Abstract
Understanding protein folding and unfolding mechanisms are a central problem in molecular biology. Data obtained from molecular dynamics unfolding simulations may provide valuable insights for a better understanding of these mechanisms. Here, we propose the application of an augmented version of hierarchical clustering analysis to detect clusters of amino-acid residues with similar behavior in protein unfolding simulations. These clusters hold similar global pattern behavior of solvent accessible surface area (SASA) variation in unfolding simulations of the protein Transthyretin (TTR). Classical hierarchical clustering was applied to build a dendrogram based on the SASA variation of each amino-acid residue. The dendrogram was enriched with background information on the amino-acid residues, enabling the extraction of sub-clusters with well differentiated characteristics.

Abstract
In this paper we derive a set of approximate but general bilinear Kalman filter equations for a multiinput multi-output bilinear stochastic system driven by general autocorrelated inputs. The derivation is based on a convergent Picard sequence of linear stochastic state-space subsystems. We also derive necessary and sufficient conditions for a steady-state solution to exist. Provided all the eigenvalues of a chain of structured matrices are inside the unit circle, the approximate bilinear Kalman filter equations converge to a stationary value. When the input is a zero-mean white noise process, the approximate bilinear Kalman filter equations coincide with those of the well known bilinear Kalman filter model operating under white noise inputs.

Abstract
In this paper we present a case study involving mathematical modeling, system identification, and controller design of a two tank fluid level system. The case study is motivated by a realistic application of a two tank problem. We address some fundamental control oriented issues such as physical plant design and identification, transformation from discrete-time to continuous-time, and finally the controller design. We also introduce a novel physical system identification algorithm consisting of subspace identification, followed by a similarity transformation computation to extract the physical parameters of the system. The controller design is done by Pole Placement.

Abstract
Recent advances in mobile positioning systems and telecommunications are providing the technology needed for the development of location-aware tele-care applications. This paper introduces CAALYX - Complete Ambient Assisted Living Experiment, an EU-funded project that aims at increasing older people's autonomy and self-confidence by developing a wearable light device capable of measuring specific vital signs of the elderly, detecting falls and location, and communicating automatically in real-time with his/her care provider in case of an emergency, wherever the older person happens to be, at home or outside.

Abstract
After characterization of preferred conditions for Helicobacter pylori survival in the sessile state, it was observed that the bacterium transforms from spiral to coccoid under mild circumstances, whereas under extreme ones it is unable to undergo shape modification. This strongly supports the view that transformation into the coccoid form is an active, biologically led process, switched on by the bacterium as a protection mechanism.

Abstract
The problem of discovering previously unknown frequent patterns in time series, also called motifs, has been recently introduced. A motif is a subseries pattern that appears a significant number of times. Results demonstrate that motifs may provide valuable insights about the data and have a wide range of applications in data mining tasks. The main motivation for this study was the need to mine time series data from protein folding/unfolding simulations. We propose an algorithm that extracts approximate motifs, i.e. motifs that capture portions of time series with a similar and eventually symmetric behavior. Preliminary results on the analysis of protein unfolding data support this proposal as a valuable tool. A.dditional experiments demonstrate that the application of utility of our algorithm is not limited to this particular problem. Rather it can be an interesting tool to be applied in many real world problems.