(Table 1) Ostracode assemblage parameters in sediments of ODP Hole 113-689

During the late Paleocene thermal maximum (ca. 55.50 Ma) mid-bathyal ostracodes at Maud Rise in the Southern Ocean (Ocean Drilling Program Site 689) underwent a sudden, dramatic turnover synchronous with a global extinction in deep-sea benthic foraminifers and with large-scale, short-lived negative excursions in the stable isotope record of foraminiferal calcite. A previously stable and long-lived ostracode assemblage, dominated by heavily calcified, chiefly epifaunal taxa, was replaced within ~10 k.y. by a taxonomically novel association of small, thin-walled opportunistic and generalist forms that persisted for ~25-40 k.y. Thereafter, ostracode faunas recovered and common bathyal forms returned, although species were smaller and/or less-heavily calcified than before the turnover. The complex fabric of change in ostracode shell morphology and assemblage composition and structure reflects both long-term and sudden perturbations in seawater chemistry at this site. Ostracode data are in agreement with the hypothesis that the latest Paleocene extinctions in the deep sea were caused by a change in the dominant source area of intermediate water mass from high altitudes to the subtropics. These data also suggest that warm saline waters persisted at Maud Rise for the next 100 k.y.

Social attitude toward sustainable development in 2025: A case for reinforcing scenario design

This paper shows the role that some foresight tools, such as scenario design, may play in exploring the future impacts of global challenges in our contemporary Society. Additionally, it provides some clues about how to reinforce scenario design so that it displays more in-depth analysis without losing its qualitative nature and communication advantages. Since its inception in the early seventies, scenario design has become one of the most popular foresight tools used in several fields of knowledge. Nevertheless, its wide acceptance has not been seconded by the urban planning academic and professional realm. In some instances, scenario design is just perceived as a story telling technique that generates oversimplified future visions without the support of rigorous and sound analysis. As a matter of fact, the potential of scenario design for providing more in-depth analysis and for connecting with quantitative methods has been generally missed, giving arguments away to its critics. Based on these premises, this document tries to prove the capability of scenario design to anticipate the impacts of complex global challenges and to do it in a more analytical way. These assumptions are tested through a scenario design exercise which explores the future evolution of the sustainable development paradigm (SD) and its implications in the Spanish urban development model. In order to reinforce the perception of scenario design as a useful and added value instrument to urban planners, three sets of implications –functional, parametric and spatial— are displayed to provide substantial and in-depth information for policy makers. This study shows some major findings. First, it is feasible to set up a systematic approach that provides anticipatory intelligence about future disruptive events that may affect the natural environment and socioeconomic fabric of a given territory. Second, there are opportunities for innovating in the Spanish urban planning processes and city governance models. Third, as a foresight tool, scenario design can be substantially reinforced if proper efforts are made to display functional, parametric and spatial implications generated by the scenarios. Fourth, the study confirms that foresight offers interesting opportunities for urban planners, such as anticipating changes, formulating visions, fostering participation and building networks

Bio-inspired FPGA Architecture for Self-Calibration of an Image Compression Core based on Wavelet Transforms in Embedded Systems

A generic bio-inspired adaptive architecture for image compression suitable to be implemented in embedded systems is presented. The architecture allows the system to be tuned during its calibration phase. An evolutionary algorithm is responsible of making the system evolve towards the required performance. A prototype has been implemented in a Xilinx Virtex-5 FPGA featuring an adaptive wavelet transform core directed at improving image compression for specific types of images. An Evolution Strategy has been chosen as the search algorithm and its typical genetic operators adapted to allow for a hardware friendly implementation. HW/SW partitioning issues are also considered after a high level description of the algorithm is profiled which validates the proposed resource allocation in the device fabric. To check the robustness of the system and its adaptation capabilities, different types of images have been selected as validation patterns. A direct application of such a system is its deployment in an unknown environment during design time, letting the calibration phase adjust the system parameters so that it performs efcient image compression. Also, this prototype implementation may serve as an accelerator for the automatic design of evolved transform coefficients which are later on synthesized and implemented in a non-adaptive system in the final implementation device, whether it is a HW or SW based computing device. The architecture has been built in a modular way so that it can be easily extended to adapt other types of image processing cores. Details on this pluggable component point of view are also given in the paper.

Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics

This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC) and Normalized Cuts (NCuts). The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.