984 resultados para Anaerobic Threshold


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First videographic indication of an Antarctic cold seep ecosystem was recently obtained from the collapsed Larsen B ice shelf, western Weddell Sea (Domack et al., 2005). Within the framework of the R/V Polarstern expedition ANTXXIII-8, we revisited this area for geochemical, microbiological and further videographical examinations. During two dives with ROV Cherokee (MARUM, Bremen), several bivalve shell agglomerations of the seep-associated, chemosynthetic clam Calyptogena sp. were found in the trough of the Crane and Evans glacier. The absence of living clam specimens indicates that the flux of sulphide and hence the seepage activity is diminished at present. This impression was further substantiated by our geochemical observations. Concentrations of thermogenic methane were moderately elevated with 2 µM in surface sediments of a clam patch, increasing up to 9 µM at a sediment depth of about 1 m in the bottom sections of the sediment cores. This correlated with a moderate decrease in sulphate from about 28 mM at the surface down to 23.4 mM, an increase in sulphide to up to 1.43 mM and elevated rates of the anaerobic oxidation of methane (AOM) of up to 600 pmol cm**-3 d**-1 at about 1 m below the seafloor. Molecular analyses indicate that methanotrophic archaea related to ANME-3 are the most likely candidates mediating AOM in sediments of the Larsen B seep.

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The anaerobic oxidation of methane (AOM) with sulfate as terminal electron acceptor is mediated by consortia of methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB). In sediment samples from Hydrate Ridge, the Isis Mud Volcano and the Gulf of Mexico, DSS cells accounted for 3-6% of all DAPI-stained single cells. Out of these, 8-17% were labelled with probe SEEP1a-1441. This translated into relative abundances of single SEEP-SRB1a cells of 0.3% to 0.7%. Contrastingly, in a sediment sample from the Gullfaks oil field, DSS cells accounted for 18% and SEEP-SRB1a for 9% of all single cells. This sediment sample also featured an unusually high abundance of single ANME-2 cells and only very few ANME-2/DSS aggregates in comparison with other AOM habitats. Considering also the nature of the sample, it is likely that the high number of single ANME-2 and SEEP-SRB1a cells were an artifact of sample preparation. Here, harsher sonication was required to remove the microorganisms from coarse sand prior to CARD-FISH analysis.

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In this paper, by employing the threshold regression method, we estimate the average tariff equivalent of fixed costs for the use of a free trade agreement (FTA) among all existing FTAs in the world. It is estimated to be 3.2%. This global estimate serves as a reference rate in the evaluation of each FTA’s fixed costs.

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El entrenamiento con cargas es una actividad anaeróbica glucolítica intensa y se ha comprobado que el error en las estimaciones del gasto energético en esta actividad varía entre un 13 y un 30%. El principal objetivo de este trabajo es describir la contribución anaeróbica de energía en un circuito con cargas. Doce hombres (20-26 años) y diecisiete mujeres (18-29 años) estudiantes de Ciencias de la Actividad Física y del Deporte realizaron un entrenamiento en circuito de cargas a 6 intensidades diferentes (entre el 30% y 80% de su 15RM). Durante la totalidad de los circuitos se registró el gasto energético aeróbico por calorimetría indirecta, la frecuencia cardiaca con pulsómetro Polar® y la concentración de lactato en sangre capilar para medir la contribución anaeróbica. El incremento que produjo la energía anaeróbica se situó entre el 5,1% y un máximo del 13,5%, lo que hace evidente que medir o no la contribución anaeróbica en el entrenamiento en circuito puede provocar un error medio del 9,65%. Existen diferencias significativas (Pmenor que 0,05) entre el gasto energético aeróbico y total (aeróbico+anaeróbico) en todas las intensidades, en un circuito de entrenamiento con cargas a intensidades progresivas.

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Relacionado con línea de investigación del GDS del ISOM ver http://www.isom.upm.es/dsemiconductores.php

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To improve percolation modelling on soils the geometrical properties of the pore space must be understood; this includes porosity, particle and pore size distribution and connectivity of the pores. A study was conducted with a soil at different bulk densities based on 3D grey images acquired by X-ray computed tomography. The objective was to analyze the effect in percolation of aspects of pore network geometry and discuss the influence of the grey threshold applied to the images. A model based on random walk algorithms was applied to the images, combining five bulk densities with up to six threshold values per density. This allowed for a dynamical perspective of soil structure in relation to water transport through the inclusion of percolation speed in the analyses. To evaluate separately connectivity and isolate the effect of the grey threshold, a critical value of 35% of porosity was selected for every density. This value was the smallest at which total-percolation walks appeared for the all images of the same porosity and may represent a situation of percolation comparable among bulks densities. This criterion avoided an arbitrary decision in grey thresholds. Besides, a random matrix simulation at 35% of porosity with real images was used to test the existence of pore connectivity as a consequence of a non-random soil structure.

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In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

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Ionoluminescence (IL) has been used in this work as a sensitive tool to probe the microscopic electronic processes and structural changes produced on quartz by the irradiation with swift heavy ions. The IL yields have been measured as a function of irradiation fluence and electronic stopping power. The results are consistent with the assignment of the 2.7 eV (460 nm) band to the recombination of self-trapped excitons at the damaged regions in the irradiated material. Moreover, it was possible to determine the threshold for amorphization by a single ion impact, as 1:7 keV/nm, which agrees well with the results of previous studies.

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This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.