Has Xylella fastidiosa "chosen" olive trees to establish in the Mediterranean basin?

<p>Severe decline of olive trees was observed in the Lecce province, Apulia (Italy), and received the name ‘complesso del disseccamento rapido dell’olivo’ (olive rapid decline complex). Affected plants showed leaf scorch symptoms and dieback of twigs, branches and even of the whole plant. Similar symptoms, unusual for the area, have also been observed in other Apulian localities (Cerignola, Foggia, Canosa di Puglia, and Andria). Three fungal species were associated with the symptoms: Phaeoacremonium aleophilum, Neofusicoccum parvum, and Pleurostomophora richardsiae. The latter is the first report of this fungal species infecting olives. In the Lecce province, the bacterium Xylella fastidiosa also was detected from affected olive trees. Xylella fastidiosa is a quarantine agent in Europe that had been previously reported in the Mediterranean region, but did not spread probably because of the lack of a vector. Present findings suggest that this fundamental condition has now been met.</p

A domain-independent framework for building conversational recommender systems

Conversational Recommender Systems (CoRSs) implement a paradigm where users can interact with the system for defining their preferences and discovering items that best fit their needs. A CoRS can be straightforwardly implemented as a chatbot. Chatbots are becoming more and more popular for several applications like customer care, health care, medical diagnoses. In the most complex form, the implementation of a chatbot is a challenging task since it requires knowledge about natural language processing, human-computer interaction, and so on. In this paper, we propose a general framework for making easy the generation of conversational recommender systems. The framework, based on a content-based recommendation algorithm, is independent from the domain. Indeed, it allows to build a conversational recommender system with different interaction modes (natural language, buttons, hybrid) for any domain. The framework has been evaluated on two state-of-the-art datasets with the aim of identifying the components that mainly influence the final recommendation accuracy

HPLC-HRMS Global Metabolomics Approach for the Diagnosis of “Olive Quick Decline Syndrome” Markers in Olive Trees Leaves

Olive quick decline syndrome (OQDS) is a multifactorial disease affecting olive plants. The onset of this economically devastating disease has been associated with a Gram-negative plant pathogen called Xylella fastidiosa (Xf). Liquid chromatography separation coupled to high-resolution mass spectrometry detection is one the most widely applied technologies in metabolomics, as it provides a blend of rapid, sensitive, and selective qualitative and quantitative analyses with the ability to identify metabolites. The purpose of this work is the development of a global metabolomics mass spectrometry assay able to identify OQDS molecular markers that could discriminate between healthy (HP) and infected (OP) olive tree leaves. Results obtained via multivariate analysis through an HPLC-ESI HRMS platform (LTQ-Orbitrap from Thermo Scientific) show a clear separation between HP and OP samples. Among the differentially expressed metabolites, 18 different organic compounds highly expressed in the OP group were annotated; results obtained by this metabolomic approach could be used as a fast and reliable method for the biochemical characterization of OQDS and to develop targeted MS approaches for OQDS detection by foliage analysis

A personalized and context-aware news offer for mobile devices

For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer

All-ceramic prosthetic rehabilitation of the upper incisors after removal of a periapical lesion from the lateral incisors: palatal approach

The indication of Osseointegrated implants to restore edentulous gaps or replace hopeless teeth could be assumed as a routine dental treatment; instead, if possible natural teeth should be preferred for the support of fixed prostheses. A continuous pervasive pain was referred by a 49 year-old female patient at the palatal aspect of the anterior maxillary area. Soft tissue swelling at the palatal aspect was present during the clinical intraoral examination. An extensive radiolucent area apically to the area from teeth 21 to 23 was showed by means of the X-ray examination. That teeth supported single crown fixed prostheses. A surgical entry was performed for the lesion treatment. The fixed dental prostheses were removed and root canal therapies were performed on teeth 13 and 23. After that, muco-gingival surgery was performed in order to expose the tooth root. A provisional fixed restoration on the four upper incisors was made. After the lesion resolution an all-ceramic definitive fixed prosthesis was delivered. No adverse events or prosthetic complications were detected during the two years of follow-up after prostheses cementation

Galileo, the European GNSS program, and LAGEOS

With the ASI-INFN project “ETRUSCO-2 (Extra Terrestrial Ranging to Unified Satellite COnstellations-2)” we have the opportunity to continue and enhance the work already done with the former ETRUSCO INFN experiment. With ETRUSCO (2005-2010) the SCF LAB (Satellite/lunar laser ranging Characterization Facility LABoratory) team developed a new industry-standard test for laser retroreflectors characterization (the SCF-Test). This test is an integrated and concurrent thermal and optical measurement in accurately laboratory-simulated space environment. In the same period we had the opportunity to test several flight models of retroreflectors from NASA, ESA and ASI. Doing this we examined the detailed thermal behavior and the optical performance of LAGEOS (Laser GEOdynamics Satellites) cube corner retroreflectors and many others being used on the Global Navigation Satellite System (GNSS) constellations currently in orbit, mainly GPS, GLONASS and GIOVE-A/GIOVE-B (Galileo In Orbit Validation Element) satellites, which deploy old-generation aluminium back-coated reflectors; we also SCFTested for ESA prototype new-generation uncoated reflectors for the Galileo IOV (In-Orbit Validation) satellites, which is the most important result presented here. ETRUSCO-2 inherits all this work and a new lab with doubled instrumentation (cryostat, sun simulator, optical bench) inside a new, dedicated 85m2 class 10000 (or better) clean room. This new project aims at a new revision of the SCF-Test expressly conceived to dynamically simulate the actual GNSS typical orbital environment, a new, reliable Key Performance Indicator for the future GNSS retroreflectors payload. Following up on this and using LAGEOS as a reference standard target in terms of optical performances, the SCF LAB research team led by S. Dell’Agnello is designing, building and testing a new generation of GNSS retroreflectors array (GRA) for the new European GNSS constellation Galileo

Multi-dimension Tensor Factorization Collaborative Filtering Recommendation for Academic Profiles

The choice of academic itineraries and/or optional subjects to attend is not usually an easy decision since, in most cases, students lack the information, maturity, and knowledge required to make right decisions. This paper evaluates the support of Collaborative Systems for helping and guiding students in this decision-making process, considering the behavior and impact of these systems on the use of data different from the formal information the students usually use. For this purpose, the research applied the clustering based Multi-dimension Tensor Factorization approach to build a recommendation system and confirm that the increment in tensors improves the recommendation accuracy. As a result, this approach permits the user to take advantage of the contextual information to reduce the sparsity issue and increase the recommendation accuracy

MOONLIGHT: A NEW LUNAR LASER RANGING RETROREFLECTOR AND THE LUNAR GEODETIC PRECESSION

Since the 1970s Lunar Laser Ranging (LLR) to the Apollo Cube Corner Retroreflector (CCR) arrays (developed by the University of Maryland, UMD) supplied almost all significant tests of General Relativity (Alley et al., 1970; Chang et al., 1971; Bender et al.,1973): possible changes in the gravitational constant, gravitational self-energy, weak equivalence principle, geodetic precession, inverse-square force-law. The LNF group, in fact, has just completed a new measurement of the lunar geodetic precession with Apollo array, with accuracy of 9 × 10−3, comparable to the best measurement to date. LLR has also provided significant information on the composition and origin of the moon. This is the only Apollo experiment still in operation. In the 1970s Apollo LLR arrays contributed a negligible fraction of the ranging error budget. Since the ranging capabilities of ground stations improved by more than two orders of magnitude, now, because of the lunar librations, Apollo CCR arrays dominate the error budget. With the project MoonLIGHT (Moon Laser Instrumentation for General relativity High-accuracy Tests), in 2006 INFN-LNF joined UMD in the development and test of a new-generation LLR payload made by a single, large CCR (100mm diameter) unaffected by the effect of librations. With MoonLIGHT CCRs the accuracy of the measurement of the lunar geodetic precession can be improved up to a factor 100 compared to Apollo arrays. From a technological point of view, INFN-LNF built and is operating a new experimental apparatus (Satellite/lunar laser ranging Characterization Facility, SCF) and created a new industry-standard test procedure (SCF-Test) to characterize and model the detailed thermal behavior and the optical performance of CCRs in accurately laboratory-simulated space conditions, for industrial and scientific applications. Our key experimental innovation is the concurrent measurement and modeling of the optical Far Field Diffraction Pattern (FFDP) and the temperature distribution of retroreflector payloads under thermal conditions produced with a close-match solar simulator. The apparatus includes infrared cameras for non-invasive thermometry, thermal control and real-time payload movement to simulate satellite orientation on orbit with respect to solar illumination and laser interrogation beams. These capabilities provide: unique pre-launch performance validation of the space segment of LLR/SLR (Satellite Laser Ranging); retroreflector design optimization to maximize ranging efficiency and signal-to-noise conditions in daylight. Results of the SCF-Test of our CCR payload will be presented. Negotiations are underway to propose our payload and SCF-Test services for precision gravity and lunar science measurements with next robotic lunar landing missions. In particular, a scientific collaboration agreement was signed on Jan. 30, 2012, by D. Currie, S. Dell’Agnello and the Japanese PI team of the LLR instrument of the proposed SELENE-2 mission by JAXA (Registered with INFN Protocol n. 0000242-03/Feb/2012). The agreement foresees that, under no exchange of funds, the Japanese single, large, hollow LLR reflector will be SCF-Tested and that MoonLIGHT will be considered as backup instrument