Evaporation is a major factor controlling the hydrological dynamics of surface water reservoirs in dry environments, therefore quantification with minimal uncertainties is desired. The aim of this paper is to assess the spatial variability and impact of riparian vegetation on reservoir evaporation by remote sensing. Eight reservoirs located in subhumid and semi-arid climates in the Brazilian Drylands were studied. Scenes from Landsat 5 and Landsat 8 satellites (1985 and 2018) supplied the data for four evaporation models. For reference evaporation, the Class A Pan and Piché Evaporimeter closest to the reservoirs were considered. The occurrence/density of riparian vegetation was associated with the Normalized Difference Vegetation Index (NDVI) and its influence on evaporation was assessed. The Surface Energy Balance System for Water (AquaSEBS) model presented the best average performance (Nash-Sutcliffe Efficiency coefficient 0.40 ± 0.19). Evaporation was observed to be higher at the reservoirs' margins and near the dams, due to the contact of exposed soil and rock/concrete, respectively, which transfer heat to the water. Marginal areas near the riparian forest presented low evaporation rates with decreases between 18% and 31% in relation to the average. This interdependence was evidenced by the high negative correlation (R 0.87-0.96) between NDVI and evaporation; vegetation reduces radiation because of the shading of the reservoir margin and changes local aerodynamics, reducing evaporation. Depending on the spatial variability of evaporation, it was found that the volumes transferred to the atmosphere may have variations of up to 30%. On average, the evaporated volume in all the studied reservoirs is 450,000 m/day, a quantity enough to supply more than two million people. Overall, the results of this study contribute not only to a better understanding of the spatial variability of evaporation in surface reservoirs, but also of the interdependence between riparian vegetation and evaporation rates.
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http://dx.doi.org/10.1016/j.scitotenv.2021.149059 | DOI Listing |
Spatially variable genes (SVGs) reveal the molecular and functional heterogeneity of cells across different spatial regions of a tissue. We found that sample-wide SVGs, identified by previous methods across the whole sample, largely overlap with cell-type marker genes derived from single-cell gene expression, leaving the spatial location information largely underutilized. We developed ctSVG, a computational method specifically tailored for Visium HD spatial transcriptomics at single-cell resolution.
View Article and Find Full Text PDFBrain functional connectivity patterns exhibit distinctive, individualized characteristics capable of distinguishing one individual from others, like fingerprint. Accurate and reliable depiction of individualized functional connectivity patterns during infancy is crucial for advancing our understanding of individual uniqueness and variability of the intrinsic functional architecture during dynamic early brain development, as well as its role in neurodevelopmental disorders. However, the highly dynamic and rapidly developing nature of the infant brain presents significant challenges in capturing robust and stable functional fingerprint, resulting in low accuracy in individual identification over ages during infancy using functional connectivity.
View Article and Find Full Text PDFBackground: Transcranial Electrical Stimulation (TES), Temporal Interference Stimulation (TIS), Electroconvulsive Therapy (ECT) and Tumor Treating Fields (TTFields) are based on the application of electric current patterns to the brain.
Objective: The optimal electrode positions, shapes and alignments for generating a desired current pattern in the brain vary between persons due to anatomical variability. The aim is to develop a flexible and efficient computational approach to determine individually optimal montages based on electric field simulations.
J Cent Nerv Syst Dis
January 2025
CRCSEP, Université Nice Cote d'Azur, Nice, France.
Multiple sclerosis (MS) falls within the spectrum of central nervous system (CNS) demyelinating diseases that may lead to permanent neurological disability. Fundamental to the diagnosis and clinical surveillance is magnetic resonance imaging (MRI) that allows for the identification of T2-hyperintensities associated with autoimmune injury that demonstrate distinct spatial distribution patterns. Here, we describe the clinical experience of a 31-year-old, right-handed, White man seen in consultation at The University of Texas Southwestern Medical Center in Dallas, Texas, following complaints of headaches that began after head trauma related to military service.
View Article and Find Full Text PDFMed Phys
January 2025
Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada.
Background: A stemless plastic scintillation detector (SPSD) is composed of an organic plastic scintillator coupled to an organic photodiode. Previous research has shown that SPSDs are ideally suited to challenging dosimetry measurements such as output factors and profiles in small fields. Lacking from the current literature is a systematic effort to optimize the performance of the photodiode component of the detector.
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