Expanding the clinical and genetic heterogeneity of SPAX5

Mutations in the ATPase family 3-like gene (AFG3L2) have been linked to autosomal-dominant spinocerebellar ataxia type 28 and autosomal recessive spastic ataxia-neuropathy syndrome. Here, we describe the case of a child carrying bi-allelic mutations in AFG3L2 and presenting with ictal paroxysmal episodes associated with neuroimaging suggestive of basal ganglia involvement. Studies in skin fibroblasts showed a significant reduction of AFG3L2 expression. The relatively mild clinical presentation and the benign course, in spite of severe neuroimaging features, distinguish this case from data reported in the literature, and therefore expand the spectrum of neurological and neuroradiological features associated with AFG3L2 mutations

B23 Cartridge Prototype Manufacturing and Integration Report

This document reports on the manufacturing and assembly of the B23 Prototype cartridge to perform cryogenic noise tests @ INAF/IASF-Bologna

U-PHOS Project: Development of a Large Diameter Pulsating Heat Pipe Experiment on board REXUS 22

U-PHOS Project aims to analyse and characterise the behaviour of a large diameter Pulsating Heat Pipe (PHP) on board REXUS 22 sounding rocket. A PHP is a passive thermal control device consisting of a serpentine capillary tube, evacuated, partially filled with a working fluid and finally sealed. In this configuration, the liquid and vapour phases are randomly distributed in the form of liquid slugs and vapour plugs. The heat is efficiently transported by means of the self-sustained oscillatory fluid motion driven by the phase change phenomena. On ground conditions, a small diameter is required in order to obtain a confined slug flow regime. In milli-gravity conditions, buoyancy forces become less intense and the PHP diameter may be increased still maintaining the slug/plug flow configuration typical of the PHP operation. Consequently, the PHP heat power capability may be increased too. U-PHOS aims at proving that a Large Diameter PHP effectively works in milli-g conditions by characterizing its thermal response during a sounding rocket flight. The actual PHP tube is made of aluminum (3 mm inner diameter, filled with FC-72), heated at the evaporator by a compact electrical resistance, cooled at the condenser by a Phase Change Material (PCM) embedded in a metallic foam. The tube wall temperatures are recorded by means of Fibre Bragg Grating (FBG) sensors; the local fluid pressure is acquired by means of a pressure transducer. The present work intends to report the actual status of the project, focusing in particular on the experiment improvements with respect to the previous campaign

The detector control unit of the fine guidance sensor instrument on-board the ARIEL mission: design status

ARIEL is an ESA mission whose scientific goal is to investigate exoplanetary atmospheres. The payload is composed by two instruments: AIRS (ARIEL IR Spectrometer) and FGS (Fine Guidance System). The FGS detection chain is composed by two HgCdTe detectors and by the cold Front End Electronics (SIDECAR), kept at cryogenic temperatures, interfacing with the F-DCU (FGS Detector Control Unit) boards that we will describe thoroughly in this paper. The F-DCU are situated in the warm side of the payload in a box called FCU (FGS Control Unit) and contribute to the FGS VIS/NIR imaging and NIR spectroscopy. The F-DCU performs several tasks: drives the detectors, processes science data and housekeeping telemetries, manages the commands exchange between the FGS/DPU (Data Processing Unit) and the SIDECARs and provides high quality voltages to the detectors. This paper reports the F-DCU status, describing its architecture, the operation and the activities, past and future necessary for its development

The instrument control unit of the ARIEL payload: design evolution following the unit and payload subsystems SRR (system requirements review)

ARIEL (Atmospheric Remote-sensing InfraRed Large-survey) is a medium-class mission of the European Space Agency, part of the Cosmic Vision program, whose launch is foreseen by early 2029. ARIEL aims to study the composition of exoplanet atmospheres, their formation and evolution. The ARIEL’s target will be a sample of about 1000 planets observed with one or more of the following methods: transit, eclipse and phase-curve spectroscopy, at both visible and infrared wavelengths simultaneously. The scientific payload is composed by a reflective telescope having a 1m-class elliptical primary mirror, built in solid Aluminium, and two focal-plane instruments: FGS and AIRS. FGS (Fine Guidance System)1 has the double purpose, as suggested by its name, of performing photometry (0.50-0.55 µm) and low resolution spectrometry over three bands (from 0.8 to 1.95 µm) and, simultaneously, to provide data to the spacecraft AOCS (Attitude and Orbit Control System) with a cadence of 10 Hz and contributing to reach a 0.02 arcsec pointing accuracy for bright targets. AIRS (ARIEL InfraRed Spectrometer) instrument will perform IR spectrometry in two wavelength ranges: between 1.95 and 3.9 µm (with a spectral resolution R > 100) and between 3.9 and 7.8 µm with a spectral resolution R > 30. This paper provides the status of the ICU (Instrument Control Unit), an electronic box whose purpose is to command and supply power to AIRS (as well as acquire science data from its two channels) and to command and control the TCU (Telescope Control Unit)

Front-Ends and Phased Array Feeds for the Sardinia Radio Telescope

We describe the design and performance of the Front- Ends for the 64-m diameter Sardinia Radio Telescope (SRT). An early science program was completed with SRT in August 2016, following a successful technical and scientific commissioning of the telescope and of its instrumentation. We give an overview of the three cryogenic Front-Ends, covering four bands, that were deployed on SRT during the early science program: P-band (305-410 MHz), L-band (1.3-1.8 GHz), high C-band (5.7- 7.7 GHz) and K-band (18-26.5 GHz). In addition, we describe the cryogenic Front-Ends that are currently under development, among which a seven beam for S-band (3.0-4.5 GHz) a mono-feed for Low-Cband (4.2-5.6 GHz), a 19-element for Q-band (33-50 GHz) and a mono-feed for a 3 mm band. Finally, we describe the development status of a demonstrator of a cryogenic C-band Phased Array Feed (PAF) for potential use at the SRT primary focus

Eye Tracking for Proton Clinic Environment - Development of a High Accuracy Eye Tracking Device for Uveal Melanoma Proton Therapy

Uveal Melanoma is the most common intraocular tumor in humans, and one of the most promising treatments available is proton therapy. Proton clinics use specic devices for high energy proton beams forming and delivery, used to damage selectively the tumoral cells, saving the healthy part of the eye and maintaining as much vision as possible. Accurate energy dose delivery is critical for this kind of treatment, and position and rotation of the eye must be measured with high accuracy, in order to determine the position and orientation of the tumor in real-time. This is achievable with eye tracking. Aim of this thesis is the design and validation of a non-invasive eye tracker suitable for proton clinic environment, with accuracy of 0.5° in the worst case. For this purpose a feature-based video-oculography eye tracker with IR active illumination was studied, simulated and implemented. In addition, a custom pupil and glint detection algorithm has been developed, along with a Kalman filter. A mapping procedure and a regression strategy has also been developed and implemented. Results of a single mapping on 5 volunteers show accuracy above the 0.5° bound, with great differences among the different tests. Results are below the required accuracy only if the mapping is repeated several times, and then averaged

Tackling wicked problems: the case of Living Labs

Over the last years, wicked problems have received increasing attention, fostering the search for creative ways of tackling with high uncertainty and complexity. As a consequence, new substantive and procedural policy instruments have been designed and experimented, including behavioral science-based tools and new forms of collaborative or networked policy making. Among these, so called ‘Living labs’ have been spreading in many European countries to address complex problems such as sustainable growth, innovation, digitalization, IoT, aging society, food consumptions, and healthcare, also thanks to the impulse given by the European Commission from the Sixth Framework Program on. Although several case studies and some comparative analyses exist in the literature, the nature of this new policy instrument and its characteristics in relation to more traditional instruments have not yet been properly analyzed and discussed. This paper aims at making a step forward in this direction through an extensive analysis on a medium-N sample of Living labs selected from the European Network of Living Labs (ENOLL). This highly inductive theoretical analysis will serve not only to better understand the intrinsic qualities of this new policy instrument and the peculiar mechanisms it is expected to trigger, but also its potential and its pitfalls in terms of overall capacity of politico-administrative systems to cope with wicked problems

Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting

Over the last few years, convolutional neural networks (CNNs) have proved to reach super-human performance in visual recognition tasks. However, CNNs can easily be fooled by adversarial examples, i.e., maliciously-crafted images that force the networks to predict an incorrect output while being extremely similar to those for which a correct output is predicted. Regular adversarial examples are not robust to input image transformations, which can then be used to detect whether an adversarial example is presented to the network. Nevertheless, it is still possible to generate adversarial examples that are robust to such transformations. This paper extensively explores the detection of adversarial examples via image transformations and proposes a novel methodology, called \textit{defense perturbation}, to detect robust adversarial examples with the same input transformations the adversarial examples are robust to. Such a \textit{defense perturbation} is shown to be an effective counter-measure to robust adversarial examples. Furthermore, multi-network adversarial examples are introduced. This kind of adversarial examples can be used to simultaneously fool multiple networks, which is critical in systems that use network redundancy, such as those based on architectures with majority voting over multiple CNNs. An extensive set of experiments based on state-of-the-art CNNs trained on the Imagenet dataset is finally reported