146 research outputs found

    COSMO-SkyMed potential to detect and monitor Mediterranean maquis fires and regrowth: a pilot study in Capo Figari, Sardinia, Italy

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    Mediterranean maquis is a complex and widespread ecosystem in the region, intrinsically prone to fire. Many species have developed specific adaptation traits to cope with fire, ensuring resistance and resilience. Due to the recent changes in socio-economy and land uses, fires are more and more frequent in the urban-rural fringe and in the coastlines, both now densely populated. The detection of fires and the monitoring of vegetation regrowth is thus of primary interest for local management and for understanding the ecosystem dynamics and processes, also in the light of the recurrent droughts induced by climate change. Among the main objectives of the COSMO-SkyMed radar constellation mission there is the monitoring of environmental hazards; the very high revisiting time of this mission is optimal for post-hazard response activities. However, very few studies exploited such data for fire and vegetation monitoring. In this research, Cosmo-SkyMed is used in a Mediterranean protected area covered by maquis to detect the burnt area extension and to conduct a mid-term assessment of vegetation regrowth. The positive results obtained in this research highlight the importance of the very high-resolution continuous acquisitions and the multi-polarization information provided by COSMO-SkyMed for monitoring fire impacts on vegetation

    Bot and gender detection of twitter accounts using distortion and LSA notebook for PAN at CLEF 2019

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    In this work, we present our approach for the Author Profiling task of PAN 2019. The task is divided into two sub-problems, bot, and gender detection, for two different languages: English and Spanish. For each instance of the problem and each language, we address the problem differently. We use an ensemble architecture to solve the Bot Detection for accounts that write in English and a single SVM for those who write in Spanish. For the Gender detection we use a single SVM architecture for both the languages, but we pre-process the tweets in a different way. Our final models achieve accuracy over the 90% in the bot detection task, while for the gender detection, of 84.17% and 77.61% respectively for the English and Spanish languages

    Cross-domain authorship attribution combining instance-based and profile-based features notebook for PAN at CLEF 2019

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    Being able to identify the author of an unknown text is crucial. Although it is a well-studied field, it is still an open problem, since a standard approach has yet to be found. In this notebook, we propose our model for the Authorship Attribution task of PAN 2019, that focuses on cross-domain setting covering 4 different languages: French, Italian, English, and Spanish. We use n-grams of characters, words, stemmed words, and distorted text. Our model has an SVM for each feature and an ensemble architecture. Our final results outperform the baseline given by PAN in almost every problem. With this model, we reach the second place in the task with an F1-score of 68%

    Pediatric cochlear implantation: an update

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    Deafness in pediatric age can adversely impact language acquisition as well as educational and social-emotional development. Once diagnosed, hearing loss should be rehabilitated early; the goal is to provide the child with maximum access to the acoustic features of speech within a listening range that is safe and comfortable. In presence of severe to profound deafness, benefit from auditory amplification cannot be enough to allow a proper language development. Cochlear implants are partially implantable electronic devices designed to provide profoundly deafened patients with hearing sensitivity within the speech range. Since their introduction more than 30 years ago, cochlear implants have improved their performance to the extent that are now considered to be standard of care in the treatment of children with severe to profound deafness. Over the years patient candidacy has been expanded and the criteria for implantation continue to evolve within the paediatric population. The minimum age for implantation has progressively reduced; it has been recognized that implantation at a very early age (12–18 months) provides children with the best outcomes, taking advantage of sensitive periods of auditory development. Bilateral implantation offers a better sound localization, as well as a superior ability to understand speech in noisy environments than unilateral cochlear implant. Deafened children with special clinical situations, including inner ear malformation, cochlear nerve deficiency, cochlear ossification, and additional disabilities can be successfully treated, even thogh they require an individualized candidacy evaluation and a complex post-implantation rehabilitation. Benefits from cochlear implantation include not only better abilities to hear and to develop speech and language skills, but also improved academic attainment, improved quality of life, and better employment status. Cochlear implants permit deaf people to hear, but they have a long way to go before their performance being comparable to that of the intact human ear; researchers are looking for more sophisticated speech processing strategies as well as a more efficient coupling between the electrodes and the cochlear nerve with the goal of dramatically improving the quality of sound of the next generation of implants

    Ranger, an Example of Integration of Robotics into the Home Ecosystem

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    This paper presents the concept and an example of robject, a robotic entity embedded in an everyday object. Robjects use the affordance of the original object to ensure an efficient interaction and a high acceptance. The example of the ranger robot shows that this approach can be applied to the domestic environment. We explore the integration of a robot (robject) into a family household, by regarding the home as a ecosystem, which consists of people, parts, products, activities, and interactions. A test of the ranger robot in families validates this holistic approach and shows the impact of this type of design in respect to the complexity of the robotic system

    Harmonized dataset of surface fuels under Alpine, temperate and Mediterranean conditions in Italy. A synthesis supporting fire management

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    Surface biomass characterization plays a key role in wildfire management. It allows classifying vegetation fuels flammability for fire risk analysis, to define silvicultural prescriptions for fire hazard reduction, to plan prescribed burning, or to model fire behavior and its effects, such as greenhouse gas and pollutant emissions. To facilitate fuel classification and analysis of potential fire behavior and effects in Italy, we harmonized 634 measurements of surface wildland fuels from Alpine, temperate and Mediterranean environments. The dataset provides quantitative data for duff, fine dead fuels and downed woody material, live grasses and shrubs fuel components. Surface fuel data were harmonized by subdividing loads (Mg ha(-1)) to standard size classes for dead (0-6, 6-25 and 25-75 mm) and live (0-6, 6-25 mm) fuels, collecting percent cover and depth/height (cm) of the various fuel components, and classifying observations into 19 fuelbed categories. To ensure comparability with existing vegetation classification systems, we classified each observation according to the European Fuel Map, the Corine Land Cover classes (level IV), the European Forest Types, and the forest categories of the Italian National Forest Inventory. The dataset and a photo description of each fuelbed category are available as Supplementary material. This dataset is the first step to develop several products at the national scale such as: (i) fuel type classification and mapping; (ii) carbon stock and wildfire emission estimates; (iii) calibration of fuel models for the simulation of fire behavior and effects

    Downscaling Climate Change Impacts, Socio-Economic Implications and Alternative Adaptation Pathways for Islands and Outermost Regions

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    This book provides a comprehensive overview of the future scenarios of climate change and management concerns associated with climate change impacts on the blue economy of European islands and outermost regions. The publication collects major findings of the SOCLIMPACT project’s research outcomes, aiming to raise social awareness among policy-makers and industry about climate change consequences at local level, and provide knowledge-based information to support policy design, from local to national level. This comprehensive book will also assist students, scholars and practitioners to understand, conceptualize and effectively and responsibly manage climate change information and applied research. This book provides invaluable material for Blue Growth Management, theory and application, at all levels. This first edition includes up-to-date data, statistics, references, case material and figures of the 12 islands case studies. ¨Downscaling climate change impacts, socio-economic implications and alternative adaptation pathways for Islands and Outermost Regions¨ is a must-read book, given the accessible style and breadth and depth with which the topic is dealt. The book is an up-to-date synthesis of key knowledge on this area, written by a multidisciplinary group of experts on climate and economic modelling, and policy design

    Phenotypic and genetic variation in the response of chickens to Eimeria tenella induced coccidiosis

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    Background: Coccidiosis is a major contributor to losses in poultry production. With emerging constraints on the use of in-feed prophylactic anticoccidial drugs and the relatively high costs of effective vaccines, there are commercial incentives to breed chickens with greater resistance to this important production disease. To identify phenotypic biomarkers that are associated with the production impacts of coccidiosis, and to assess their covariance and heritability, 942 Cobb500 commercial broilers were subjected to a defined challenge with Eimeria tenella (Houghton). Three traits were measured: weight gain (WG) during the period of infection, caecal lesion score (CLS) post mortem, and the level of a serum biomarker of intestinal inflammation, i.e. circulating interleukin 10 (IL-10), measured at the height of the infection.Results: Phenotypic analysis of the challenged chicken cohort revealed a significant positive correlation between CLS and IL-10, with significant negative correlations of both these traits with WG. Eigenanalysis of phenotypic covariances between measured traits revealed three distinct eigenvectors. Trait weightings of the first eigenvector, (EV1, eigenvalue = 59%), were biologically interpreted as representing a response of birds that were susceptible to infection, with low WG, high CLS and high IL-10. Similarly, the second eigenvector represented infection resilience/resistance (EV2, 22%; high WG, low CLS and high IL-10), and the third eigenvector tolerance (EV3, 19%; high WG, high CLS and low IL-10), respectively. Genome-wide association studies (GWAS) identified two SNPs that were associated with WG at the suggestive level.Conclusions: Eigenanalysis separated the phenotypic impact of a defined challenge with E. tenella on WG, caecal inflammation/pathology, and production of IL-10 into three major eigenvectors, indicating that the susceptibility-resistance axis is not a single continuous quantitative trait. The SNPs identified by the GWAS for body weight were located in close proximity to two genes that are involved in innate immunity (FAM96B and RRAD)

    Beyond Conventional N

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