Spatial variability of soil physical properties in two management systems in sugarcane crop

O objetivo deste trabalho foi caracterizar a variabilidade espacial da densidade do solo (Ds), teor de água no solo (θ) e porosidade total (Pt) em dois sistemas de manejo da colheita da cana-de-açúcar, com queima e sem queima, em um Latossolo Vermelho, na camada de 0-0,20 m. A área de estudo está localizada no município de Rio Brilhante-MS, na Usina Eldorado. A parcela de cada talhão apresentou malha com comprimento de 180 m e largura de 145,6 m, perfazendo 90 pontos distribuídos na forma de uma grade de nove colunas por dez linhas, com pontos distanciados 20 m de seu vizinho. Foram coletadas amostras de solo na camada de 0-0,20 m, nos anos agrícolas de 2007/2008 e 2008/2009. O sistema de colheita com queima apresentou maior densidade em relação ao mecanizado, nos dois períodos de análise. O teor de água no solo, assim como a porosidade, teve aumento proporcional com relação à diminuição da densidade do sistema de colheita com queima para com o mecanizado.

Effects of nanoscale spatial inhomogeneity in strongly correlated systems

We calculate ground-state energies and density distributions of Hubbard superlattices characterized by periodic modulations of the on-site interaction and the on-site potential. Both density-matrix renormalization group and density-functional methods are employed and compared. We find that small variations in the on-site potential v(i) can simulate, cancel, or even overcompensate effects due to much larger variations in the on-site interaction U-i. Our findings highlight the importance of nanoscale spatial inhomogeneity in strongly correlated systems, and call for a reexamination of model calculations assuming spatial homogeneity.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

Disturbance detection for optimal database storage in electrical distribution systems using artificial immune systems with negative selection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Metacommunity organisation, spatial extent and dispersal in aquatic systems: patterns, processes and prospects

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

BtoxDB: a comprehensive database of protein structural data on toxin-antitoxin systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Global Lithological Map Database v1.0 (gridded to 0.5° spatial resolution)

Lithology describes the geochemical, mineralogical, and physical properties of rocks. It plays a key role in many processes at the Earth surface, especially the fluxes of matter to soils, ecosystems, rivers, and oceans. Understanding these processes at the global scale requires a high resolution description of lithology. A new high resolution global lithological map (GLiM) was assembled from existing regional geological maps translated into lithological information with the help of regional literature. The GLiM represents the rock types of the Earth surface using 1,235,400 polygons. The lithological classification consists of three levels. The first level contains 16 lithological classes comparable to previously applied definitions in global lithological maps. The additional two levels contain 12 and 14 subclasses, respectively, which describe more specific rock attributes. According to the GLiM, the Earth is covered by 64 % sediments (a third of which is carbonates), 13 % metamorphics, 7 % plutonics, and 6 % volcanics, and 10% are covered by water or ice. The high resolution of the GLiM allows observation of regional lithological distributions which often vary from the global average. The GLiM enables regional analysis of Earth surface processes at global scales.

Modelling spatial decisión support systems focused on the development of a data warehouse: applying software engineering

Nowadays, organizations have plenty of data stored in DB databases, which contain invaluable information. Decision Support Systems DSS provide the support needed to manage this information and planning médium and long-term ?the modus operandi? of these organizations. Despite the growing importance of these systems, most proposals do not include its total evelopment, mostly limiting itself on the development of isolated parts, which often have serious integration problems. Hence, methodologies that include models and processes that consider every factor are necessary. This paper will try to fill this void as it proposes an approach for developing spatial DSS driven by the development of their associated Data Warehouse DW, without forgetting its other components. To the end of framing the proposal different Engineering Software focus (The Software Engineering Process and Model Driven Architecture) are used, and coupling with the DB development methodology, (and both of them adapted to DW peculiarities). Finally, an example illustrates the proposal.

Performance evaluation of database replication systems.

One of the most demanding needs in cloud computing is that of having scalable and highly available databases. One of the ways to attend these needs is to leverage the scalable replication techniques developed in the last decade. These techniques allow increasing both the availability and scalability of databases. Many replication protocols have been proposed during the last decade. The main research challenge was how to scale under the eager replication model, the one that provides consistency across replicas. In this paper, we examine three eager database replication systems available today: Middle-R, C-JDBC and MySQL Cluster using TPC-W benchmark. We analyze their architecture, replication protocols and compare the performance both in the absence of failures and when there are failures.

Comparison of Architectures and Performance of Database Replication Systems

One of the most demanding needs in cloud computing and big data is that of having scalable and highly available databases. One of the ways to attend these needs is to leverage the scalable replication techniques developed in the last decade. These techniques allow increasing both the availability and scalability of databases. Many replication protocols have been proposed during the last decade. The main research challenge was how to scale under the eager replication model, the one that provides consistency across replicas. This thesis provides an in depth study of three eager database replication systems based on relational systems: Middle-R, C-JDBC and MySQL Cluster and three systems based on In-Memory Data Grids: JBoss Data Grid, Oracle Coherence and Terracotta Ehcache. Thesis explore these systems based on their architecture, replication protocols, fault tolerance and various other functionalities. It also provides experimental analysis of these systems using state-of-the art benchmarks: TPC-C and TPC-W (for relational systems) and Yahoo! Cloud Serving Benchmark (In- Memory Data Grids). Thesis also discusses three Graph Databases, Neo4j, Titan and Sparksee based on their architecture and transactional capabilities and highlights the weaker transactional consistencies provided by these systems. It discusses an implementation of snapshot isolation in Neo4j graph database to provide stronger isolation guarantees for transactions.

Global database of surface ocean particulate organic carbon export fluxes diagnosed from the 234Th technique

Through the processes of the biological pump, carbon is exported to the deep ocean in the form of dissolved and particulate organic matter. There are several ways by which downward export fluxes can be estimated. The great attraction of the 234Th technique is that its fundamental operation allows a downward flux rate to be determined from a single water column profile of thorium coupled to an estimate of POC/234Th ratio in sinking matter. We present a database of 723 estimates of organic carbon export from the surface ocean derived from the 234Th technique. Data were collected from tables in papers published between 1985 and 2013 only. We also present sampling dates, publication dates and sampling areas. Most of the open ocean Longhurst provinces are represented by several measurements. However, the Western Pacific, the Atlantic Arctic, South Pacific and the South Indian Ocean are not well represented. There is a variety of integration depths ranging from surface to 220m. Globally the fluxes ranged from -22 to 125 mmol of C/m**2/d. We believe that this database is important for providing new global estimate of the magnitude of the biological carbon pump.

Dynamic multi-resolution spatial object derivation for mobile and WWW applications

Online geographic information systems provide the means to extract a subset of desired spatial information from a larger remote repository. Data retrieved representing real-world geographic phenomena are then manipulated to suit the specific needs of an end-user. Often this extraction requires the derivation of representations of objects specific to a particular resolution or scale from a single original stored version. Currently standard spatial data handling techniques cannot support the multi-resolution representation of such features in a database. In this paper a methodology to store and retrieve versions of spatial objects at, different resolutions with respect to scale using standard database primitives and SQL is presented. The technique involves heavy fragmentation of spatial features that allows dynamic simplification into scale-specific object representations customised to the display resolution of the end-user's device. Experimental results comparing the new approach to traditional R-Tree indexing and external object simplification reveal the former performs notably better for mobile and WWW applications where client-side resources are limited and retrieved data loads are kept relatively small.