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Understanding the role played by genetic variations in diseases, exploring genomic variants and discovering disease-associated loci are among the most pressing challenges of genomic medicine. A huge and ever-increasing amount of information is available to researchers to address these challenges. Unfortunately, it is stored in fragmented ontologies and databases, which use heterogeneous formats and poorly integrated schemas. To overcome these limitations, we propose a linked data approach, based on the formalism of multilayer networks, able to integrate and harmonize biomedical information from multiple sources into a single dense network covering different aspects on Neuroendocrine Neoplasms (NENs). The proposed integration schema consists of three interconnected layers representing, respectively, information on the disease, on the affected genes, on the related biological processes and molecular functions. An easy-to-use client-server application was also developed to browse and search for information on the model supporting multilayer network analysis.

A weighted likelihood technique for robust estimation of multivariate Wrapped distributions of data points scattered on a p-dimensional torus is proposed. The occurrence of outliers in the sample at hand can badly compromise inference for standard techniques such as maximum likelihood method. Therefore, there is the need to handle such model inadequacies in the fitting process by a robust technique and an effective downweighting of observations not following the assumed model. Furthermore, the employ of a robust method could help in situations of hidden and unexpected substructures in the data. Here, it is suggested to build a set of data-dependent weights based on the Pearson residuals and solve the corresponding weighted likelihood estimating equations. In particular, robust estimation is carried out by using a Classification EM algorithm whose M-step is enhanced by the computation of weights based on current parameters’ values. The finite sample behavior of the proposed method has been investigated by a Monte Carlo numerical study and real data examples.

In psychology and philosophy, emotion is a subjective, conscious experience characterized primarily by psychophysiological expressions, biological reactions, and mental states. Emotion could be also considered as a “positive or negative experience” that is associated with a particular pattern of physiological activity. So, the extraction and recognition of emotions from multimedia contents is becoming one of the most challenging research topics in human–computer interaction. Facial expressions, posture, gestures, speech, emotive changes of physical parameters (e.g. body temperature, blush and changes in the tone of the voice) can reflect changes in the user׳s emotional state and all this kind of parameters can be detected and interpreted by a computer leading to the so-called “affective computing”. In this paper an approach for the extraction of emotions from images and videos will be introduced. In particular, it involves the adoption of action units׳ extraction from facial expression according to the Ekman theory. The proposed approach has been tested on standard and real datasets with interesting and promising results.

We investigate the problem of stabilising the attitude of a 3-D axially symmetric pendulum. The system is assumed to be actuated by two torques acting on a plane orthogonal to the symmetry axis. We develop a smooth control law to stabilise the pendulum to the upright position with a given orientation starting from almost all initial conditions. Our approach consists in two steps: first, stabilising the kinematic subsystem by using the angular velocity as a virtual input; second, exploiting the actual inputs to force the angular velocity to follow the reference designed in the previous step.

This paper investigates the problem of making the cart of a spherical pendulum follow a circular path with constant speed, while guaranteeing that the pendulum does not fall over. A solution methodology is presented which is hierarchical in nature. First, one of the two control inputs is used to stabilize the angle of the pendulum from the vertical axis at a constant value. The remaining control input is used to make the cart converge to the circular path with a desired speed.

We consider the control of differentially flat linear delay systems with constraints. The constraints can be given on the state and/or on the control. Linear delay systems are here envisioned as modules over a ring of differential and distributed delay operators. Due to the nice Bezout property that this ring enjoys, the controllability notions of freeness, projectivity and torsion freeness coincide. Thanks to the flatness (corresponding to freeness for linear systems) property, all constraints are reported through the flat output (the basis of the corresponding module). We then make use of polynomial B-splines as specialisations for the flat output; the constraints are then expressed as inequalities in these B-splines control points. Some examples illustrate the effectiveness of the approach.

This paper presents an aeroelastic formulation based on the Finite Element Method (FEM) for performance and stability predictions of isolated horizontal axis wind turbines. Hamilton’s principle is applied to derive the equations of blade aeroelasticity, by coupling a nonlinear beam model with Beddoes-Leishman sectional unsteady aerodynamics. A devoted fifteen-degrees-of-freedom finite element to model kinematics and elastic behaviour of rotating blades is introduced. Spatial discretization of the aeroelastic equations is carried-out to derive a set of coupled nonlinear ordinary differential equations solved by a time-marching algorithm. The proposed formulation may be enhanced to face the analysis of advanced-shape blades, as well as the inclusion of the presence of the tower, and represents the first step of an ongoing activity on wind energy based on a FEM approach; as a consequence, results have to be considered as preliminary. Due to similarities between wind turbine and helicopter rotor blades aeroelasticity, validation results firstly concern with the aeroelastic response of helicopter rotors in hovering. Next, the performance of a wind turbine in terms of blade elastic response and delivered thrust and power is predicted and compared to that provided by a validated aeroelastic solver based on a modal approach as well as with experimental data.

A Boundary Element Method (BEM) hydrodynamics combined with a flow-alignment technique to evaluate blades shed vorticity is presented and applied to a marine propeller in open water. Potentialities and drawbacks of this approach in capturing propeller performance, slipstream velocities, blade pressure distribution and pressure disturbance in the flow-field are highlighted by comparisons with available experiments and RANSE results. In particular, correlations between the shape of the convected vortex-sheet and the accuracy of BEM results are discussed throughout the paper. To this aim, the analysis of propeller thrust and torque is the starting point towards a detailed discussion on the capability of a 3-D free-wake BEM hydrodynamic approach to describe the local features of the flow-field behind the propeller disk, in view of applications to propulsive configurations where the shed wake plays a dominant role.

A Boundary Element Method (BEM) hydrodynamics combined with a flow-alignment technique to evaluate blades shed vorticity is presented and applied to a marine propeller in open water. Potentialities and drawbacks of this approach in capturing propeller performance, slipstream velocities, blade pressure distribution and pressure disturbance in the flow-field are highlighted by comparisons with available experiments and RANSE results. In particular, correlations between the shape of the convected vortex- sheet and the accuracy of BEM results are discussed throughout the paper. To this aim, the analysis of propeller thrust and torque is the starting point towards a detailed discussion on the capability of a 3-D free-wake BEM hydrodynamic approach to describe the local features of the flow-field behind the propeller disk, in view of applications to propulsive configurations where the shed wake plays a dominant role.

In today's competitive global market, understanding quickly customers' needs is a primary task for a successful design and implementation of customised products. For this aim an effective approach is the adoption of a product configurator. The product configuration is the activity of customising a product to meet the needs of a particular customer that, usually, expresses his/her preferences by the use of the natural language. In this scenario a challenging problem is the definition of a common vocabulary that opens possibilities such as the ability to express the customer requirements and to exchange knowledge. For this aim the adoption of the ontological formalism is an effective approach. Ontology, in fact, is a key factor for enabling interoperability across heterogeneous systems, services and users. This paper presents an ontology–based configurator system that maximally satisfies users' needs starting from the desired requirements, the available components, the context information and previous similar configurations.

This paper addresses the problem of stabilizing uncertain nonlinear plants over a shared limited-bandwidth packet-switching network for which both the time between consecutive accesses to each node (MATI) and the transmission and processing delays (MAD) for measurements and control packets are bounded. While conventional control loops are designed to work with circuit-switching networks, where dedicated communication channels provide almost constant bit rate and delay, many networks, such as Ethernet, organize data transmission in packets, carrying larger amount of information at less predictable rates. To avoid the bandwidth waste due to the relatively large overhead inherent to packet transmission, we exploit the packet payload to carry longer control sequences. To this aim we adopt a model-based approach to remotely compute a predictive control signal on a suitable time horizon, which leads to effectively reducing the bandwidth required to guarantee stability. Communications are assumed to be ruled by a rather general protocol model, which encompasses many protocols used in practice. As a distinct improvement over the state of the art, our result is shown to be robust with respect to sector-bounded uncertainties in the plant model. Namely, an explicit bound on the combined effects of MATI and MAD is provided as a function of the basin of attraction and the model accuracy.

Robust regression generates more reliable estimates by detecting and downweighting outliers.