Proton CT on biological phantoms for x-ray CT calibration in proton treatment planning.

To present and characterize a novel method for x-ray computed tomography (xCT) calibration in proton treatment planning, based on proton CT (pCT) measurements on biological phantoms.A pCT apparatus was used to perform direct measurements of 3D stopping power relative to water (SPR) maps on stabilized, biological phantoms. Two single-energy xCT calibration curves-i.

Quantitative assessment of transmural fibrosis profile in the human atrium: evidence for a three-dimensional arrhythmic substrate by slice-to-slice histology.

Aims: Intramural fibrosis represents a crucial factor in the formation of a three-dimensional (3D) substrate for atrial fibrillation (AF). However, the transmural distribution of fibrosis and its relationship with atrial overload remain largely unknown. The aim of this study is to quantify the transmural profile of atrial fibrosis in patients with different degrees of atrial dilatation and arrhythmic profiles by a high-resolution 3D histology method.

A Particle Filtering Approach for Fault Detection and Isolation of UAV IMU Sensors: Design, Implementation and Sensitivity Analysis.

Sensor fault detection and isolation (SFDI) is a fundamental topic in unmanned aerial vehicle (UAV) development, where attitude estimation plays a key role in flight control systems and its accuracy is crucial for UAV reliability. In commercial drones with low maximum take-off weights, typical redundant architectures, based on triplex, can represent a strong limitation in UAV payload capabilities. This paper proposes an FDI algorithm for low-cost multi-rotor drones equipped with duplex sensor architecture.

Decentralized Mesh-Based Model Predictive Control for Swarms of UAVs.

This paper deals with the design of a decentralized guidance and control strategy for a swarm of unmanned aerial vehicles (UAVs), with the objective of maintaining a given connection topology with assigned mutual distances while flying to a target area. In the absence of obstacles, the assigned topology, based on an extended Delaunay triangulation concept, implements regular and connected formation shapes. In the presence of obstacles, this technique is combined with a model predictive control (MPC) that allows forming independent sub-swarms optimizing the formation spreading to avoid obstacles and collisions between neighboring vehicles.

Scalable Distributed State Estimation in UTM Context.

This article proposes a novel approach to the Distributed State Estimation (DSE) problem for a set of co-operating UAVs equipped with heterogeneous on board sensors capable of exploiting certain characteristics typical of the UAS Traffic Management (UTM) context, such as high traffic density and the presence of limited range, Vehicle-to-Vehicle communication devices. The proposed algorithm is based on a scalable decentralized Kalman Filter derived from the Internodal Transformation Theory enhanced on the basis of the Consensus Theory. The general benefit of the proposed algorithm consists of, on the one hand, reducing the estimation problem to smaller local sub-problems, through a self-organization process of the local estimating nodes in response to the time varying communication topology; and on the other hand, of exploiting measures carried out nearby in order to improve the accuracy of the local estimates.