[1] Many Earth system science and environmental applications require knowledge of mapped evaporation. Satellite remote sensing can indirectly provide these measurements with a spatial coverage that is logistically and economically impossible to obtain through ground-based observation networks. Here a model for surface energy fluxes estimation based on the assimilation of land surface temperature from satellite is presented. The data assimilation scheme provides a useful framework that allows us to combine measurements and models to produce an optimal and dynamically consistent estimate of the evolving state of the system. The assimilation scheme can take advantage of the synergy of multisensor-multiplatform observations in order to obtain estimations of surface fluxes, flux partitioning, and surface characteristics. The model is based on the surface energy balance and bulk transfer formulation. A simplified soil wetness model, which is a filter of antecedent precipitation, is introduced in order to develop a more robust estimation scheme. This approach is implemented and tested over the Southern Great Plain field experiment domain. Comparisons with observed surface energy fluxes and soil moisture maps have shown that this assimilation system can estimate, when compared with the ground truth observations, the surface energy balance and its partitioning among turbulent heat fluxes. The introduction of the simplified soil wetness model forced by precipitation data improved evaporative fraction estimation. Further research is still required to analyze the reliability of retrieved fluxes in periods where radiation is the limiting factor for latent heat flux.

Rivers close to populated or strategically important areas can cause damages and safety risks to people in the event of a flood. Traditional river flood monitoring systems like radar and ultrasonic sensors may not be completely reliable and require frequent on-site human interventions for calibration. This time-consuming and resource-intensive activity has attracted the attention of many researchers looking for highly reliable camera-based solutions. In this article we propose an automatic Computer Vision solution for river’s water-level monitoring, based on the processing of staff gauge images acquired by a V-IoT device. The solution is based on two modules. The first is implemented on the edge in order to avoid power consumption due to the transmission of poor quality frames, and another is implemented on the Cloud server, where the frames acquired and sent by the V-IoT device are processed for water level extraction. The proposed system was tested on sample images relating to more than a year of acquisitions at a river site. The first module of the proposed solution achieved excellent performances in discerning bad quality frames from good quality ones. The second module achieved very good results too, especially for what it concerns night frames.

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Perinatal stroke is related to possible differences in predisposing factors and outcomes between acutely and retrospectively diagnosed cases. In most cases, there are different risk factors and infections that could play an important role. Thus far, different clinical manifestations have been reported in children presenting with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), ranging from asymptomatic status to severe disease sustained by an immune-mediated inflammatory response. SARS-CoV-2 has been associated with severe neurological diseases including seizures and encephalitis in both adults and children. However, there are still few reports regarding the possible relation between SARS-CoV-2 infection of mothers during pregnancy and the neurologic outcome of the newborns. We described the case of a newborn diagnosed with a perinatal stroke, born at 35 weeks of gestation from a mother presenting with SARS- CoV-2 infection during the last months of pregnancy. We also added a brief review of the literature with similar cases. Close monitoring and early intervention in young children born to infected mothers would be highly recommended for the potential neurodevelopmental risk.