Palaeontological data about the climatic trends from Chattian to present along the Northeastern Atlantic frontage

Climatic changes that affected the Northeastern Atlantic frontage are analyzed on the basis of the evolution of faunas and floras from the late Oligocene onwards. The study deals with calcareous nannoplankton, marine micro- and macrofaunas, some terrestrial vertebrates and vegetal assemblages. The climate, first tropical, underwent a progressive cooling (North-South thermic gradient). Notable climatic deteriorations (withdrawal towards the South or disappearance of taxa indicative of warm climate and appearance of "cold" taxa) are evidenced mainly during the Middle Miocene and the late Pliocene. Faunas and floras of modern pattern have regained, after the Pleistocene glaciations, a new climatic ranging of a temperate type in the northern part.

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

Enhanced PCA-based localization using depth maps with missing data

In this paper a new method for self-localization of mobile robots, based on a PCA positioning sensor to operate in unstructured environments, is proposed and experimentally validated. The proposed PCA extension is able to perform the eigenvectors computation from a set of signals corrupted by missing data. The sensor package considered in this work contains a 2D depth sensor pointed upwards to the ceiling, providing depth images with missing data. The positioning sensor obtained is then integrated in a Linear Parameter Varying mobile robot model to obtain a self-localization system, based on linear Kalman filters, with globally stable position error estimates. A study consisting in adding synthetic random corrupted data to the captured depth images revealed that this extended PCA technique is able to reconstruct the signals, with improved accuracy. The self-localization system obtained is assessed in unstructured environments and the methodologies are validated even in the case of varying illumination conditions.

Paleoambiental reconstruction based on mineralogical data of quaternary littoral deposits occuring at Cortegaça and Maceda beaches (Ovar, Portugal)

The main goal of the present work is the use of mineralogical data corresponding to sediment fine fractions (silt and clay) of Quaternary littoral deposits for the definition of a more detailed vertical zonography and to discriminate the most significant morphoclimatic changes concerned with sediment source areas and sediment deposition areas. The analysis of the available mineralogical data reveals a vertical evolution of the mineral composition. The following aspects deserve particular reference: 1) fine fractions (<38 nm) are composed of quartz and phyllosilicates associated to feldspars, prevailing over other minerals; however in certain sections iron hydroxides and evaporitic minerals occur in significant amounts; 2) clay fractions (<2 nm) show a general prevalence of illite associated with kaolinite and oscillations, in relative terms, of kaolinite and illite contents. Qualitative and quantitative lateral and vertical variations of clay and non clay minerals allow the discrimination of sedimentary sequences and the establishment of the ritmicity and periodicity of the morphoclimatic Quaternary episodes that occurred in the Cortegaça and Maceda beaches. To each one of the sedimentary sequences corresponds, in a first stage, a littoral environment that increasingly became more continental. Climate would be mild to cold, sometimes with humidity - aridity oscillations. Warmer and moister episodes alternated with cooler and dryer ones.

Miocene sediments from Foz da Fonte and Penedo sections (Lower Tagus basin): clay minerals and isotopic data

Eight depositional sequences (DS) delimited by regional disconformities had been recognized in the Miocene of Lisbon and Setúbal Peninsula areas. In the case of the western coast of the Setúbal Peninsula, outcrops consisting of Lower Burdigalian to Lower Tortonian sediments were studied. The stratigraphic zonography and the environmental considerations are mainly supported on data concerning to foraminifera, ostracoda, vertebrates and palynomorphs. The first mineralogical and geochemical data determined for Foz da Fonte, Penedo Sul and Penedo Norte sedimentary sequences are presented. These analytical data mainly correspond to the sediments' fine fractions. Mineralogical data are based on X-ray diffraction (XRD), carried out on both the less than 38 nm and 2 nm fractions. Qualitative and semi-quantitative determinations of clay and non-clay minerals were obtained for both fractions. The clay minerals assemblages complete the lithostratigraphic and paleoenvironmental data obtained by stratigraphic and palaeontological studies. Some palaeomagnetic and isotopic data are discussed and correlated with the mineralogical data. Multivariate data analysis (Principal Components Analysis) of the mineralogical data was carried out using both R-mode and Q-mode factor analysis.

Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.