Nationalism-as-Technology and Peace in Europe, 1815-1914

This study offers a theory in which nationalism is not only conducive to war -which is the conventional wisdom-, but also brings peace to entire groupings of states under a specific set of conditions. After the theory is laid out, a plausibility probe of 19th century Europe offers good justification for a continued research program of nationalism-as-technology and its effects. The theory's insight comes from seeing nationalism not as an ideology, but as a form of military technology. For such technologies, their effect on war depends on how widely all countries employ them. When everyone has the same technology (i.e. when all countries are similarly endowed with nationalism), peace is cemented because countries mutually deter each other from launching wars of conquest. They do this by building mass armies to offset that of their neighbors, and threaten would-be conquerors with costly guerrilla wars and insurgencies. (Conversely, if only a few states possess the technology, the temptation to abuse it in conflict does rise.) The theoretical section of this study first justifies this analytical possibility of seeing nationalism as a technology. Among other things, the absence of definitional stumbling blocks is discussed. That is, given how technology is broadly defined by leading technologists, there is nothing inherent in the concept of nationalism that prevents its consideration as a technology. The study then proceeds to derive a series of hypotheses about the curvilinear effects of nationalism on war across a given region. As mentioned, the primary case study is 19th century Europe (1815-1914), which lends itself to a plausibility probe. The results are corroborating. Napoleonic France first "discovered" nationalism as a technology with military applications - it formed the first mass armies and attempted continental conquest. Later on, other "early-adopters" also employed nationalism to take land from their neighbors. Sardinia, for instance, used Italian nationalism to build volunteer armies and fight Austria for control of northern Italy in 1859. But the early adopters were then followed by most other European countries, which took reins of their own nationalisms to build mass-armies and boost their defenses. In line with the theory, the widespread adoption of nationalism preceded two whole generations of European peace, from 1871 to 1914. (So rare was this long peace that it would not be equaled until after World War II.) In sum, the history of the 1800s seems to fit broadly with the theory, and gives good reason for continued research into the pacifying role of nationalism

Charlas de radio : Darío Arizmendi, Hernán Peláez, Félix de Bedout, Gustavo Gómez, Héctor Rincón y Jordi Finazzi hablan de radio exitosa en Colombia

Comunicador (a) SocialPregrad

New Multiobjective Shortest Path Algorithms

The main problem studied in this thesis is the Multiobjective Shortest Path (MOSP) problem. We focus on the problem variant with three or more objectives. It is a generalization of the classical Shortest Path problem in which arcs in the input graph are weighted with vectors instead of scalars. The main contribution is the Multiobjective Dijkstra Algorithm (MDA), a label- setting algorithm that achieves state of the art performance in theory and in practice. Motivated by this result, the thesis goes on with the design of variants of the MDA for different variants of the MOSP problem. For the One-to-One MOSP problem the Targeted MDA (T-MDA) has the same asymptotic running time than the MDA but trades in memory for speed in practice. The additional paths stored during the T-MDA are managed in a pseudo-lazy way. This is a novel way to organize explored paths that ensures that the algorithm’s priority queue stores at most one path per node in the input graph simultaneously. The paths that are held back from the queue are organized in lists that are kept sorted by just prepending or appending paths to them, i.e., using constant time insertions. The resulting implementation of the T-MDA solves bigger instances than the MDA and is also faster. We study the generalization of the Time-Dependent Shortest Path problem to the multiobjective case. We provide a detailed analysis of the generalization’s limitations and discuss when the MDA is applicable. For MOSP instances with large sets of optimal paths, good approximation algorithms are important. We combine the MDA with an outcome space partition technique from the literature to obtain a new FPTAS for the MOSP problem. The resulting MD-FPTAS works also for multiobjective instances of the Time-Dependent Shortest Path problem, which is a novelty. Finally, we use the MDA and its biobjective version, the BDA, to solve the Multiobjective Minimum Spanning Tree (MO-MST) problem and the k-Shortest Simple Path (k-SSP) problem, respectively. For the solution of instances of these two problems, the MDA and the BDA are used as subroutines. An MO-MST instance is solved applying the MDA on a so called transition graph. In this graph paths have equivalent costs to trees in the original graph and thus, the optimal solutions computed by the MDA in the transition graph correspond to optimal trees in the original graph. Since the transition graph has an exponential size w.r.t. the size of the original graph, we discuss new pruning techniques to reduce its number of arcs effectively. The solution of the k-SSP, which is a scalar optimization problem, using a biobjective subroutine is surprising but our new algorithm is state of the art in theory and in practice.In dieser Arbeit beschäftigen wir uns hauptsächlich mit dem Multikriterielle Kürzeste Wege (MOSP) Problem. Es ist eine Verallgemeinerung des klassischen Kürzeste Wege Problems, bei der Kanten im Eingangsgraphen mit d-dimensionalen Vektoren anstelle von Skalaren gewichtet sind. Der Hauptbeitrag der Arbeit ist der Multiobjective Dijkstra Algorithmus (MDA), ein label-setting Algorithmus, der in der Theorie und in der Praxis eine Verbesserung der in der Literatur vorhandenen Ergebnisse darstellt. Motiviert durch dieses Ergebnis entwickeln wir im weiteren Verlauf der Arbeit Varianten des MDAs für verschiedene Varianten des MOSP Problems. Für das Punkt-zu-Punkt MOSP Problem hat der Targeted MDA (T-MDA) die gleiche asymptotische Laufzeit wie der MDA. Durch einen erhöhten Speicherverbrauch ist er in der Praxis aber deutlich schneller. Die zusätzlich gespeicherten Pfade werden auf eine pseudo-lazy Art verwaltet. Dies ist eine neuartige Methode zur Organisation von explorierten Pfaden, die sicherstellt, dass die Größe der Prioritätswarteschlange des Algorithmus auf höchstens einen Pfad pro Knoten im Graphen beschränkt bleibt. Die Pfade, die aus der Warteschlange zurückgehalten werden, werden in Listen organisiert, die durch Voranstellen oder Anhängen von Pfaden sortiert bleiben. Das heißt, dass nur Konstantzeit-Operationen benötigt werden. Der T-MDA löst größere Instanzen als der MDA und ist auch schneller. Wir untersuchen die Verallgemeinerung des zeitabhängigen Kürzeste Wege Problems auf den multikriteriellen Fall. Wir bieten eine detaillierte Analyse der Grenzen und Möglichkeiten dieser Verallgemeinerung und diskutieren, wann der MDA hierauf anwendbar ist. Für MOSP Instanzen mit großen Mengen optimaler Pfade sind gute Approximationsalgorithmen wichtig. Wir kombinieren den MDA mit einer Technik zur Partitionierung des Ergebnisraums aus der Literatur, um einen neuen FPTAS für das MOSP Problem zu erhalten. Der resultierende MD-FPTAS funktioniert auch für Instanzen mit verallgemeinert zeitabhängigen Kostenfunktionen, was neuartig ist. Schließlich verwenden wir den MDA und seine bikriterielle Version als Unterroutinen, um jeweils das Multiobjective Minimum Spanning Tree (MOMST) Problem und das k-Shortest Simple Path (k-SSP) Problem zu lösen. Eine MO-MST Instanz wird gelöst, indem der MDA auf einen sogenannten Übergangsgraphen angewendet wird. In diesem Graphen haben Pfade äquivalente Kosten zu den Bäumen im ursprünglichen Graphen und somit entsprechen die optimalen Lösungen, die vom MDA im Übergangsgraphen berechnet werden, den optimalen Bäumen im ursprünglichen Graphen. Da der Übergangsgraph eine exponentielle Größe im Verhältnis zur Größe des ursprünglichen Graphen hat, diskutieren wir neue Techniken zur Reduzierung seiner Anzahl von Kanten. Die Lösung des k-SSP Problems, ein skalares Optimierungsproblem, unter Verwendung einer bikriteriellen Unterroutine ist überraschend, aber unser neuer Algorithmus ist sowohl in der Theorie als auch in der Praxis auf dem neuesten Stand

Model-free Optimization of Trajectory And Impedance Parameters on Exercise Robots With Applications To Human Performance And Rehabilitation

This dissertation focuses on the study and optimization of human training and its physiological effects through the use of advanced exercise machines (AEMs). These machines provide an invaluable contribution to advanced training by combining exercise physiology with technology. Unlike conventional exercise machines (CEMs), AEMs provide controllable trajectories and impedances by using electric motors and control systems. Therefore, they can produce various patterns even in the absence of gravity. Moreover, the ability of the AEMs to target multiple physiological systems makes them the best available option to improve human performance and rehabilitation. During the early stage of the research, the physiological effects produced under training by the manual regulation of the trajectory and impedance parameters of the AEMs were studied. Human dynamics appear as not only complex but also unique and time-varying due to the particular features of each person such as its musculoskeletal distribution, level of fatigue,fitness condition, hydration, etc. However, the possibility of the optimization of the AEM training parameters by using physiological effects was likely, thus the optimization objective started to be formulated. Some previous research suggests that a model-based optimization of advanced training is complicated for real-time environments as a consequence of the high level of v complexity, computational cost, and especially the many unidentifiable parameters. Moreover, a model-based method differs from person to person and it would require periodic updates based on physical and psychological variations in the user. Consequently, we aimed to develop a model-free optimization framework based on the use of Extremum Seeking Control (ESC). ESC is a non-model based controller for real-time optimization which its main advantage over similar controllers is its ability to deal with unknown plants. This framework uses a physiological effect of training as bio-feedback. Three different frameworks were performed for single-variable and multi-variable optimization of trajectory and impedance parameters. Based on the framework, the objective is achieved by seeking the optimal trajectory and/or impedance parameters associated with the orientation of the ellipsoidal path to be tracked by the user and the stiffness property of the resistance by using weighted measures of muscle activations

Labeling Methods for Partially Ordered Paths

The landscape of applications and subroutines relying on shortest path computations continues to grow steadily. This growth is driven by the undeniable success of shortest path algorithms in theory and practice. It also introduces new challenges as the models and assessing the optimality of paths become more complicated. Hence, multiple recent publications in the field adapt existing labeling methods in an ad-hoc fashion to their specific problem variant without considering the underlying general structure: they always deal with multi-criteria scenarios and those criteria define different partial orders on the paths. In this paper, we introduce the partial order shortest path problem (POSP), a generalization of the multi-objective shortest path problem (MOSP) and in turn also of the classical shortest path problem. POSP captures the particular structure of many shortest path applications as special cases. In this generality, we study optimality conditions or the lack of them, depending on the objective functions' properties. Our final contribution is a big lookup table summarizing our findings and providing the reader an easy way to choose among the most recent multicriteria shortest path algorithms depending on their problem's weight structure. Examples range from time-dependent shortest path and bottleneck path problems to the fuzzy shortest path problem and complex financial weight functions studied in the public transportation community. Our results hold for general digraphs and therefore surpass previous generalizations that were limited to acyclic graphs

An A* Algorithm for Flight Planning Based on Idealized Vertical Profiles

The Flight Planning Problem is to find a minimum fuel trajectory between two airports in a 3D airway network under consideration of the wind. We show that this problem is NP-hard, even in its most basic version. We then present a novel A* heuristic, whose potential function is derived from an idealized vertical profile over the remaining flight distance. This potential is, under rather general assumptions, both admissible and consistent and it can be computed efficiently. The method outperforms the state-of-the-art heuristic on real-life instances

Eduardo Torroja: Engineer and Constructor

Además de las cubiertas laminares Eduardo Torroja realizó numerosas obras en las que su aportación fundamental fue idear y poner en práctica los procesos constructivos para llevarlas a cabo. Creemos que tanto esta actividad como ingeniero constructor, como su labor divulgadora, con la intención de promover la mejora de la calidad de la construcción basada en un conocimiento científico, tanto de materiales como de técnicas, son una de sus aportaciones fundamentales a la historia de la ingeniería

Cutting Out the Fat: Fatphobia and Vegan Embodiment

Thesis advisor: Stephen J. PfohlUsing qualitative data from semi-structured interviews with vegans of diverse backgrounds and body types, this study aims to investigate how vegans understand their own bodies and the bodies of others in relation to their consumptive practices and habits. The context of fatphobia in vegan activist spaces and communities surrounds this research as a tension within veganism that helps to elucidate the ways vegans use and engage with their bodies, further helping to understand not only vegan embodiment but also how fat vegans navigate these tensions with their own bodies. Vegans often engage with veganism as a tool for better understanding their own bodies and the social identities their bodies are associated with. This reflexivity causes them to not only concern themselves with how they relate to their own bodies but also with how others view and perceive their bodies. Thus, vegans respond to anxieties and fears about these perceptions by constructing their bodies in opposition to the stereotypes others apply to them (unhealthiness, preachiness, militancy, etc.). This may result in the exclusion of some bodies which are socially understood as fitting these roles (such as fat bodies as unhealthy) and, further, the ethical nature of vegan practices also causes these bodies to be seen as immoral or especially indulgent. This research helps to understand more precisely how vegans act as bodies in promoting their veganism and how they sometimes exclude other bodies in their attempts to defend vegan bodies.Thesis (MA) — Boston College, 2023.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Sociology