95 research outputs found

    Motion recognition using nonparametric image motion models estimated from temporal and multiscale co-occurrence statistics

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    Shedding Light on Fish Otolith Biomineralization Using a Bioenergetic Approach

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    Otoliths are biocalcified bodies connected to the sensory system in the inner ears of fish. Their layered, biorhythm-following formation provides individual records of the age, the individual history and the natural environment of extinct and living fish species. Such data are critical for ecosystem and fisheries monitoring. They however often lack validation and the poor understanding of biomineralization mechanisms has led to striking examples of misinterpretations and subsequent erroneous conclusions in fish ecology and fisheries management. Here we develop and validate a numerical model of otolith biomineralization. Based on a general bioenergetic theory, it disentangles the complex interplay between metabolic and temperature effects on biomineralization. This model resolves controversial issues and explains poorly understood observations of otolith formation. It represents a unique simulation tool to improve otolith interpretation and applications, and, beyond, to address the effects of both climate change and ocean acidification on other biomineralizing organisms such as corals and bivalves

    Factors associated with Toxoplasma gondii infection in confined farrow-to-finish pig herds in western France: an exploratory study in 60 herds

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    Background: Infection by Toxoplasma gondii postnatally can occur after ingestion of contaminated meat or water (tissue cysts/oocysts). In Europe, percentage of meat borne infections is estimated between 30 and 63 %, out of which pork makes the most important source. The aim of this study was to (i) investigate the seroprevalence of T. gondii in intensive pig farms from western France; and (ii) identify the risk factors associated with seropositivity. Methods: Data were collected between November 2006 and February 2008 in 60 intensive farrow-to-finish farms, where sera were taken from 3595 fattening pigs, weaned and suckling piglets. Information about three classes of potential seropositivity risk factors were obtained through a questionnaire concerning: (i) breeding characteristics; (ii) farm management; and (iii) husbandry and hygiene. The modified agglutination test (MAT) was used for detection of specific anti T. gondii antibodies in pig sera, starting from 1/6 dilution. Results: The overall proportion of seropositive animals was 6.9 %, but the proportion of herds with at least one positive pig was 100 %. Multivariate logistic mixed model showed an increased seropositivity risk in weaned compared to suckling piglets, and a decreasing risk for mid-sized and large farms. The presence of a Danish entry facility, that clearly separates clean and dirty areas, had a protective effect on T. gondii seropositivity as well. Conclusions: The observed proportion of herds with at least one T. gondii seropositive animal provides further evidence that even in confined conditions of pig breeding, infection occurs, and is common. The highest risk for acquiring T. gondii is at the end of weaning period. Smaller confined pig farms demonstrate higher T. gondii seropositivity levels. This study also showed that Danish entry on farm buildings provides effective protection against T. gondii

    Altimetry for the future: Building on 25 years of progress

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    In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the ‘‘Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion

    Altimetry for the future: building on 25 years of progress

    Get PDF
    In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion

    Motion Recognition Using Nonparametric Image Motion Models Estimated from Temporal and Multiscale Co-Occurrence Statistics

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    A new approach for motion characterization in image sequences is presented. It relies on the probabilistic modeling of temporal and scale cooccurrence distributions of local motion-related measurements directly computed over image sequences. Temporal multiscale Gibbs models allow us to handle both spatial and temporal aspects of image motion content within a unified statistical framework. Since this modeling mainly involves the scalar product between cooccurrence values and Gibbs potentials, we can formulate and address several fundamental issues: model estimation according to the ML criterion (hence, model training and learning) and motion classification. We have conducted motion recognition experiments over a large set of real image sequences comprising various motion types such as temporal texture samples, human motion examples, and rigid motion situations

    Statistical Motion-Based Object Indexing Using Optic Flow Field

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    In this paper, we propose an original approach for content-based video indexing and retrieval. It relies on the tracking of entities of interest and the analysis of their apparent motion. To characterize the dynamic information attached to these objects, we consider a probabilistic modeling of the spatio-temporal distribution of the optic flow field computed within the tracked area after canceling the estimated dominant motion due to camera movement. This leads to a general statistical framework for motion-based video classification and retrieval. We have obtained promising results on a set of various real image sequences.
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