Physical soil attributes of Conilon coffee (Coffea canephora) under organic and conventional management systems.

Coffea sp. is cultivated in large areas, using both conventional and organic management. However, information about the sustainability of these two management systems is still deficient. The objective of the present study was to evaluate the physical properties of soil cultivated with Conilon coffee (C. canephora) under organic and conventional management. Two areas cultivated with Conilon coffee (under organic and conventional management) and a fragment of Atlantic forest, used as a reference, were selected for the experiment. Soil granulometry, hydraulic conductivity, water retention curve, resistance to penetration, porosity, optimal hydric interval, and other physical characteristics were measured at depths of 0 to 10 and 10 to 20 cm. The data was submitted to multivariate and descriptive statistical analyses. Higher similarity was observed between the soil cultivated with Conilon coffee under organic management and the Atlantic forest soil. Soil resistance to penetration at 10, 30, 100, 500 and 1500 kPa, macro porosity, density and total porosity were the main physical properties that differentiated both management systems studied. The non-use of agricultural machinery and the addition of organic matter may be the main reasons for higher soil sustainability observed under organic management when compared with the conventional system.

Soil management systems for sustainable melon cropping in the Submedian of the São Francisco Valley.

Changes in soils management systems, including the application of green manure, are able to increase crop productivity. The aim of this study was to propose a soil management system with the use of green manure to improve the nutritional status and melon productivity in the submedian of the São Francisco Valley. The experiment was installed in Typic Plinthustalf and conducted in split plot. There were two soil tillage systems, tillage (T) and no tillage (NT), and three types of green manure (two vegetal cocktails: VC1- 75% legumes (L) + 25% non-legumes (NL); VC2- 25% L+ 75% NL and spontaneous vegetation (SV)). The experimental design was a randomised block with four replications. Fourteen species of legumes, grasses and oilseeds were used for the composition of the plant cocktails. We evaluated production of the dry shoot and root biomass and carbon and nutrient accumulation by green manures and melon plant. Data were subjected to analysis of variance and the treatment means were compared by Tukey´s test (P<0.05). Shoot biomass production and carbon and nutrient accumulation were higher in plant mixtures compared to spontaneous vegetation. The root system of the plant cocktails added larger quantities of biomass and nutrients to the soil to a depth of 0.60 m when compared to the spontaneous vegetation. The cultivation of plant cocktails with soil tillage, regardless of their composition, is a viable alternative for adding biomass and nutrients to the soil in melon crops in semi-arid conditions, providing productivity increases.

Relationships between labile soil organic carbon fractions under different soil management systems.

ABSTRACT: The study of labile carbon fractions (LCF) provides an understanding of the behavior of soil organic matter (SOM) under different soil management systems and cover crops. The aim of this study was to assess the effect of different soil management systems with respect to tillage, cover crop and phosphate fertilization on the amount of the LCF of SOM. Treatments consisted of conventional tillage (CT) and no-tillage (NT) with millet as the cover crop and a no-tillage system with velvet bean at two phosphorus dosages. Soil samples were collected and analyzed for organic carbon (OC), C oxidizable by KMnO4 (C-KMnO4), particulate OC (POC), microbial biomass carbon and light SOM in the 0.0-0.05, 0.05-0.10 and 0.10-0.20 m soil layers. The Carbon Management Index (CMI) was calculated to evaluate the impacts of soil management treatments on the quality of the SOM. The different LCFs are sensitive to different soil management systems, and there are significant correlations between them. C-KMnO4 is considered the best indicator of OC carbon lability. In the soil surface layers, the CT reduced the carbon content in all of the labile fractions of the SOM. The use of phosphorus led to the accumulation of OC and carbon in the different soil fractions regardless of the tillage system or cover crop. The application of phosphate fertilizer improved the ability of the NTsystem to promote soil quality, as assessed by the CMI.

Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

Multi-version Speculative Concurrency Control with Delayed Commit

This paper presents an algorithm which extends the relatively new notion of speculative concurrency control by delaying the commitment of transactions, thus allowing other conflicting transactions to continue execution and commit rather than restart. This algorithm propagates uncommitted data to other outstanding transactions thus allowing more speculative schedules to be considered. The algorithm is shown always to find a serializable schedule, and to avoid cascading aborts. Like speculative concurrency control, it considers strictly more schedules than traditional concurrency control algorithms. Further work is needed to determine which of these speculative methods performs better on actual transaction loads.

Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.

The ocean sampling day consortium.

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.

Teaching, learning and assessment in MSc. Databases units at University of Greenwich

In this paper we look at ways of delivering and assessing learning on database units offered on higher degree programmes (MSc) in the School of Computing and Mathematical Sciences at the University of Greenwich. Of critical importance is the teaching methods employed for verbal disposition, practical laboratory exercises and a careful evaluation of assessment methods and assessment tools in view of the fact that databases involve not only database design but also use of practical tools, such as database management systems (DBMSs) software, human designers, database administrators (DBA) and end users. Our goal is to clearly identify potential key success factors in delivering and assessing learning in both practical and theoretical aspects of database course units.

Tourism planning informatization

The Tourism activity, due to its own characteristics, causes high environmental impact and its development should be influenced by the environmental characteristics of each region. The Information Systems, mainly those which represent the geographical information, will permit the development of a design, allowing the Decision-Maker the consult, the management and the presentation of decision schemes based on the defined measures of the Tourism Planning of a region. As the information associated with this design should be real and update, the Internet should be used as a means of access to the information of the region. The design presents the schemes associated to each decision, offering competitive advantages to the Decision-Makers involved in the decision process, since it is possible to evaluate, foresee and control the future environmental impacts of Tourism.

GIS on tourism planning: preventing the impacts caused by the developing tourism activity in a specific site

The environment is one of the greatest concerns of humankind. Nowadays, the activities which improve or destroy it must be assessed and controlled by efficient means which should permit the control of environmental impact caused by the development of these activities. This document presents an information system implementation, as a Decision Support system, allowing the Decision Maker to evaluate, foresee and control the future environmental impact of Tourism through consultation, the management and the presentation of decision schemes based on defined measures of a regional tourism planning.

Aprendizagem baseada em projetos na consolidação de conceitos de programação de linguagens SCRIPT

Relatório da prática de ensino supervisionada, Mestrado em Ensino de Informática, Universidade de Lisboa, 2014

Comuns: An Open-Data Provider, Explorer and Analytic Toolbox Based on FOSS

Contém resumo

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Managing object identity with less I/O operations

Non-conventional database management systems are used to achieve a better performance when dealing with complex data. One fundamental concept of these systems is object identity (OID). Two techniques can be used for the implementation of OIDs: physical or logical. A logical implementation of OIDs, based on an Indirection Table, is used by NuGeM, a multimedia data manager kernel which is described in this paper. NuGeM Indirection Table allows the relocation of all pages in a database. The proposed strategy modifies the workings of this table so that it is possible to reduce considerably the number of I/O operations during the request and release of pages containing objects and their OIDs. Tests show a reduction of 84% in reading operations and a 67% reduction in writing operations when pages are requested. Although no changes were observed in writing operations during the release of pages, a 100% of reduction in reading operations was obtained. © 2012 IEEE.