The COP9 SIGNALOSOME is required for postembryonic meristem maintenance in Arabidopsis thaliana

Cullin-RING E3 ligases (CRLs) regulate different aspects of plant development, and are activated by modification of their cullin subunit with the ubiquitin-like protein NEDD8 (NEural precursor cell expressed Developmentally Down-regulated 8) (neddylation) and deactivated by NEDD8 removal (deneddylation). The CONSTITUTIVELY PHOTOMORPHOGENIC9 (COP9) signalosome (CSN) acts as a molecular switch of CRLs activity by reverting their neddylation status, but its contribution to embryonic and early seedling development remains poorly characterized. Here, we analyzed the phenotypic defects of csn mutants and monitored the cullin deneddylation/neddylation ratio during embryonic and early seedling development. We show that while csn mutants can complete embryogenesis (albeit at a slower pace than wild type) and are able to germinate (albeit at a reduced rate), they progressively loose meristem activity upon germination, until they become unable to sustain growth. We also show that the majority of cullin proteins is progressively neddylated during the late stages of seed maturation and becomes deneddylated upon seed germination. This developmentally regulated shift in the cullin neddylation status is absent in csn mutants. We conclude that the CSN and its cullin deneddylation activity are required to sustain postembryonic meristem function in Arabidopsis

Pre-impact fall detection: optimal sensor positioning based on a machine learning paradigm

The aim of this study was to identify the best subset of body segments that provides for a rapid and reliable detection of the transition from steady walking to a slipping event. Fifteen healthy young subjects managed unexpected perturbations during walking. Whole-body 3D kinematics was recorded and a machine learning algorithm was developed to detect perturbation events. In particular, the linear acceleration of all the body segments was parsed by Independent Component Analysis and a Neural Network was used to classify walking from unexpected perturbations. The Mean Detection Time (MDT) was 3516123 ms with an Accuracy of 95.4%. The procedure was repeated with data related to different subsets of all body segments whose variability appeared strongly influenced by the perturbation-induced dynamic modifications. Accordingly, feet and hands accounted for most data information and the performance of the algorithm were slightly reduced using their combination. Results support the hypothesis that, in the framework of the proposed approach, the information conveyed by all the body segments is redundant to achieve effective fall detection, and suitable performance can be obtained by simply observing the kinematics of upper and lower distal extremities. Future studies are required to assess the extent to which such results can be reproduced in older adults and in different experimental conditions

A case study of arrival and departure managers cooperation for reducing airborne holding times at destination airports

Congestion of flights arriving at terminal areas invariably leads to aircraft having to extend their flying time, which often results in the need to orbit at a holding point as aircraft are sequenced to land. This extended flying time can be significantly reduced by the implementation of the delay-on-ground concept, where aircraft flying short sectors are delayed in their departure from the respective airport, thus reducing the amount of congestion at the destination point. This paper analysis the impact, in terms of reduced flying time, fuel burn and carbon emissions, that can be achieved at Oslo-Gardemoen airport if the present flights that have a flying time of 1 hour or less are delayed on the ground at their departure point. The impact such a concept would have if traffic densities of 15% and 30% above current levels were to be experienced is also considered

Airborne laser systems for atmospheric sounding in the near infrared

This paper presents new techniques for atmospheric sounding using Near Infrared (NIR) laser sources, direct detection electro-optics and passive infrared imaging systems. These techniques allow a direct determination of atmospheric extinction and, through the adoption of suitable inversion algorithms, the indirect measurement of some important natural and man-made atmospheric constituents, including Carbon Dioxide (CO2). The proposed techniques are suitable for remote sensing missions performed by using aircraft, satellites, Unmanned Aerial Vehicles (UAV), parachute/gliding vehicles, Roving Surface Vehicles (RSV), or Permanent Surface Installations (PSI). The various techniques proposed offer relative advantages in different scenarios. All are based on measurements of the laser energy/power incident on target surfaces of known geometric and reflective characteristics, by means of infrared detectors and/or infrared cameras calibrated for radiance. (cont.

Low-cost navigation and guidance systems for unmanned aerial vehicles - part 1: Vision-based and integrated sensors

In this paper we present a new low-cost navigation system designed for small size Unmanned Aerial Vehicles (UAVs) based on Vision-Based Navigation (VBN) and other avionics sensors. The main objective of our research was to design a compact, light and relatively inexpensive system capable of providing the Required Navigation Performance (RNP) in all phases of flight of a small UAV, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN were compared and the Appearance-Based Approach (ABA) was selected for implementation. Feature extraction and optical flow techniques were employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway and body rates. Additionally, we addressed the possible synergies between VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, as well as the aiding from Aircraft Dynamics Models (ADMs)

21-cm synthesis observations of VIRGOHI 21 - a possible dark galaxy in the Virgo Cluster

Many observations indicate that dark matter dominates the extra-galactic Universe, yet no totally dark structure of galactic proportions has ever been convincingly identified. Previously we have suggested that VIRGOHI 21, a 21-cm source we found in the Virgo Cluster using Jodrell Bank, was a possible dark galaxy because of its broad line-width (~200 km/s) unaccompanied by any visible gravitational source to account for it. We have now imaged VIRGOHI 21 in the neutral-hydrogen line and find what could be a dark, edge-on, spinning disk with the mass and diameter of a typical spiral galaxy. Moreover, VIRGOHI 21 has unquestionably been involved in an interaction with NGC 4254, a luminous spiral with an odd one-armed morphology, but lacking the massive interactor normally linked with such a feature. Numerical models of NGC 4254 call for a close interaction ~10^8 years ago with a perturber of ~10^11 solar masses. This we take as additional evidence for the massive nature of VIRGOHI 21 as there does not appear to be any other viable candidate. We have also used the Hubble Space Telescope to search for stars associated with the HI and find none down to an I band surface brightness limit of 31.1 +/- 0.2 mag/sq. arcsec.Comment: 8 pages, accepted to ApJ, uses emulateapj.cls. Mpeg animation (Fig. 2) available at ftp://ftp.naic.edu/pub/publications/minchin/video2.mp

MERAV: a tool for comparing gene expression across human tissues and cell types

The oncogenic transformation of normal cells into malignant, rapidly proliferating cells requires major alterations in cell physiology. For example, the transformed cells remodel their metabolic processes to supply the additional demand for cellular building blocks. We have recently demonstrated essential metabolic processes in tumor progression through the development of a methodological analysis of gene expression. Here, we present the Metabolic gEne RApid Visualizer (MERAV, http://merav.wi.mit.edu), a web-based tool that can query a database comprising ∼4300 microarrays, representing human gene expression in normal tissues, cancer cell lines and primary tumors. MERAV has been designed as a powerful tool for whole genome analysis which offers multiple advantages: one can search many genes in parallel; compare gene expression among different tissue types as well as between normal and cancer cells; download raw data; and generate heatmaps; and finally, use its internal statistical tool. Most importantly, MERAV has been designed as a unique tool for analyzing metabolic processes as it includes matrixes specifically focused on metabolic genes and is linked to the Kyoto Encyclopedia of Genes and Genomes pathway search.United States. National Institutes of Health (CA103866)United States. National Institutes of Health (AI47389)Life Sciences Research FoundationMassachusetts Institute of Technology. Ludwig Center for Molecular OncologyHoward Hughes Medical Institut

The far-infrared view of M87 as seen by the Herschel Space Observatory

The origin of the far-infrared emission from the nearby radio galaxy M87 remains a matter of debate. Some studies find evidence of a far-infrared excess due to thermal dust emission, whereas others propose that the far-infrared emission can be explained by synchrotron emission without the need for an additional dust emission component. We observed M87 with PACS and SPIRE as part of the Herschel Virgo Cluster Survey (HeViCS). We compare the new Herschel data with a synchrotron model based on infrared, submm and radio data to investigate the origin of the far-infrared emission. We find that both the integrated SED and the Herschel surface brightness maps are adequately explained by synchrotron emission. At odds with previous claims, we find no evidence of a diffuse dust component in M87.Comment: 4 pages, 2 figures, proceedings IAU Symposium 275 (Jets at all scales