Sensitivity of desert dust emissions to model horizontal grid spacing during the Bodélé Dust Experiment 2005

The impact of model horizontal grid spacing on meteorology and dust emissions in the Bodélé depression was investigated during the well-documented period of the Bodélé Dust Experiment 2005 (BoDEx 2005). Five horizontal grid spacing ranging from 100 km to 5 km were tested. The main conclusion of these sensitivity tests is that the meteorology of the Bodélé depression is quite insensitive to model horizontal grid spacing below 50 km in agreement with Todd et al.'s (2008b) results. Below 50 km, dust emissions also appear relatively insensitive to model mesh size, the influence of model horizontal grid spacing on dust emissions tending towards an asymptotic behavior as model mesh size is reduced

Erosion éolienne dans les régions arides et semi-arides africaines : processus physiques, métrologie et techniques de lutte

Cette étude présente une approche par modélisation pour estimer les émissions de particules terrigènes provenant de la région semi-aride sahélienne. Deux modèles spécifiques ont été combinés : l'un pour représenter le couvert herbacé saisonnier au Sahel, l'autre pour quantifier les émissions de particules terrigènes. Le Sahel (12°N–20°N, 20°W–35°E) constitue la région d'étude et les simulations ont été effectuées à une résolution spatiale de 0,25° sur une période de 4 ans (2004-2007). Le forçage pluviométrique provient d'un produit satellitaire TRMM (Tropical Rainfall Measuring Mission). Les autres forçages météorologiques ont été fournis par le CEPMMT (Centre Européen pour les Prévisions Météorologiques à Moyen Terme). La rugosité aérodynamique de la surface a été estimée à partir d'une paramétrisation empirique pour représenter sa dynamique temporelle à partir des simulations du couvert végétal saisonnier. Les simulations de végétation ont été comparées à des observations satellitaires au préalable. Lorsqu'aucune végétation ne pousse, les propriétés de la surface ont été considérées constantes et déduites de mesures satellitaires. Les flux d'émission annuels simulés sont compris entre 100 et 400 Mt pour l'ensemble de la région considérée, en accord avec des travaux précédents portant sur le Sahara. Leur variabilité interannuelle est aussi en accord avec les observations satellitaires. Nous avons par ailleurs mis en évidence l'existence d’une "frange émissive saisonnièrement végétalisée" dont la superficie varie selon l'année et pour laquelle les émissions annuelles sont comprises entre 0,5 Mt et 20 Mt pour la période considérée. L'inhibition en masse de ces émissions due à la végétation saisonnière et à l'humidité superficielle du sol sur cette frange varie de 20% à 35%

A discrete cluster of urinary biomarkers discriminates between active systemic lupus erythematosus patients with and without glomerulonephritis.

BackgroundManagement of lupus nephritis (LN) would be greatly aided by the discovery of biomarkers that accurately reflect changes in disease activity. Here, we used a proteomics approach to identify potential urinary biomarkers associated with LN.MethodsUrine was obtained from 60 LN patients with paired renal biopsies, 25 active non-LN SLE patients, and 24 healthy controls. Using Luminex, 128 analytes were quantified and normalized to urinary creatinine levels. Data were analyzed by linear modeling and non-parametric statistics, with corrections for multiple comparisons. A second cohort of 33 active LN, 16 active non-LN, and 30 remission LN SLE patients was used to validate the results.ResultsForty-four analytes were identified that were significantly increased in active LN as compared to active non-LN. This included a number of unique proteins (e.g., TIMP-1, PAI-1, PF4, vWF, and IL-15) as well as known candidate LN biomarkers (e.g., adiponectin, sVCAM-1, and IL-6), that differed markedly (>4-fold) between active LN and non-LN, all of which were confirmed in the validation cohort and normalized in remission LN patients. These proteins demonstrated an enhanced ability to discriminate between active LN and non-LN patients over several previously reported biomarkers. Ten proteins were found to significantly correlate with the activity score on renal biopsy, eight of which strongly discriminated between active proliferative and non-proliferative/chronic renal lesions.ConclusionsA number of promising urinary biomarkers that correlate with the presence of active renal disease and/or renal biopsy changes were identified and appear to outperform many of the existing proposed biomarkers

Fabiana stephanii A. T. Hunz. et Barboza

Quebrada a 43 km de Azapa. Camino a ChapiquiñaUniversidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentin

Factive and nonfactive mental state attribution

Factive mental states, such as knowing or being aware, can only link an agent to the truth; by contrast, nonfactive states, such as believing or thinking, can link an agent to either truths or falsehoods. Researchers of mental state attribution often draw a sharp line between the capacity to attribute accurate states of mind and the capacity to attribute inaccurate or “reality-incongruent” states of mind, such as false belief. This article argues that the contrast that really matters for mental state attribution does not divide accurate from inaccurate states, but factive from nonfactive ones

Contrast response function estimation with nonparametric Bayesian active learning

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast sensitivity functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This article describes the development of the machine learning contrast response function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the machine learning contrast sensitivity function (MLCSF) was evaluated to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential

Concentrador cilíndrico parabólico aplicado a la generación de vapor de uso industrial : Evaluación óptica y térmica de un prototipo

En este trabajo se presenta el diseño, desarrollo y estudio de funcionamiento de un prototipo de concentrador cilindrico parabólico (CCP) destinado a la generación de vapor de agua de baja entalpia para uso industrial. El área de apertura del prototipo es de 2,5 m². Se realiza una evaluación óptica de su funcionamiento consistente en un mapeo de la superficie reflectante utilizando punteros láser. Por medio de un software de simulación específico, se determina el tiempo de ajuste necesario para que el plano de la parábola se mantenga orientado de manera de optimizar el aprovechamiento energético. Este tiempo de ajuste podrá ser utilizado en el sistema de control discontinuo de seguimiento solar. Por último se realiza un ensayo de baja temperatura de acuerdo a la norma ASHRAE 93-1986 (RA 91) con el que se obtiene un rendimiento óptico del 70 %.This paper presents the design, technological development and functioning analysis of a parabolic trough collector prototype, which will be used for industrial low enthalpy steam generation. The prototype aperture area is 2,5 m². An optical evaluation of its behaviour is made by performing a mapping of its reflectance surface by means of laser pointers. A specific simulation software was used in order to determine the necessary adjusting time for the parabola surface to be maintained well guided, which will optimize the use of energy. This adjusting time will be used in the broken control system of collector sun tracking. A low temperature test was made, in accordance to ASHRAE 93-1986 (RA 91) standard, from which an optical efficiency of 70 % was determinedAsociación Argentina de Energías Renovables y Medio Ambiente (ASADES