algorithm to a Robotic Classifier

The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.

The Application of a Dendric Cell Algorithm to a Robotic Classifier

The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.

Genetic algorithm seeding of idiotypic networks for mobile-robot navigation

Robot-control designers have begun to exploit the properties of the human immune system in order to produce dynamic systems that can adapt to complex, varying, real-world tasks. Jerne’s idiotypic-network theory has proved the most popular artificial-immune-system (AIS) method for incorporation into behaviour-based robotics, since idiotypic selection produces highly adaptive responses. However, previous efforts have mostly focused on evolving the network connections and have often worked with a single, preengineered set of behaviours, limiting variability. This paper describes a method for encoding behaviours as a variable set of attributes, and shows that when the encoding is used with a genetic algorithm (GA), multiple sets of diverse behaviours can develop naturally and rapidly, providing much greater scope for flexible behaviour-selection. The algorithm is tested extensively with a simulated e-puck robot that navigates around a maze by tracking colour. Results show that highly successful behaviour sets can be generated within about 25 minutes, and that much greater diversity can be obtained when multiple autonomous populations are used, rather than a single one.

An idiotypic immune network as a short-term learning architecture for mobile robots

A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile robot navigation problems is presented and tested in both real and simulated environments. The LTL consists of rapid simulations that use a Genetic Algorithm to derive diverse sets of behaviours. These sets are then transferred to an idiotypic Artificial Immune System (AIS), which forms the STL phase, and the system is said to be seeded. The combined LTL-STL approach is compared with using STL only, and with using a handdesigned controller. In addition, the STL phase is tested when the idiotypic mechanism is turned off. The results provide substantial evidence that the best option is the seeded idiotypic system, i.e. the architecture that merges LTL with an idiotypic AIS for the STL. They also show that structurally different environments can be used for the two phases without compromising transferability.

Otolith shape variation provides a marker of stock origin for north Atlantic bluefin tuna (Thunnus thynnus)

Two stocks of bluefin tuna (Thunnus thynnus) inhabit the north Atlantic; the western and eastern stocks spawn in the Gulf of Mexico and the Mediterranean Sea respectively. Trans-Atlantic movements occur outside spawning time whereas natal homing maintains stock structure. Commercial fisheries may exploit a mixed assemblage of both stocks. The incorporation of mixing rates into stock assessment is precluded by uncertainties surrounding stock discrimination. Otolith shape descriptors were used to characterise western and eastern stocks of Atlantic bluefin tuna in the present study and to estimate stock composition in catches of unknown origin. Otolith shape varied with length and between locations and years. Within a restricted size range (200-297-cm fork length (FL)) the two stocks were distinguished with an accuracy of 83%. Bayesian stock mixture analysis indicated that samples from the east Atlantic and Mediterranean were predominantly of eastern origin. The proportion assigned to the eastern stock showed slight spatial variation; however, overlapping 95% credible intervals indicated no significant difference (200-297 cm FL: central Atlantic, 73-100%; Straits of Gibraltar, 73-100%; Morocco, 50-99%; Portugal 64-100%). Otolith shape could be used in combination with other population markers to improve the accuracy of mixing rate estimates for Atlantic bluefin tuna.