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Jennifer Light,* Maria Boucher,* Jacquelyn Baskin-Miller,* Mike Winstead* Pediatric Hematology-Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA*These authors contributed equally to this workCorrespondence: Mike Winstead, Division of Pediatric Hematology-Oncology, University of North Carolina at Chapel Hill, 101 Manning Drive, Chapel Hill, NC, USA, Tel +1 919-966-1178, Fax +1 919-966-7629, Email mwins@email.unc.eduAbstract: The importance of protecting brain function for people with sickle cell disease (SCD) cannot be overstated. SCD is associated with multiple cerebrovascular complications that threaten neurocognitive function and life. Without screening and preventive management, 11% of children at 24% of adults with SCD have ischemic or hemorrhagic strokes. Stroke screening in children with SCD is well-established using transcranial Doppler ultrasound (TCD). TCD velocities above 200 cm/s significantly increase the risk of stroke, which can be prevented using chronic red blood cell (RBC) transfusion. RBC transfusion is also the cornerstone of acute stroke management and secondary stroke prevention. Chronic transfusion requires long-term management of complications like iron overload. Hydroxyurea can replace chronic transfusions for primary stroke prevention in a select group of patients or in populations where chronic transfusions are not feasible. Silent cerebral infarction (SCI) is even more common than stroke, affecting 39% of children and more than 50% of adults with SCD; management of SCI is individualized and includes careful neurocognitive evaluation. Hematopoietic stem cell transplant prevents cerebrovascular complications, despite the short- and long-term risks. Newer disease-modifying agents like voxelotor and crizanlizumab, as well as gene therapy, may treat cerebrovascular complications, but these approaches are investigational.Keywords: stroke, silent cerebral infarction, moyamoya syndrome, transfusion, stem cell transplantation

Abstract. Climate change is expected to have the greatest impact on the world's economically poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled evapotranspiration (ET), a key input in continental-scale hydrologic models. In this study, a remote sensing model of transpiration (the primary component of ET), driven by a time series of vegetation indices, was used to substitute transpiration from the Global Land Data Assimilation System realization of the National Centers for Environmental Prediction, Oregon State University, Air Force, and Hydrology Research Laboratory at National Weather Service Land Surface Model (GNOAH) to improve total ET model estimates for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against GNOAH ET and the remote sensing method using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance were at humid sites with dense vegetation, while performance at semi-arid sites was poor, but better than the models before hybridization. The reduction in errors using the hybrid model can be attributed to the integration of a simple canopy scheme that depends primarily on low bias surface climate reanalysis data and is driven primarily by a time series of vegetation indices.

L'étude du comportement d'un réservoir de gaz en nappe aquifère réclame une connaissance aussi précise que possible des caractéristiques géométriques et pétrophysiques des couches réservoirs. Les moyens d'investigation sont de deux natures : - forages permettant une connaissance locale des roches réservoirs ; - mesures sismiques conduisant à une estimation approximative des cotes de certains repères stratigraphiques, en des points situés le long de profils. Les données recueillies sont donc, par nature, fragmentaires et discrètes : là où elles sont absentes, il y a lieu d'estimer les grandeurs étudiées en tenant compte au mieux de notre connaissance de leur variabilité spatiale. Ce problème d'interpolation optimale a donné lieu, depuis une vingtaine d'années, à l'élaboration et la mise en pratique d'un outil théorique particulièrement bien adapté aux besoins exprimés par les techniciens des sciences de la terre : la théorie des variables régionalisées due à G. Matheron. Des programmes informatiques mettant en oeuvre cette théorie sont actuellement opérationnels. Des exemples d'application en sont donnés : - tracé automatique de cartes structurales à partir des données de forages et des mesures sismiques ; - estimation des incertitudes de prévision sur les profondeurs ; - tracé de plusieurs variantes de carte compatibles avec les données ; - établissement d'éléments statistiques relatifs à une grandeur caractéristique d'un stockage : volume stockable par exemple ; - génération automatique des données nécessaires à la mise en oeuvre d'un modèle maillé de réservoir. Predicting and monitoring the behavior of an aquifer gas-storage reservoir requires as precise a knowledge as possible of the geometric and petrophysical properties of the reservoir layer. Two ways of obtaining this information can be given: (a) Boreholes which provide local knowledge of the reservoir, and (b) Seismic measurements which lead to more or less accurate depth estimates for some stratigraphic markers at points located along profiles. Therefore, the data are inherently fragmentary. At points where they are lacking, we have to make the most of available information in order to estimate the unknown values. This problem of optimum interpolation has led to a new theoretical approach which is particularly suited to the earth sciences. This theory is called the theory of regionalized variablesby its author, G. Matheron. It has given rise to effective computer programs, and developments are still being made. Examples of possible applications are: (a) Computer-drawn structural maps based on borehole data and seismic measurements; assessment of the prediction uncertainty for the depth of the top-layer; alternative top-layer maps all of which are consistent with the data. (b) Probabilistic evaluation of the storage volume available. (c) Gridded input to reservoir models.