Embodied and Evolved Dynamical Neural Networks for Robust Planetary Navigation

The N.E.Me.Sys project has the aim of controlling a legged rover for planetary exploration using dynamical recurrent neural networks and evolutionary algorithms. This paper describes the realization of the navigation module of such a rover using a 2D chemiotaxis scenario, in which the agent must reach the source of a chemical signal. The analyses carried out in this work show the high degree of robustness of the neuro-controller versus uncertainties, noise, errors, or unpredicted situations. Moreover an analysis of the topology of the network has been realized in order to find the reasons of the good performances of the proposed methodology: it is possible to prove that different individuals share the same topology, i.e. the evolutionary process looks for the same feedback paths more than for the optimal set of parameters

Modelization, Failures Identification and High-Level Recovery in Fast Varying Non-Linear Dynamical Systems for Space Autonomy

This paper shows the realization and validation of a detection, identification and recovery module for hardware failures on ESA GOCE satellite, merging two independently developed modules. The work is currently focused on its attitude control subsystem, following a previous work on the power subsystem. This application is more challenging than the former because of two reasons. Control system, sensors and actuators are highly interdependent; hence to correctly understand which is the faulty device is definitely a hard task. Secondly, the dynamical behaviour of some components is related to very high frequencies, asking for a finer attention to be paid in the neuro-fuzzy model identification phase

Clickable 2,2-bis(hydroxymethyl)propionic acid-derived AB2 monomers: Hyperbranched polyesters through the CuAAC cycloaddition (click) reaction

AbstractWe present the synthesis and characterization of two aliphatic AB2 monomers derived from the readily available 2,2‐bis(hydroxymethyl)propionic acid and containing one alkyne group and two azide functionalities. The distance between the polymerizable groups differs in the two monomers by the insertion of an additional carbon atom in the aliphatic structure that addresses the steric demand during polymerization. The synthetic procedure for the monomers is relatively simple and scalable, and the monomers are able to polymerize through the Copper(I)‐catalyzed Azide‐Alkyne Cycloaddition (CuAAC reaction). The polymerization affords hyperbranched polymers in good yields and molecular weights and moderate degrees of branching. Copyright © 2021 John Wiley & Sons, Ltd

Endorectal Ultrasound and Magnetic Resonance Imaging for Rectal Cancer Staging: A Modern Multimodality Approach

Preoperative staging represents a crucial point for the management, type of surgery, and candidacy for neoadjuvant therapy in patient with rectal cancer. The most recent clinical guidelines in oncology recommend an accurate preoperative evaluation in order to address early and advanced tumors to different therapeutic options. In particular, potential pitfalls may occur in the assessment of T3 tumors, which represents the most common stage at diagnosis. The depth of tumor invasion is known to be an important prognostic factor in rectal carcinoma; as a consequence, the T3 imaging classification has a substantial importance for treatment strategy and patient survival. However, the differentiation between tumor invasion of perirectal fat and mesorectal desmoplastic reactions remains a main goal for radiologists. Magnetic resonance imaging (MRI) is actually considered as the best imaging modality for rectal cancer staging. Although the endorectal ultrasound (ERUS) is the preferred staging method for early tumors, it could also be useful in identifying perirectal fat invasion. Moreover, the addiction of diffusion weighted imaging (DWI) improves the diagnostic performance of MRI in rectal cancer staging by adding functional information about rectal tumor and adjacent mesorectal tissues. This study investigated the diagnostic performance of conventional MRI alone, in combination with the DWI technique and ERUS in order to assess the best diagnostic imaging combination for rectal cancer staging