2 resultados para horse riding

em Universidad Politécnica de Madrid


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Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

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Mine soils usually contain large levels of heavy metals and poor fertility conditions which limit their reclamation and the application of phyto-remediation technologies. Two organic waste materials (pine bark compost and sheep and horse manure compost), with different pHs and varying degrees of humification and nutrient contents, were applied as amendments to assess their effects on copper (Cu) and zinc (Zn) bioavailability and on fertility conditions of mine soils. Soil samples collected from two abandoned mining areas near Madrid (Spain) were mixed with 0, 30 and 60 t ha?1 of the organic amendments. The concentrations of metals among the different mineral and organic fractions of soil were determined by several extraction procedures to study the metal distribution in the solid phase of the soil affected by the organic amendments. The results showed that the manure amendment increased the soil pH and the cation exchange capacity and enhanced the nutrient levels of these soils. The pine bark amendment decreased the soil pH and did not significantly change the nutrient status of soil. Soil pH, organic matter content and its degree of humification, which were altered by the amendments, were the main factors affecting Cu fractionation. Zn fractionation was mainly affected by soil pH. The addition of manure not only improved soil fertility, but also decreased metal bioavailability resulting in a reduction of metal toxicity. Conversely, pine bark amendment increased metal ioavailability. The use of sheep and horse manure could be a cost-effective practice for the restoration of contaminated mine soils.