The ARIEL Instrument Control Unit design for the M4 Mission Selection Review of the ESA's Cosmic Vision Program

The Atmospheric Remote-sensing Infrared Exoplanet Large-survey mission (ARIEL) is one of the three present candidates for the ESA M4 (the fourth medium mission) launch opportunity. The proposed Payload will perform a large unbiased spectroscopic survey from space concerning the nature of exoplanets atmospheres and their interiors to determine the key factors affecting the formation and evolution of planetary systems. ARIEL will observe a large number (>500) of warm and hot transiting gas giants, Neptunes and super-Earths around a wide range of host star types, targeting planets hotter than 600 K to take advantage of their well-mixed atmospheres. It will exploit primary and secondary transits spectroscopy in the 1.2-8 um spectral range and broad-band photometry in the optical and Near IR (NIR). The main instrument of the ARIEL Payload is the IR Spectrometer (AIRS) providing low-resolution spectroscopy in two IR channels: Channel 0 (CH0) for the 1.95-3.90 um band and Channel 1 (CH1) for the 3.90-7.80 um range. It is located at the intermediate focal plane of the telescope and common optical system and it hosts two IR sensors and two cold front-end electronics (CFEE) for detectors readout, a well defined process calibrated for the selected target brightness and driven by the Payload's Instrument Control Unit (ICU).Comment: Experimental Astronomy, Special Issue on ARIEL, (2017

The Atmospheric Remote-sensing Infrared Exoplanets Large-survey (ARIEL) payload electronic subsystems

The ARIEL mission has been proposed to ESA by an European Consortium as the first space mission to extensively perform remote sensing on the atmospheres of a well defined set of warm and hot transiting gas giant exoplanets, whose temperature range between ~600 K and 3000 K. ARIEL will observe a large number (~500) of warm and hot transiting gas giants, Neptunes and super-Earths around a range of host star types using transit spectroscopy in the ~2-8 μm spectral range and broad-band photometry in the NIR and optical. ARIEL will target planets hotter than 600 K to take advantage of their well-mixed atmospheres, which should show minimal condensation and sequestration of high-Z materials and thus reveal their bulk and elemental composition. One of the major motivations for exoplanet characterisation is to understand the probability of occurrence of habitable worlds, i.e. suitable for surface liquid water. While ARIEL will not study habitable planets, its major contribution to this topic will results from its capability to detect the presence of atmospheres on many terrestrial planets outside the habitable zone and, in many cases, characterise them. This represents a fundamental breakthrough in understanding the physical and chemical processes of a large sample of exoplanets atmospheres as well as their bulk properties and to probe in-space technology. The ARIEL infrared spectrometer (AIRS) provides data on the atmospheric composition; these data are acquired and processed by an On-Board Data Handling (OBDH) system including the Cold Front End Electronics (CFEE) and the Instrument Control Unit (ICU). The Telescope Control Unit (TCU) is also included inside the ICU. The latter is directly connected to the Control and Data Management Unit (CDMU) on board the Service Module (SVM). The general hardware architecture and the application software of the ICU are described. The Fine Guidance Sensor (FGS) electronics and the Cooler Control Electronics are also presented

Design of the instrument and telescope control units integrated subsystem of the ESA-ARIEL payload

The Atmospheric Remote-sensing Infrared Exoplanets Large-survey (ARIEL)1 Mission has been recently selected by ESA as the fourth medium-class Mission (M4) in the framework of the Cosmic Vision Program. The goal of ARIEL is to investigate, thanks to VIS photometry and IR spectroscopy, the atmospheres of several hundreds of planets orbiting nearby stars in order to address the fundamental questions on how planetary systems form and evolve.2 During its four-years mission, ARIEL will observe several hundreds of exoplanets ranging from Jupiter- and Neptune-size down to super-Earth and Earth-size with its 1 meter-class telescope.3 The analysis of spectra and photometric data will allow to extract the chemical fingerprints of gases and condensates in the planets atmospheres, including the elemental composition for the most favorable targets. It will also enable the study of thermal and scattering properties of the atmosphere as the planet orbits around its parent star

Gene therapy for carcinoma of the breast: Pro-apoptotic gene therapy

The dysregulation of apoptosis contributes in a variety of ways to the malignant phenotype. It is increasingly recognized that the alteration of pro-apoptotic and anti-apoptotic molecules determines not only escape from mechanisms that control cell cycle and DNA damage, but also endows the cancer cells with the capacity to survive in the presence of a metabolically adverse milieu, to resist the attack of the immune system, to locally invade and survive despite a lack of tissue anchorage, and to evade the otherwise lethal insults induced by drugs and radiotherapy. A multitude of apoptosis mediators has been identified in the past decade, and the roles of several of them in breast cancer have been delineated by studying the clinical correlates of pathologically documented abnormalities. Using this information, attempts are being made to correct the fundamental anomalies at the genetic level. Fundamental to this end are the design of more efficient and selective gene transfer systems, and the employment of complex interventions that are tailored to breast cancer and that are aimed concomitantly towards different components of the redundant regulatory pathways. The combination of such genetic modifications is most likely to be effective when combined with conventional treatments, thus robustly activating several pro-apoptotic pathways

Personalised automated assessments

Copyright © 2016, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved. Consider a person who needs to assess a large amount of information. For instance, think of a teacher of a massive open online course with thousands of enrolled students, or a senior program committee member in a large conference who needs to decide what are the final marks of reviewed papers, or a buyer in an e-commerce scenario who needs to build up her opinion about products. When assessing a large number of objects, sometimes it is simply unfeasible to evaluate them all and very often one needs to rely on the opinions of others. In this paper, we provide a model that uses peer assessments (assessments made by others) in an online community to approximate the assessments that a particular member of the community would generate given the occasion to do so (e.g. the tutor, the SPC member or the buyer-we refer to this person as the leader). Furthermore, we provide a measure of the uncertainty of the computed assessments and a ranking of the objects that should be assessed next. The model, although inspired by human societies is thought to be used in the organisation of agent communities