Michela Quadrini

AAL domain ontology for event-based human activity recognition

The design of an Ambient Assisted Living (AAL) aims to create better living conditions for the elderly, especially those who choose to live in their own houses, as long as possible. To this objective, AAL systems must mainly monitor the health status of the elderly through the analysis of data gathered via technologies based on sensor devices. Sensors networks produce collections of data of fine-grained nature, regarding general information such as device name, data type, data value, timestamp, but also specific one. The data analysis, due to its granularity and heterogeneity, makes very difficult to infer a clear overall view of the status of the elderly, it demands automatic tools for selecting meaningful data and mapping them in a common conceptual schema. In the last decade, ontologies became widely used tool to describe application domains and to enrich data with its meaning. In this paper, we propose an ontology-based methodology to perform semantic queries on a data repository, where records originated from networks of heterogeneous sources are stored. A semantic query is a pattern matching process that supports the recognition of specific temporal sequences of events that can be extracted from fine-grained data. In our framework a domain ontology are exploited at different levels of abstraction and the reasoning techniques are used to pre-process data for the final temporal analysis. The proposed approach is a deliverable of the ongoing AALISABETH project funded by Region Marche Government; while the software component is integrated into the AALISABETH framework.

Loop-loop Interaction Metrics on RNA Secondary Structures with Pseudoknots

Many methods have been proposed in the literature to face the problem of RNA secondary structures comparison. From a biological point of view, most of these methods are satisfactory for the comparison of pseudoknot free secondary structures, whereas the problem of pseudoknotted motifs comparison has not been solved yet. In this paper, we propose loop-loop interaction metrics, a new measure able to compute the distance of two pseudoknotted secondary structures by comparing loops and their interactions. The new measure is defined for RNA molecules whose structural and biological information is represented as algebraic expressions of hairpin loops, so that each RNA secondary structure can be represented as a word, which describes the interactions among loops and uniquely defines the intersection set, the set of pairs of loops that cross. Hence, the interaction metrics is defined as the symmetric set difference applied to the intersection sets of molecules. To illustrate how to apply the proposed methodology, we compare two RNA molecules, PKB66 and PKB10, extracted from Pseudobase++ database. To test the validity of the measure, we evaluated the evolutionary conservation of the pseudoknot domain of Vertebrate Telomerase RNA.

An integral equation method for the numerical solution of the Burgers equation

Abstract We consider an initial–boundary value problem for the two-dimensional Burgers equation on the plane. This problem is reformulated by an equivalent integral equation on the Fourier transform space. For the solution of this integral equation, two numerical methods are proposed. One of these two methods is based on the properties of the Gaussian function, whereas the other one is based on the FFT algorithm. Finally, the Galerkin method with Gaussian basis functions is applied to the original initial–boundary value problem, in order to compare the performances of the proposed methods with a standard numerical procedure. Some numerical examples are given to evaluate the efficiency of the proposed methods. The performances obtained from these numerical experiments promise that these methods can be applied effectively to more complex problems, such as the Navier–Stokes equation and the turbulence flows.

Topological Classification of RNA Structures via Intersection Graph

We introduce a new algebraic representation of RNA secondary structures as a composition of hairpins, considered as basic loops. Starting from it, we define an abstract algebraic representation and we propose a novel methodology to classify RNA structures based on two topological invariants, the genus and the crossing number. It takes advantage of the abstract representation to easily obtain two intersection graphs: one of the RNA molecule and another one of the relative shape. The edges cardinality of the former corresponds to the number of interactions among hairpins, whereas the edges cardinality of the latter is the crossing number of the shape associated to the molecule. The aforementioned crossing number together with the genus permits to define a more precise energy function than the standard one which is based on the genus only. Our methodology is validated over a subset of RNA structures extracted from Pseudobase++ database, and we classify them according to the two topological invariants.

An algebraic representation for tree alignment of RNA pseudoknotted structures

The methods proposed in the literature for RNA comparison focus mainly on pseudoknot free structures. The comparison of pseudoknotted structures is still a challenge. In this work, we propose a new algebraic representation of RNA secondary structures based on relations among hairpins in terms of nesting, crossing, and concatenation. Such algebraic representation is obtained from a defined multiple context-free grammar, which maps any kind of RNA secondary structures into extended trees, i.e., ordered trees where internal nodes are labeled with algebraic operators and leaves are labeled with loops. These extended trees permit the definition of the RNA secondary structure comparison as a tree alignment problem.