Android App para Multilingual Central Repository

El objetivo del proyecto es crear una aplicación Android usando la base de conocimiento multilingüe Multilingual Central Repository 3.0 (MCR 3.0).

The central nervous control of walking in the locust, Schistocerca Americana

Rhythmic motor behaviors in all animals appear to be under the control of "central pattern generator" circuits, neural circuits which can produce output patterns appropriate for behavior even when isolated from their normal peripheral inputs. Insects have been a useful model system in which to study the control of legged terrestrial locomotion. Much is known about walking in insects at the behavioral level, but to date there has been no clear demonstration that a central pattern generator for walking exists. The focus of this thesis is to explore the central neural basis for locomotion in the locust, Schistocerca americana.

Rhythmic motor patterns could be evoked in leg motor neurons of isolated thoracic ganglia of locusts by the muscarinic agonist pilocarpine. These motor patterns would be appropriate for the movement of single legs during walking. Rhythmic patterns could be evoked in all three thoracic ganglia, but the segmental rhythms differed in their sensitivities to pilocarpine, their frequencies, and the phase relationships of motor neuron antagonists. These different patterns could be generated by a simple adaptable model circuit, which was both simulated and implemented in VLSI hardware. The intersegmental coordination of leg motor rhythms was then examined in preparations of isolated chains of thoracic ganglia. Correlations between motor patterns in different thoracic ganglia indicated that central coupling between segmental pattern generators is likely to contribute to the coordination of the legs during walking.

The work described here clearly demonstrates that segmental pattern generators for walking exist in insects. The pattern generators produce motor outputs which are likely to contribute to the coordination of the joints of a limb, as well as the coordination of different limbs. These studies lay the groundwork for further studies to determine the relative contributions of central and sensory neural mechanisms to terrestrial walking.

Addressing and adapting to contemporary coastal management issues in the central Philippines

With arguably the world’s most decentralized coastal governance regime, the Philippines has implemented integrated coastal management (ICM) for over 30 years as one of the most successful frameworks for coastal resource management in the country. Anthropogenic drivers continue to threaten the food security and livelihood of coastal residents; contributing to the destruction of critical marine habitats, which are heavily relied upon for the goods and services they provide. ICM initiatives in the Philippines have utilized a variety of tools, particularly marine protected areas (MPAs), to promote poverty alleviation through food security and sustainable forms of development. From the time marine reserves were first shown to effectively address habitat degradation and decline in reef fishery production (Alcala et al., 2001) over 1,100 locally managed MPAs have been established in the Philippines; yet only 10-20% of these are effectively managed (White et al., 2006; PhilReefs, 2008). In order to increase management effectiveness, biophysical, legal, institutional and social linkages need to be strengthened and “scaled up” to accommodate a more holistic systems approach (Lowry et al., 2009). This summary paper incorporates the preliminary results of five independently conducted studies. Subject areas covered are the social and institutional elements of MPA networks, ecosystem-based management applicability, financial sustainability and the social vulnerability of coastal residents to climate change in the Central Philippines. Each section will provide insight into these focal areas and suggest how management strategies may be adapted to holistically address these contemporary issues. (PDF contains 4 pages)

Distributed optimization in power networks and general multi-agent systems

The dissertation studies the general area of complex networked systems that consist of interconnected and active heterogeneous components and usually operate in uncertain environments and with incomplete information. Problems associated with those systems are typically large-scale and computationally intractable, yet they are also very well-structured and have features that can be exploited by appropriate modeling and computational methods. The goal of this thesis is to develop foundational theories and tools to exploit those structures that can lead to computationally-efficient and distributed solutions, and apply them to improve systems operations and architecture.

Specifically, the thesis focuses on two concrete areas. The first one is to design distributed rules to manage distributed energy resources in the power network. The power network is undergoing a fundamental transformation. The future smart grid, especially on the distribution system, will be a large-scale network of distributed energy resources (DERs), each introducing random and rapid fluctuations in power supply, demand, voltage and frequency. These DERs provide a tremendous opportunity for sustainability, efficiency, and power reliability. However, there are daunting technical challenges in managing these DERs and optimizing their operation. The focus of this dissertation is to develop scalable, distributed, and real-time control and optimization to achieve system-wide efficiency, reliability, and robustness for the future power grid. In particular, we will present how to explore the power network structure to design efficient and distributed market and algorithms for the energy management. We will also show how to connect the algorithms with physical dynamics and existing control mechanisms for real-time control in power networks.

The second focus is to develop distributed optimization rules for general multi-agent engineering systems. A central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to the given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent’s control on the least amount of information possible. Our work focused on achieving this goal using the framework of game theory. In particular, we derived a systematic methodology for designing local agent objective functions that guarantees (i) an equivalence between the resulting game-theoretic equilibria and the system level design objective and (ii) that the resulting game possesses an inherent structure that can be exploited for distributed learning, e.g., potential games. The control design can then be completed by applying any distributed learning algorithm that guarantees convergence to the game-theoretic equilibrium. One main advantage of this game theoretic approach is that it provides a hierarchical decomposition between the decomposition of the systemic objective (game design) and the specific local decision rules (distributed learning algorithms). This decomposition provides the system designer with tremendous flexibility to meet the design objectives and constraints inherent in a broad class of multiagent systems. Furthermore, in many settings the resulting controllers will be inherently robust to a host of uncertainties including asynchronous clock rates, delays in information, and component failures.

Conformal geometry processing

This thesis introduces fundamental equations and numerical methods for manipulating surfaces in three dimensions via conformal transformations. Conformal transformations are valuable in applications because they naturally preserve the integrity of geometric data. To date, however, there has been no clearly stated and consistent theory of conformal transformations that can be used to develop general-purpose geometry processing algorithms: previous methods for computing conformal maps have been restricted to the flat two-dimensional plane, or other spaces of constant curvature. In contrast, our formulation can be used to produce---for the first time---general surface deformations that are perfectly conformal in the limit of refinement. It is for this reason that we commandeer the title Conformal Geometry Processing.

The main contribution of this thesis is analysis and discretization of a certain time-independent Dirac equation, which plays a central role in our theory. Given an immersed surface, we wish to construct new immersions that (i) induce a conformally equivalent metric and (ii) exhibit a prescribed change in extrinsic curvature. Curvature determines the potential in the Dirac equation; the solution of this equation determines the geometry of the new surface. We derive the precise conditions under which curvature is allowed to evolve, and develop efficient numerical algorithms for solving the Dirac equation on triangulated surfaces.

From a practical perspective, this theory has a variety of benefits: conformal maps are desirable in geometry processing because they do not exhibit shear, and therefore preserve textures as well as the quality of the mesh itself. Our discretization yields a sparse linear system that is simple to build and can be used to efficiently edit surfaces by manipulating curvature and boundary data, as demonstrated via several mesh processing applications. We also present a formulation of Willmore flow for triangulated surfaces that permits extraordinarily large time steps and apply this algorithm to surface fairing, geometric modeling, and construction of constant mean curvature (CMC) surfaces.

Designing superresolution optical pupil filter with constrained global optimization algorithm

In this paper, a new method for designing three-zone optical pupil filter is presented. The phase-only optical pupil filter and the amplitude-only optical pupil filters were designed. The first kind of pupil for optical data storage can increase the transverse resolution. The second kind of pupil filter can increase the axial and transverse resolution at the same time, which is applicable in three-dimension imaging in confocal microscopy. (C) 2007 Elsevier GmbH. All rights reserved.

Small Indigenous Freshwater Fish Species: their Role in Poverty Alleviation, Food Security and Conservation of Biodiversity, 23-25 February 2010, Central Inland Fisheries Research Institute, Barrackpore, Kolkata, West Bengal. Workshop report

This is the report on the workshop on “Small Indigenous Freshwater Fish Species: Their Role in Poverty Alleviation, Food Security and Conservation of Biodiversity”, organized by the International Collective in Support of Fishworkers(ICSF) in collaboration with the Inland Fisheries Society of India (IFSI). The workshop was a forum for exchange of views on the role of small indigenous freshwater fish species (SIFFS) in enhancing rural food supply and livelihood security, and in conserving biodiversity. The workshop also discussed the socioeconomic and cultural contexts for the culture and capture of SIFFS, and how to enhance access—especially for women—to better incomes, livelihoods and nutritional security, through appropriate policy spaces. This report provides a fresh focus on SIFFS, usually regarded as ‘trash’ fish. It urges scientists, researchers and decisionmakers to develop policy and legislative measures to ensure the conservation and promotion of SIFFS, both in capture- and culture-fisheries systems. This report will be useful for fishworker organizations, researchers, policymakers, fish farmers, members of civil society and anyone interested in fisheries and livelihoods. (PDF contains 86 pages)

Aseismic deformation in subduction megathrusts : central Andes and north-east Japan

We aim to characterize fault slip behavior during all stages of the seismic cycle in subduction megathrust environments with the eventual goal of understanding temporal and spatial variations of fault zone rheology, and to infer possible causal relationships between inter-, co- and post-seismic slip, as well as implications for earthquake and tsunami hazard. In particular we focus on analyzing aseismic deformation occurring during inter-seismic and post-seismic periods of the seismic cycle. We approach the problem using both Bayesian and optimization techniques. The Bayesian approach allows us to completely characterize the model parameter space by searching a posteriori estimates of the range of allowable models, to easily implement any kind of physically plausible a priori information and to perform the inversion without regularization other than that imposed by the parameterization of the model. However, the Bayesian approach computational expensive and not currently viable for quick response scenarios. Therefore, we also pursue improvements in the optimization inference scheme. We present a novel, robust and yet simple regularization technique that allows us to infer robust and somewhat more detailed models of slip on faults. We apply such methodologies, using simple quasi-static elastic models, to perform studies of inter- seismic deformation in the Central Andes subduction zone, and post-seismic deformation induced by the occurrence of the 2011 Mw 9.0 Tohoku-Oki earthquake in Japan. For the Central Andes, we present estimates of apparent coupling probability of the subduction interface and analyze its relationship to past earthquakes in the region. For Japan, we infer high spatial variability in material properties of the megathrust offshore Tohoku. We discuss the potential for a large earthquake just south of the Tohoku-Oki earthquake where our inferences suggest dominantly aseismic behavior.

Optimization of single attosecond x-ray pulses by genetic algorithm control of the chirp and initial phase of 5 fs laser pulses

We show that the peak intensity of single attosecond x-ray pulses is enhanced by 1 or 2 orders of magnitude, the pulse duration is greatly compressed, and the optimal propagation distance is shortened by genetic algorithm optimization of the chirp and initial phase of 5 fs laser pulses. However, as the laser intensity increases, more efficient nonadiabatic self-phase matching can lead to a dramatically enhanced harmonic yield, and the efficiency of optimization decreases in the enhancement and compression of the generated attosecond pulses. (c) 2006 Optical Society of America.