Search

International audience; Vespa velutina Lepieltier, 1836 (Hymenoptera: Vespidae) is an invasive predator of honeybees accidentally introduced into Europe from eastern Asia. It was observed for the first time in southwest France in 2004 and in the following years it rapidly spread almost all over the country. In 2013 it was officially reported in Italy, in the region Liguria, near the border with France. In three years it invaded the whole province of Imperia and it was occasionally reported also in the South Western of Piedmont and in one locality in South Eastern Piedmont. The VELUTINA project was funded in 2014 by the Italian Ministry of Agriculture, with the aim of finding effective control methods against the predator. It includes both research and surveillance: adult and nest monitoring; development of methods for nest detection; development of protocols for nest destruction; studies on wasp chemical communication. Adult monitoring was performed in 5 Italian regions – the two where the hornet is already present and the three bordering ones – with the cooperation of Universities, research centres and beekeeping associations. Reports of V. velutina nests were collected from 2014 to 2016 thanks to the activity of the beekeeping association Apiliguria. Between 2014 and 2015 the presence of V. velutina was confirmed in the provinces were it was already present, with a small enlargement of the distribution area, both along the coast and the valleys, with no trespassing to other regions. Only recently, in November 2016, the presence of V. velutina was reported and confirmed by our institution in a locality of Veneto region, very near to the border with Lombardy and Emilia Romagna. At present, nest destruction represents the most effective method to limit the diffusion of the hornet, but it shows limitations and inconveniences. Nests are often difficult to locate and reach, their destruction is costly and risky for the staff and it is not regulated by official approved protocols. Within VELUTINA project some progresses have been made towards the official recognition of the method, thanks to the cooperation with national and regional institutions. After the end of Velutina project, the researchers of the project and the beekeeping associations of the invaded areas joined together in the scientific net Stopvelutina (www.stopvelutina.it), whose aim is to collect information and find new solutions to limit the spread of V. velutina. Beside the continuation of previous researches, a patent pending method was tested in summer 2016 to fight V. velutina adults in front of the apiaries in Liguria. From the first preliminary results the method resulted highly effective and it seems suitable to contrast the predator also in new invaded areas.

Vespa velutina Lepieltier, 1836 (Hymenoptera: Vespidae) is an invasive predator of honeybees accidentally introduced into Europe from eastern Asia. It was observed for the first time in southwest France in 2004 and in the following years it rapidly spread almost all over the country. In 2013 it was officially reported in Italy, in the region Liguria, near the border with France. In three years it invaded the whole province of Imperia and it was occasionally reported also in the South Western of Piedmont and in one locality in South Eastern Piedmont. The VELUTINA project was funded in 2014 by the Italian Ministry of Agriculture, with the aim of finding effective control methods against the predator. It includes both research and surveillance: adult and nest monitoring; development of methods for nest detection; development of protocols for nest destruction; studies on wasp chemical communication. Adult monitoring was performed in 5 Italian regions – the two where the hornet is already present and the three bordering ones – with the cooperation of Universities, research centres and beekeeping associations. Reports of V. velutina nests were collected from 2014 to 2016 thanks to the activity of the beekeeping association Apiliguria. Between 2014 and 2015 the presence of V. velutina was confirmed in the provinces were it was already present, with a small enlargement of the distribution area, both along the coast and the valleys, with no trespassing to other regions. Only recently, in November 2016, the presence of V. velutina was reported and confirmed by our institution in a locality of Veneto region, very near to the border with Lombardy and Emilia Romagna. At present, nest destruction represents the most effective method to limit the diffusion of the hornet, but it shows limitations and inconveniences. Nests are often difficult to locate and reach, their destruction is costly and risky for the staff and it is not regulated by official approved protocols. Within VELUTINA project some progresses have been made towards the official recognition of the method, thanks to the cooperation with national and regional institutions. After the end of Velutina project, the researchers of the project and the beekeeping associations of the invaded areas joined together in the scientific net Stopvelutina (www.stopvelutina.it), whose aim is to collect information and find new solutions to limit the spread of V. velutina. Beside the continuation of previous researches, a patent pending method was tested in summer 2016 to fight V. velutina adults in front of the apiaries in Liguria. From the first preliminary results the method resulted highly effective and it seems suitable to contrast the predator also in new invaded areas.

The face reveals the healthy status of an individual, through a combination of physical signs and facial expressions. The project SEMEOTICONS is translating the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, images, and 3D scans of the face. SEMEOTICONS is developing a multisensory platform, in the form of a smart mirror, looking for signs related to cardio-metabolic risk. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. Building the multisensory mirror requires addressing significant scientific and technological challenges, from touch-less data acquisition, to real-time processing and integration of multimodal data.

Thesaurus Project aims at promoting the knowledge of the underwater cultural heritage, ancient and modern, through the application of several typologies of tools: underwater autonomous vehicles, which will be able to explore the sea bottom in teams communicating with each other; a database, which will be useful to store and manage all the information referring to archaeological or historical objects, shipwrecks and sites. This paper aims to explain the logic structure of the database indicating the particular needs of the research, the different typologies of items which have to be managed (archaeological and historical objects; ancient, medieval or modern shipwrecks; underwater sites; written or figurative sources, etc.), the relation with other similar databases and projects. The main task of this part of Thesaurus is to plan and organize an IT system, which will allow archaeologists to describe information in detail, in order to make an efficient managing and retrieving data system available.

ARROWS is the acronym for ARchaeological RObot systems for the World's Seas1. The project, started in September 2012, is funded by the EU in the framework of the FP7 call ENV-2012, challenge 6.2-6, devoted to "Development of advanced technologies and tools for mapping, diagnosing, excavating, and securing underwater and coastal archaeological sites". The ARROWS consortium comprises expertise from underwater archaeology, underwater engineering, robotics, image processing and recognition from academia and industry. 10 partners from 5 different Countries are involved. The cost of underwater archaeological investigations using a research ship with skilled human operators and/or Remotely Operated Vehicles (ROVs) is high (up to EUR50k per day) and beyond the range of many archaeological research institutions. Reducing the cost of underwater archaeological operations is an important issue to address in advancing the knowledge of our cultural heritage. The challenge faced by ARROWS is to generate and adapt existing technologies in the field of military, security and offshore oil and gas applications, in order to develop user-friendly and low cost Autonomous Underwater Vehicle (AUV) technologies for archaeological investigation in different sea environments. Two different demonstration sites will used, one in the Baltic Sea and one in the Egadi archipelago (Sicily).

One explanation that has been proposed for TSM is a psychophysiological model which builds on previous dream building models. The model depicts two subsystems of the dream builder which include the associative and metaphorical systems of dreaming which connect to both the brain state and the dream experience.

The THESAURUS project (2011-2013) is financed by Regione Toscana (Italy) in the framework of the "FAS" program 2007-2013 under Deliberation CIPE (Italian government) 166/2007. The overall goal of THESAURUS project is to develop multidisciplinary methodologies and technologies to detect, catalogue and document underwater artifacts and wreckage with archaeological and ethno-anthropological value. In particular, specially designed Autonomous Underwater Vehicles (AUVs) will be used to systematically explore the sea floor in a co-operative way, by collecting and analyzing in real time heterogeneous data from acoustic, optical and magnetic sensors with the aim of promptly detecting objects of interest. Data recorded from AUVs missions will also be analyzed and integrated off-line, by building large-scale sea-floor maps and 3D reconstructions for granting virtual access to underwater sites.

The automatic subcellular localisation of proteins in living cells is a critical step in determining their function. The evaluation of fluorescence images constitutes a common method of localising these proteins. For this, additional knowledge about the position of the considered cells within an image is required. In an automated system, it is advantageous to recognise these cells in bright-field microscope images taken in parallel with the regarded fluorescence micrographs. Unfortunately, currently available cell recognition methods are only of limited use within the context of protein localisation, since they frequently require microscopy techniques that enable images of higher contrast (e.g. phase contrast microscopy or additional dyes) or can only be employed with too low magnifications. Therefore, this article introduces a novel approach to the robust automatic recognition of unstained living cells in bright-field microscope images. Here, the focus is on the automatic segmentation of cells.

A research has been carried out finalised to the definition of a methodology useful to detect and track moving targets in video sequences. Algorithms performing this task have been also developed for real time monitoring and surveillance purposes. Due to deformations occurring in the appearance of the target in the videos, a Hierarchical Artificial Neural Network (HANN) has been used to recognize target occlusion or masking, and to increase the normal tracking performance. Preliminary results are presented regarding both identification and tracking of animal moving at night in an open environment, and the surveillance of known scenes for unauthorized access control.