196,016 research outputs found

    Blowhole hormonal analysis: a new approach to the study of tursiops truncatus pregnancy?

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    INTRODUCTION Hormones and behaviour are reciprocally influenced. Monitoring hormones levels can therefore provide insights into the mechanistic aspects of behaviour. Hormones are usually extracted from blood samples or saliva, urine and faeces. In cetaceans, an alternative source may be found in blowhole samples, which can be collected non-invasively. Given the current scientific knowledge on pregnancy endocrinology in dolphins, specific aims of this trail were a) to set up and validate progesterone (P4) and cortisol determination procedures from blowhole samples and b) to determine the concentration and profile of progesterone and cortisol during Tursiops truncatus pregnancy. MATERIAL AND METHODS The study was conducted in the Rimini Delfinario (Italy) on a female monitored from July to September 2003 during the last three months of gestation. The observations were made once a week until the final week before delivery when samples were taken on three alternative days. The bottlenose dolphin was trained to blow into polypropylene sterile bottles with a screw closure. The samples were stored at –20°C until assayed. Concentrations of steroid hormones were determined by validated radioimmunoassays (Seren et al., 1974; Tamanini et al., 1983). RESULTS AND DISCUSSION Progesterone concentrations during the last 12 weeks of gestation always remained high and didn’t change throughout the observed period. However, during the final week progesterone values gradually decreased as the birth date approached and continued to fall until reaching the minimum 40 days after the event. As for cortisol, its concentrations were low until 10 days before the delivery when, as expected, they started to dramatically rise until reaching the maximum the day before the birth. In conclusion, since these results are analogous to those obtained from blood serum and milk in the same species and in other mammals under similar physiological conditions, blowhole samples could represent a suitable biological material in order to detect and quantify by RIA progesterone and cortisol levels during pregnancy. At the same time, the sampling method is easy to be applied and absolutely non-invasive for the animals

    The ARPAL atmospheric operational modeling chain and its applications: description and validation

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    The paper describes the model chain operational at the Meteo-Hydrological Center of the Liguria Region (ARPAL) based on the CNR-ISAC models BOLAM (BOlogna Limited Area Model) and MOLOCH (MOdello LOCale in Hybrid coordinates). Some of the chain applications and a statistical verification of its most recent implementation are also shown. The first operational run of the BOLAM numerical weather prediction (NWP) model at ARPAL was launched in September 1999, in correspondence with the beginning of the Mesoscale Alpine Programme Special Observing Period field campaign. Since then, the collaboration between CNR-ISAC and ARPAL has allowed to maintain and update the operational chain, also thanks to a continuous upgrade of the computational resources available at ARPAL. Since 2005, the non-hydrostatic model MOLOCH has been added to the forecasting chain. In the present operational setup, BOLAM is run over a European domain at the horizontal resolution of about 8 km, using ECMWF-IFS analysis and forecasts as initial and boundary conditions. MOLOCH model is nested in BOLAM, and it runs over a domain including the entire Italian territory, on a 1.5-km horizontal resolution grid. The forecast products, consisting in 72-h BOLAM and 48-h MOLOCH predictions, are available in 1.5 h after the reception of the ECMWF-IFS data. Four runs every day are performed. Other modeling systems in cascade are driven by NWP models. For several years, wind fields obtained from the atmospheric modeling chain have been used to force the wave model WAVEWATCH III, implemented at different resolutions over the Mediterranean basin. Other applications in cascade consist in hydrological prediction for the basins of the Liguria Region, wildfire, and ocean circulation modeling. Moreover, the different ini- tializations of the BOLAM and MOLOCH models provide an important contribution to the ARPAL operational Poor Man’s Ensemble prediction system. A verification based on 3 years of data available from the ARPAL ground observing net- work shows a general capability of the high-resolution models in better forecasting heavy precipitation events, due to a better description of convective phenomena, while a less marked improvement with respect to large-scale models is shown for low precipitation thresholds. Results also show an improvement of model performance for all monitored variables, precipitation, 2-m temperature, and 10-m winds, when resolution increases and when model domains are enlarged

    Prediction of severe thunderstorm events with ensemble deep learning and radar data

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    The problem of nowcasting extreme weather events can be addressed by applying either numerical methods for the solution of dynamic model equations or data-driven artificial intelligence algorithms. Within this latter framework, the most used techniques rely on video prediction deep learning methods which take in input time series of radar reflectivity images to predict the next future sequence of reflectivity images, from which the predicted rainfall quantities are extrapolated. Differently from the previous works, the present paper proposes a deep learning method, exploiting videos of radar reflectivity frames as input and lightning data to realize a warning machine able to sound timely alarms of possible severe thunderstorm events. The problem is recast in a classification one in which the extreme events to be predicted are characterized by a an high level of precipitation and lightning density. From a technical viewpoint, the computational core of this approach is an ensemble learning method based on the recently introduced value-weighted skill scores for both transforming the probabilistic outcomes of the neural network into binary predictions and assessing the forecasting performance. Such value-weighted skill scores are particularly suitable for binary predictions performed over time since they take into account the time evolution of events and predictions paying attention to the value of the prediction for the forecaster. The result of this study is a warning machine validated against weather radar data recorded in the Liguria region, in Italy

    Dr. Duane M. Jackson, Morehouse College, July 2011

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    This video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer

    The wind forecast for safety management of port areas

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    This paper illustrates the research activities linked with the European Project ‘‘Wind and Ports: The forecast of wind for the management and the safety of port areas’’, which involves the Department of Civil, Environmental, and Architectural Engineering of the University of Genova, and the Port Authorities of Genova, La Spezia, Livorno, Savona (Italy) and Bastia (France). The project is based on three tools, namely the historical databases, the global meteorological data and forecasting system, and the data provided by a wide seaport monitoring network that represents also the first product of the project. These tools are processed by a set of numerical models that represents the second product and the key tool to derive three further products, namely the statistical mapping of seaport areas, a medium-term forecasting system and a short-term forecasting system. A web-based GIS system is being realized to make the products of this project directly available to port operators, within a global system for a safe management of port areas. Downstream of these products, this paper provides some insights of the wide validation procedure that is going to be implemented to check and to improve the quality of the results. Further prospects for new research projects using the results of the Wind and Ports Project as starting point are also discussed

    "Reflections on the subject of Emigration from Europe with a view to Settlement in the United States" By M. Carey.

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    "Reflections on the subject of Emigration from Europe with a view to Settlement in the United States: containing bried sketches of the moral and political character of those states. By M. Carey, member of the American philosophical, and of the American Antiquarian Society, and author of The Olive Branch, Cindiciae Hibernicae, essays on banking, on political economy, and on internal improvement. To which are now added the English editor's comments on the subject; together with Important Advice to Emigrants, and Cautions Against Impositions Practiced in the Outports
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