Use of SLAM and PVRL4 and Identification of Pro-HB-EGF as Cell Entry Receptors for Wild Type Phocine Distemper Virus

Signalling lymphocyte activation molecule (SLAM) has been identified as an immune cell receptor for the morbilliviruses, measles (MV), canine distemper (CDV), rinderpest and peste des petits ruminants (PPRV) viruses, while CD46 is a receptor for vaccine strains of MV. More recently poliovirus like receptor 4 (PVRL4), also known as nectin 4, has been identified as a receptor for MV, CDV and PPRV on the basolateral surface of polarised epithelial cells. PVRL4 is also up-regulated by MV in human brain endothelial cells. Utilisation of PVRL4 as a receptor by phocine distemper virus (PDV) remains to be demonstrated as well as confirmation of use of SLAM. We have observed that unlike wild type (wt) MV or wtCDV, wtPDV strains replicate in African green monkey kidney Vero cells without prior adaptation, suggesting the use of a further receptor. We therefore examined candidate molecules, glycosaminoglycans (GAG) and the tetraspan proteins, integrin β and the membrane bound form of heparin binding epithelial growth factor (proHB-EGF),for receptor usage by wtPDV in Vero cells. We show that wtPDV replicates in Chinese hamster ovary (CHO) cells expressing SLAM and PVRL4. Similar wtPDV titres are produced in Vero and VeroSLAM cells but more limited fusion occurs in the latter. Infection of Vero cells was not inhibited by anti-CD46 antibody. Removal/disruption of GAG decreased fusion but not the titre of virus. Treatment with anti-integrin β antibody increased rather than decreased infection of Vero cells by wtPDV. However, infection was inhibited by antibody to HB-EGF and the virus replicated in CHO-proHB-EGF cells, indicating use of this molecule as a receptor. Common use of SLAM and PVRL4 by morbilliviruses increases the possibility of cross-species infection. Lack of a requirement for wtPDV adaptation to Vero cells raises the possibility of usage of proHB-EGF as a receptor in vivo but requires further investigation.

The Vertical Distribution and Evolution of Slam Pressure on an Oscillating Wave Surge Converter

The accurate definition of the extreme wave loads which act on offshore structures represents a significant challenge for design engineers and even with decades of empirical data to base designs upon there are still failures attributed to wave loading. The environmental conditions which cause these loads are infrequent and highly non-linear which means that they are not well understood or simple to describe. If the structure is large enough to affect the incident wave significantly further non-linear effects can influence the loading. Moreover if the structure is floating and excited by the wave field then its responses, which are also likely to be highly non-linear, must be included in the analysis. This makes the description of the loading on such a structure difficult to determine and the design codes will often suggest employing various tools including small scale experiments, numerical and analytical methods, as well as empirical data if available.
Wave Energy Converters (WECs) are a new class of offshore structure which pose new design challenges, lacking the design codes and empirical data found in other industries. These machines are located in highly exposed and energetic sites, designed to be excited by the waves and will be expected to withstand extreme conditions over their 25 year design life. One such WEC is being developed by Aquamarine Power Ltd and is called Oyster. Oyster is a buoyant flap which is hinged close to the seabed, in water depths of 10 to 15m, piercing the water surface. The flap is driven back and forth by the action of the waves and this mechanical energy is then converted to electricity.
It has been identified in previous experiments that Oyster is not only subject to wave impacts but it occasionally slams into the water surface with high angular velocity. This slamming effect has been identified as an extreme load case and work is ongoing to describe it in terms of the pressure exerted on the outer skin and the transfer of this short duration impulsive load through various parts of the structure.
This paper describes a series of 40th scale experiments undertaken to investigate the pressure on the face of the flap during the slamming event. A vertical array of pressure sensors are used to measure the pressure exerted on the flap. Characteristics of the slam pressure such as the rise time, magnitude, spatial distribution and temporal evolution are revealed. Similarities are drawn between this slamming phenomenon and the classical water entry problems, such as ship hull slamming. With this similitude identified, common analytical tools are used to predict the slam pressure which is compared to that measured in the experiment.

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

Local map update for large scale SLAM

A technique for simultaneous localisation and mapping (SLAM) for large scale scenarios is presented. This solution is based on the use of independent submaps of a limited size to map large areas. In addition, a global stochastic map, containing the links between adjacent submaps, is built. The information in both levels is corrected every time a loop is closed: local maps are updated with the information from overlapping maps, and the global stochastic map is optimised by means of constrained minimisation

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

SLAM using an Imaging Sonar for Partially Structured Underwater Environments

In this paper we describe a system for underwater navigation with AUVs in partially structured environments, such as dams, ports or marine platforms. An imaging sonar is used to obtain information about the location of planar structures present in such environments. This information is incorporated into a feature-based SLAM algorithm in a two step process: (I) the full 360deg sonar scan is undistorted (to compensate for vehicle motion), thresholded and segmented to determine which measurements correspond to planar environment features and which should be ignored; and (2) SLAM proceeds once the data association is obtained: both the vehicle motion and the measurements whose correct association has been previously determined are incorporated in the SLAM algorithm. This two step delayed SLAM process allows to robustly determine the feature and vehicle locations in the presence of large amounts of spurious or unrelated measurements that might correspond to boats, rocks, etc. Preliminary experiments show the viability of the proposed approach

Underwater SLAM in a marina environment

This paper describes a navigation system for autonomous underwater vehicles (AUVs) in partially structured environments, such as dams, harbors, marinas or marine platforms. A mechanical scanning imaging sonar is used to obtain information about the location of planar structures present in such environments. A modified version of the Hough transform has been developed to extract line features, together with their uncertainty, from the continuous sonar dataflow. The information obtained is incorporated into a feature-based SLAM algorithm running an Extended Kalman Filter (EKF). Simultaneously, the AUV's position estimate is provided to the feature extraction algorithm to correct the distortions that the vehicle motion produces in the acoustic images. Experiments carried out in a marina located in the Costa Brava (Spain) with the Ictineu AUV show the viability of the proposed approach

Visual SLAM for 3D large-scale seabed acquisition employing underwater vehicles

This paper presents a novel technique to align partial 3D reconstructions of the seabed acquired by a stereo camera mounted on an autonomous underwater vehicle. Vehicle localization and seabed mapping is performed simultaneously by means of an Extended Kalman Filter. Passive landmarks are detected on the images and characterized considering 2D and 3D features. Landmarks are re-observed while the robot is navigating and data association becomes easier but robust. Once the survey is completed, vehicle trajectory is smoothed by a Rauch-Tung-Striebel filter obtaining an even better alignment of the 3D views and yet a large-scale acquisition of the seabed

Visual SLAM for underwater vehicles using video velocity log and natural landmarks

A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system

Le Savoir-être pour la formation initiale dans le contexte du CECRL: la prise en compte du handicap par le biais du slam

A la Conférence de Prague (2001), les Ministres ont tenu à encourager le développement des programmes qui valorisent les compétences académiques et la professionnalisation durable, souhaitant que les établissements d'enseignement supérieur jouent un rôle constructif dans ce domaine. Leur objectif instaurer un espace européen de l'enseignement supérieur en 2010. Il est attendu une réforme méthodologique mais aussi une nouvelle conception des programmes qui jusqu'à présent s'appuyaient sur les objectifs, c'est-à-dire, sur les résultats qu'on se proposait atteindre par l'intermédiaire de l'action de l'enseignant. Dorénavant, ils reposeront sur les compétences et entendent se placer du point de vue de l'action de l'apprenant. C'est aussi la perspective que privilégie le CECRL dans le domaine de l'apprentissage des langues

Underwater slam for estructured environments using and imaging sonar

Aquesta tesi tracta sobre el problema de la navegació per a vehicles submarins autònoms que operen en entorns artificials estructurats com ara ports, canals, plataformes marines i altres escenaris similars. A partir d'una estimació precisa de la posició en aquests entorns, les capacitats dels vehicles submarins s'incrementen notablement i s'obre una porta al seu funcionament autònom. El manteniment, inspecció i vigilància d'instal lacions marines són alguns exemples de possibles aplicacions. Les principals contribucions d'aquesta tesi consisteixen per una banda en el desenvolupament de diferents sistemes de localització per a aquelles situacions on es disposa d'un mapa previ de l'entorn i per l'altra en el desenvolupament d'una nova solució al problema de la Localització i Construcció Simultània de Mapes (SLAM en les seves sigles en anglès), la finalitat del qual és fer que un vehicle autònom creï un mapa de l'entorn desconegut que el rodeja i, al mateix temps, utilitzi aquest mapa per a determinar la seva pròpia posició. S'ha escollit un sonar d'imatges d'escaneig mecànic com a sensor principal per a aquest treball tant pel seu relatiu baix cost com per la seva capacitat per produir una representació detallada de l'entorn. Per altra banda, les particularitats de la seva operació i, especialment, la baixa freqúència a la que es produeixen les mesures, constitueixen els principals inconvenients que s'han hagut d'abordar en les estratègies de localització proposades. Les solucions adoptades per aquests problemes constitueixen una altra contribució d'aquesta tesi. El desenvolupament de vehicles autònoms i el seu ús com a plataformes experimentals és un altre aspecte important d'aquest treball. Experiments portats a terme tant en el laboratori com en escenaris reals d'aplicació han proporcionat les dades necessàries per a provar i avaluar els diferents sistemes de localització proposats.