Abstract
The detailed study of folding and unfolding events in proteins is becoming central to develop rational therapeutic strategies against maladies such as Alzheimer and Parkinson disease. A promising approach to study the unfolding processes of proteins is through computer simulations. However, these computer simulations generate huge amounts of data that require computational methods for their analysis. In this paper we report on the use of Inductive Logic Programming (ILP) techniques to analyse the trajectories of protein unfolding simulations. The paper describes ongoing work on one of several problems of interest in the protein unfolding setting. The problem we address here is that of explaining what makes secondary structure elements to break down during the unfolding process. We tackle such problem collecting examples of contexts where secondary structures break and (automatically) constructing rules that may be used to suggest the explanations.

Abstract
Unified Communications (UC) have the potential to dramatically simplify and improve enterprise communications, reducing costs and improving revenue opportunities. This paper proposes an architecture of three layers for a UC solution based on open source technologies and open standards. The Infrastructure layer is responsible for the physical IP infrastructure network, the Server Hardware and Operating System layer includes the back-end operating system and server services that can be used by the UC platform and the Business Applications layer integrates the UC with other external applications. Finally, the paper presents the major benefits of UC solutions, giving a special emphasis to the benefits derived for the use of a standards-based I P communications.

Abstract
Atmospheric pressure varies within a wide range of scales and thus a multi-scale description of its variability is particularly appealing. In this study, a scale-by-scale analysis of the global sea-level pressure field is carried out from reanalysis data. Wavelet-based analysis of variance is applied in order to describe the variability of the pressure field in terms of patterns representing the contribution of each scale to the overall variance. Signals at the seasonal scales account for the largest fraction of sea-level pressure variance (typically more than 60%) except in the Southern Ocean, in the Equatorial Pacific and in the North Atlantic. In the Southern Ocean and over the North Atlantic, high-frequency signals contribute to a considerable fraction (30-50%) of the overall variance in sea-level pressure. In the Equatorial Pacific, large-scale variability, associated with ENSO, contributes up to 40% of the total variance.

Abstract

Abstract
Long-term sea-level variability in Chesapeake Bay is examined from long tide gauge records in order to assess the influence of climate factors on sea-level changes in this complex estuarine system. A time series decomposition method based on autoregression is applied to extract flexible seasonal and low-frequency components from the tide gauge records, allowing to analyse long-term sea-level variability not only by estimating linear trends from the records, but also by examining fluctuations in seasonal and long-term patterns. Long-term sea-level variability in Chesapeake Bay shows considerable decadal variability. At the annual scale, variability is mainly determined by atmospheric factors, specifically atmospheric pressure and zonal wind, but no systematic trends are found in the amplitude of the annual cycle. On longer time scales, precipitation rate, a proxy for river discharge, is the main factor influencing decadal sea-level variability. Linear trends in relative sea-level heights range from 2.66 +/- 0.075 mm/year (at Baltimore) to 4.40 +/- 0.086 mm/year (at Hampton Roads) for the 1955-2007 period. Due to the gentle slope of most of the bay margin, a sea-level increase of this magnitude poses a significant threat in terms of wetland loss and consequent environmental impacts.

Abstract