870 research outputs found

    Artificial Neural Networks to reconstruct incomplete satellite data: application to the Mediterranean Sea Surface Temperature

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    Satellite data can be very useful in applications where extensive spatial information is needed, but sometimes missing data due to presence of clouds can affect data quality. In this study a methodology for pre-processing sea surface temperature (SST) data is proposed. The methodology, that processes measures in the visible wavelength, is based on an Artificial Neural Network (ANN) system. The effectiveness of the procedure has been also evaluated comparing results obtained using an interpolation method. After the methodology has been identified, a validation is performed on 3 different episodes representative of SST variability in the Mediterranean sea. The proposed technique can process SST NOAA/AVHRR data to simulate severe storm episodes by means of prognostic meteorological models

    Spatial-temporal modelling of disease risk accounting for PM2.5 exposure in the province of pavia: An area of the Po valley

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    Spatio-temporal Bayesian disease mapping is the branch of spatial epidemiology interested in providing valuable risk estimates in certain geographical regions using administrative areas as statistical units. The aim of the present paper is to describe spatio-temporal distribution of cardiovascular mortality in the Province of Pavia in 2010 through 2015 and assess its association with environmental pollution exposure. To produce reliable risk estimates, eight different models (hierarchical log-linear model) have been assessed: temporal parametric trend components were included together with some random effects that allowed the accounting of spatial structure of the region. The Bayesian approach allowed the borrowing information effect, including simpler model results in the more complex setting. To compare these models, Watanabe–Akaike Information Criteria (WAIC) and Leave One Out Information Criteria (LOOIC) were applied. In the modelling phase, the relationship between the disease risk and pollutants exposure (PM2.5) accounting for the urbanisation level of each geographical unit showed a strong significant effect of the pollutant exposure (OR = 1.075 and posterior probability, or PP, >0.999, equivalent to p < 0.001). A high-risk cluster of Cardiovascular mortality in the Lomellina subareas in the studied window was identified

    Who decides what: Spatial issues in environmental decisions

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    An integrated modelling approach is used in this work to assess the differences in defining air quality policies in spatial domains of different extensions. The tools used, SHERPA and RIAT+, are public domain and allow to rapidly define the emission scenario of the European area under examination and to solve a multi-objective problem to trade-off air quality improvement versus the costs of implementing the pollutant abatement measures. The territory considered is Northern Italy and the pollutant analysed in PM2.5, which is largely of secondary origin. The study demonstrates the importance of a proper definition of the administrative and physical boundaries of the air pollution problem, which may determine higher costs when the correct scale of decisions is missed.of the administrative and physical boundaries of the air pollution problem, which may determine highercosts when the correct scale of decisions is missed

    A practice-related risk score (PRS): a DOPPS-derived aggregate quality index for haemodialysis facilities

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    Background. The Dialysis Outcomes and Practice Patterns Study (DOPPS) database was used to develop and validate a practice-related risk score (PRS) based on modifiable practices to help facilities assess potential areas for improving patient care. Methods. Relative risks (RRs) from a multivariable Cox mortality model, based on observational haemodialysis (HD) patient data from DOPPS I (1996-2001, seven countries), were used. The four practices were the percent of patients with Kt/V >= 1.2, haemoglobin >= 11 g/dl (110 g/l), albumin >= 4.0 g/dl (40g/l) and catheter use, and were significantly related to mortality when modelled together. DOPPS II data (2002-2004, 12 countries) were used to evaluate the relationship between PRS and mortality risk using Cox regression. Results. For facilities in DOPPS I and II, changes in PRS over time were significantly correlated with changes in the standardized mortality ratio (SMR). The PRS ranged from 1.0 to 2.1. Overall, the adjusted RR of death was 1.05 per 0.1 points higher PRS (P < 0.0001). For facilities in both DOPPS I and II (N = 119), a 0.2 decrease in PRS was associated with a 0.19 decrease in SMR (P = 0.005). On average, facilities that improved PRS practices showed significantly reduced mortality over the same time frame. Conclusions. The PRS assesses modifiable HD practices that are linked to improved patient survival. Further refinements might lead to improvements in the PRS and will address regional variations in the PRS/mortality relationship

    Dura mater marsupialisation and outcome in a cat with a spinal subarachnoid pseudocyst: a case report

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    A six-month-old male domestic shorthair cat was referred with a history of acute-onset paraplegia, over the previous two months. The neurological examination revealed a thoracolumbar lesion. After myelography and myelo-computed tomography (myelo-CT), the diagnosis of a T13\u2013L1 subarachnoid pseudocyst potentially related to a previous L1 vertebral body fracture or malformation was made. Surgical decompression consisted in dorsal laminectomy followed by durotomy and marsupialisation. Immediately after surgery the cat improved neurologically and showed progressive improvement of his neurological signs over the next few months, until he died, from unrelated causes, approximately 18 months after surgery

    COMBINED USE OF SPACE-BORNE OBSERVATIONS OF NO2 AND REGIONAL CTM MODEL FOR AIR QUALITY MONITORING IN NORTHERN ITALY

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    The use of space-borne measurements of trace gas constituents for air quality monitoring is considerably increased during the past decade. This is due mainly to the new generation sensors able to observe large areas with good temporal resolution and due to new assimilation techniques that allow a synergetic use of information from satellite and from Chemical Transport Models (CTM). In fact the in situ sampling method used by the local environmental agencies for air quality monitoring is becoming too expensive to be further continued without a sensible reduction in the number of observing stations. In this paper we present the work that has been performed so far within the QUITSAT project funded by the Italian Space Agency. SCIAMACHY (Uv-Vis spectrometer on board ESA-ENVISAT platform from 2002) observations of earth radiance are used to retrieve NO2 tropospheric column by DOAS spectrometric technique and radiative transfer modelling for AMF computation. Such kind of product has been widely used to estimate emissions, to monitor pollution hot spot as well as cross country and intercontinental transport. Within this work we have merged the column measurements of nitrogen dioxide with the simulations of the Transport Chemical Aerosol Model (TCAM) to improve the model output at the ground level. The method used is a weighted rescaling of the model column in the troposphere according to the SCIAMACHY observations where the weights are the measurement errors and the model column variances within the satellite ground-pixel, respectively. The employed data are related to the Northern Italy area. The obtained ground concentrations of NO2 have been compared with in-situ observations performed by the regional environmental agencies. Results show good agreement mainly where well horizontal mixing is present. The ground concentration from SCIAMACHY-TCAM gives an average NO2 amount within the satellite ground-pixel of 30x60 km2 that is important information for air quality assessment on a regional and/or national scale not easy to obtain only with ground-based observations. Our conclusions thus stress also the actual potential role of satellite observations combined with regional CTM models in the context of air quality monitoring, mainly in rural area, where the ground-based observations are missing

    Metallicity and conductivity crossover in white light illuminated CH3_3NH3_3PbI3_3 perovskite

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    The intrinsic d.c. electrical resistivity (ρ\rho) - measurable on single crystals only - is often the quantity first revealing the properties of a given material. In the case of CH3_3NH3_3PbI3_3 perovskite measuring ρ\rho under white light illumination provides insight into the coexistence of extended and shallow localized states (0.1 eV below the conduction band). The former ones dominate the electrical conduction while the latter, coming from neutral defects, serve as a long-lifetime charge carrier reservoir accessible for charge transport by thermal excitation. Remarkably, in the best crystals the electrical resistivity shows a metallic behaviour under illumination up to room temperature, giving a new dimension to the material in basic physical studies
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