Stable Isotopes Studies in the Urucu Oil Province, Amazon Region, Brazil

The study area is the Urucu Oil Province, Municipality of Coari, State of Amazonas, Brazil. This research represents a contribution to the hydrogeological knowledge in the northern region of Brazil, particularly in the central part of the Amazon rainforest, where researches on isotopic are still incipient. The primary goal was to determine, by stable isotopes 18O and 2H measurements, interrelationships between surface water and groundwater, in order to understand the origin and mechanisms of groundwater recharge and discharge. For this, samples of rainwater, superficial water and groundwater were collected between June 2008 and May 2009 for stable isotopic analyzes. This understanding is important in cases of eventual contaminations of the area, which could degrade the water resources. The results show that the superficial waters are typically light waters and have meteoric origin, and the groundwater recharge is by direct rainfall infiltration with primary evaporation before reaching the groundwater table in the Icá-Solimoes Aquifer System. The isotopic signatures similarities between groundwater and superficial waters indicate both waters’ contributions in the streams and, therefore, in the Urucu river.

Fishermen and Territorial Trends in the Brazilian Fisheries Policies

The fishing activity has been known for centuries by man and is configured as an important source of livelihood and income for many families of Brazilian fishermen. This article tries to do a brief contextualization of fishing in Brazil, as well as discuss the notion of territoriality of sector policies. The trend shown for the future is the need for a planning/mapping of operation areas of productive agents in the country, so that fish stocks can be managed more appropriately. One of the proposals that comes with acceptance and is already being applied in some municipalities is fishing agreements, using co-management mechanisms for planning and use of fisheries resources.

Enhancing Smart Grid with Session-Oriented Communication System to Truly Support Reliability and Robustness

Environmental sustainability issues and the costs of new power generation and transmission have increased the interest in evolving current power grid to new technologies. The Smart Grid is a promising technology, since it allows a distributed computing approach with potentials for self-diagnosing/-healing, reliable multi-user communication and fast hard real-time control. However, the missing standardization associated with heterogeneity of legacy systems and wide-area service demands, makes very challenging to adopt Smart Grid in a cost-effective way. By considering this, we propose the Session-Oriented Communication System (SOCSys) to overcome the above issues by enhancing Smart Grid with truly reliable and robust capabilities over heterogeneous environments. SOCSys achieves this goal by orchestrating session-control with innovative network-centric facilities operating over a wireless mesh Information Network compliant with IEEE 802.11e/s standard. The simulation results show that SOCSys improved network performance in terms of bandwidth utilization and minimization of delay, while consuming low network resources. Graphical analyses showed that SOCSys supported multimedia sessions with excellent quality, where it outperforms the experiments with regular settings.

Data Mining of Spatio-Temporal Variability of Chlorophyll-a Concentrations in a Portion of the Western Atlantic with Low Performance Hardware

The contemporary scientific literature that deals with the dynamics of marine chlorophyll-a concentration is already customarily employing data mining techniques in small geographic areas or regional samples. However, there is little focus on the issue of missing data related to chlorophyll-a concentration estimated by remote sensors. Intending to provide greater scope to the identification of the spatiotemporal distribution patterns of marine chlorophyll-a concentrations, and to improve the reliability of results, this study presents a data mining approach to cluster similar chlorophyll-a concentration behaviors while implementing an iterative spatiotemporal interpolation technique for missing data inference. Although some dynamic behaviors of said concentrations in specific areas are already known by specialists, systematic studies in large geographical areas are still scarce due to the computational complexity involved. For this reason, this study analyzed 18 years of NASA satellite observations in one portion of the Western Atlantic Ocean, totaling more than 60 million records. Additionally, performance tests were carried out in low-cost computer systems to check the accessibility of the proposal implemented for use in computational structures of different sizes. The approach was able to identify patterns with high spatial resolution, accuracy and reliability, rendered in low-cost computers even with large volumes of data, generating new and consistent patterns of spatiotemporal variability. Thus, it opens up new possibilities for data mining research on a global scale in this field of application.

Data Analysis of Multiplex Sequencing at SOLiD Platform:A Probabilistic Approach to Characterization and Reliability Increase

New sequencing technologies such as Illumina/Solexa, SOLiD/ABI, and 454/Roche, revolutionized the biological researches. In this context, the SOLiD platform has a particular sequencing type, known as multiplex run, which enables the sequencing of several samples in a single run. It implies in cost reduction and simplifies the analysis of related samples. Meanwhile, this sequencing type requires an additional filtering step to ensure the reliability of the results. Thus, we propose in this paper a probabilistic model which considers the intrinsic characteristics of each sequencing to characterize multiplex runs and filter low-quality data, increasing the data analysis reliability of multiplex sequencing performed on SOLiD. The results show that the proposed model proves to be satisfactory due to: 1) identification of faults in the sequencing process;2) adaptation and development of new protocols for sample preparation;3) the assignment of a degree of confidence to the data generated;and 4) guiding a filtering process, without discarding useful sequences in an arbitrary manner.