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Knowledge of soil water retention is fundamental to quantify the flow of water and dissolved substances in the subsurface. Water retention is often quantified with models fitted to observed retention points. Interpretation and conversion of parameters from different models is subjective and prone to error. We examined 461 retention curves from the UNSODA database and 660 from the GRIZZLY database. Parameters of the Brooks‐Corey (BC) and van Genuchten (vG) equations were fitted to the retention data. The shape parameters in these functions (λ, m, and n) are closely correlated to soil texture and may be predicted with so‐called pedotransfer functions (PTFs). Among the scale parameters, the saturated water content θs proved to be a robust fitting parameter regardless of parameterization. Reliable optimization of the residual water content θr is more difficult; without any constraint it was negative for 54.4% of the GRIZZLY samples, and its value was strongly correlated to the shape parameters. The BC‐ and vG‐shape parameters are often converted assuming λ = mn, which is incorrect when λ or mn is large (e.g., λ > 0.8). To facilitate the interpretation, conversion, and optimization of retention parameters, we introduce a water retention shape index P This index constitutes an integral measure of the slope of the retention curve and characterizes the retention behavior of a particular soil with a single number. A value for the index can be estimated directly from retention data. For the majority of the samples P ranged between 0 and 0.4; rarely did P exceed 3, which is the maximum expected for fractal behavior. The value for P was related to soil texture: fine‐textured soils tend to have smaller values than coarse‐textured soils. The shape index provides a benchmark for conversion and comparison of parameters.

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We show that for a fractal soil the soil-water conductivity, K, is given bywhere K, is the saturated conductivity, 0 the water content, e its saturated value and D is the fractal dimension obtained from reinterpreting Millington and Quirk's equation for practical values of the porosity e, as ~4/3 qt-(1 --e) 2/3 --1 D = 2 + 32e4/3 in, e-l + (1 --e)2/3 ln(1 --e) -1"

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BackgroundImproving anesthesia administration for elderly population is of particular importance because they undergo considerably more surgical procedures and are at the most risk of suffering from anesthesia-related complications. Intraoperative brain monitors electroencephalogram (EEG) have proved useful in the general population, however, in elderly subjects this is contentious. Probably because these monitors do not account for the natural differences in EEG signals between young and older patients. In this study we attempted to systematically characterize the age-dependence of different EEG measures of anesthesia hypnosis.MethodsWe recorded EEG from 30 patients with a wide age range (19–99 years old) and analyzed four different proposed indexes of depth of hypnosis before, during and after loss of behavioral response due to slow propofol infusion during anesthetic induction. We analyzed Bispectral Index (BIS), Alpha Power and two entropy-related EEG measures, Lempel-Ziv complexity (LZc), and permutation entropy (PE) using mixed-effect analysis of variances (ANOVAs). We evaluated their possible age biases and their trajectories during propofol induction.ResultsAll measures were dependent on anesthesia stages. BIS, LZc, and PE presented lower values at increasing anesthetic dosage. Inversely, Alpha Power increased with increasing propofol at low doses, however this relation was reversed at greater effect-site propofol concentrations. Significant group differences between elderly patients (>65 years) and young patients were observed for BIS, Alpha Power, and LZc, but not for PE.ConclusionBIS, Alpha Power, and LZc show important age-related biases during slow propofol induction. These should be considered when interpreting and designing EEG monitors for clinical settings. Interestingly, PE did not present significant age differences, which makes it a promising candidate as an age-independent measure of hypnotic depth to be used in future monitor development.

The aim of this study is the deduction of an analytic representation of the optimal irrigation flow depending on the border length, hydrodynamic properties, and soil moisture constants, with high values of the coefficient of uniformity. In order not to be limited to the simplified models, the linear relationship of the numerical simulation with the hydrodynamic model, formed by the coupled equations of Barré de Saint-Venant and Richards, was established. Sample records for 10 soil types of contrasting texture were used and were applied to three water depths. On the other hand, the analytical representation of the linear relationship using the Parlange theory of infiltration proposed for integrating the differential equation of one-dimensional vertical infiltration was established. The obtained formula for calculating the optimal unitary discharge is a function of the border strip length, the net depth, the characteristic infiltration parameters (capillary forces, sorptivity, and gravitational forces), the saturated hydraulic conductivity, and a shape parameter of the hydrodynamic characteristics. The good accordance between the numerical and analytical results allows us to recommend the formula for the design of gravity irrigation.

Se realiza un análisis fractal de los eventos de lluvia registrados en Baja California, México, una región semiárida que presenta amplia variabilidad climatológica. Se utilizan series de precipitación de 92 estaciones climatológicas con longitudes de registro mayores a 30 años. Se determinan patrones y características en las series de precipitaciones a partir de valores espaciales y temporales del exponente de Hurst, así como su relación con la temperatura y precipitación media anual, altitud y distribución climatológica. Se emplean con éxito los métodos de rango reescalado, conteo de cajas y análisis multifractal de fluctuación sin tendencia, lo cual permite obtener el valor promedio del exponente de Hurst para diferentes escalas de tiempo. Los datos muestran que la series de precipitación diaria tienden a presentar un patrón persistente; además, los valores del exponente de Hurst se relacionan con el tipo de clima, la altitud, el régimen de lluvias y la temperatura en la zona de estudio. El análisis del exponente de Hurst para diferentes escalas de tiempo evidencia que dicho exponente aumenta a medida que la escala de tiempo en consideración es menor; por lo tanto, la persistencia de la serie se hace más fuerte. Por otra parte, se puede confirmar que la teoría fractal permite analizar el comportamiento de una variable climática, en este caso, la precipitación.