Abstract
Quantile regression is applied for characterizing long-term sea-level variability in the Baltic Sea from long tide gauge records. The approach allows to quantify not only variability in the mean but also in extreme heights and thus provides a more complete description of regional sea-level variability. In the Baltic, slopes in minima are similar to the classical mean-based ordinary least squares slope, but maxima exhibit larger trends, particularly at the northernmost stations, in the Gulf of Bothnia, likely associated with changes in north Atlantic atmospheric circulation and particularly regional wind patterns. Citation: Barbosa, S. M. ( 2008), Quantile trends in Baltic sea level, Geophys. Res. Lett., 35, L22704, doi: 10.1029/2008GL035182.

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Abstract
A cartographic-oriented model uses algebraic map operations to perform spatial analysis of medical data relative to the human body. A prototype system uses 3D visualization techniques to deliver analysis results. A prototype implementation suggests the model might provide the basis for a medical application tool that introduces new information insight. © 2008 IEEE.

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Objective The main goal of the CHUB (cartographic human body) model is to introduce a cartographic approach that can assist the analysis, visualization and diagnosis of medical images and related data. Method Acartographic model is proposed as a reference framework for the development of computer systems and applications. This model accommodates subtle spatial features of these data that may facilitate diagnosis. Medical images and related data are structured into different "human-referenced" information layers. Algebraic map operations are used to combine these layers and achieve greater insights into the information content. Results Two case studies were considered to evaluate and validate the model: hydrokinetic therapy and the diagnosis of knee osteoarthritis. A prototype based on the CHUB model was implemented and two different approaches were performed to test and evaluate it. Full acceptance of the model was achieved by clinicians who used the CHUB system. Conclusion Acartographic model provides a feasible means for analyzing and visualizing medical image and related data. CHUB is a suitable model that may be used as a common framework for systems, applications and/or support tools that analyze and visualize medical images and related data (for example, in disease diagnosis).

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This paper presents a framework for the design and implementation of learning objects using a competence-based approach. This framework is illustrated by the development of a standalone Windows application (Trilho GOA) whose primary purpose is to create standardized pedagogical contents trough the aggregation and standardization of instructional resources in several formats that can be used later on a Learning Management System (LMS) supporting SCORM 1.2. The paper contains a brief introduction to the developed software, its system architecture, main features and several pedagogical advantages for its users.

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