Returns to Education and Human Capital Depreciation in Spain.

The main objective of the present paper is to analise the differences in returns to education and rates of human capital depreciation between regions in Spain, during the period 1995-2002. To this end, the theoretical framework proposed by Raymond & Roig (2004) is used to incorporate the depreciation of human capital into the analysis of the private returns on education. Aditionally, the distinction between the two sources of human capital depreciation is approached by means of an estimation by sector –Neuman & Weiss (1995)- and an estimation by occupation.

Inverse modelling in estimating soil hydraulic functions: a Genetic Algorithm approach

The practical application of simulation models in the field is sometimes hindered by the difficulty of deriving the soil hydraulic properties of the study area. The procedure so-called inverse modelling has been investigated in many studies to address the problem where most of the studies were limited to hypothetical soil profile and soil core samples in the laboratory. Often, the numerical approach called forward-backward simulation is employed to generate synthetic data then added with random errors to mimic the real-world condition. Inverse modelling is used to backtrack the expected values of the parameters. This study explored the potential of a Genetic Algorithm (GA) to estimate inversely the soil hydraulic functions in the unsaturated zone. Lysimeter data from a wheat experiment in India were used in the analysis. Two cases were considered: (1) a numerical case where the forward-backward approach was employed and (2) the experimental case where the real data from the lysimeter experiment were used. Concurrently, the use of soil water, evapotranspiration (ET) and the combination of both were investigated as criteria in the inverse modelling. Results showed that using soil water as a criterion provides more accurate parameter estimates than using ET. However, from a practical point of view, ET is more attractive as it can be obtained with reasonable accuracy on a regional scale from remote sensing observations. The experimental study proved that the forward-backward approach does not take into account the effects of model errors. The formulation of the problem is found to be critical for a successful parameter estimation. The sensitivity of parameters to the objective function and their zone of influence in the soil column are major determinants in the solution. Generally, their effects sometimes lead to non-uniqueness in the solution but to some extent are partly handled by GA. Overall, it was concluded that the GA approach is promising to the inverse problem in the unsaturated zone.</p> <p style='line-height: 20px;'><b>Keywords. </b>Genetic Algorithm, inverse modelling, Mualem-Van Genuchten parameters, unsaturated zone, evapotranspiration, soil wate

Spatiotemporal analyses of soil moisture from point to footprint scale in two different hydroclimatic regions

This paper presents time stability analyses of soil moisture at different spatial measurement support scales (point scale and airborne remote sensing (RS) footprint scale 800 m × 800 m) in two different hydroclimatic regions. The data used in the analyses consist of in situ and passive microwave remotely sensed soil moisture data from the Southern Great Plains Hydrology Experiments 1997 and 1999 (SGP97 and SGP99) conducted in the Little Washita (LW) watershed, Oklahoma, and the Soil Moisture Experiments 2002 and 2005 (SMEX02 and SMEX05) in the Walnut Creek (WC) watershed, Iowa. Results show that in both the regions soil properties (i.e., percent silt, percent sand, and soil texture) and topography (elevation and slope) are significant physical controls jointly affecting the spatiotemporal evolution and time stability of soil moisture at both point and footprint scales. In Iowa, using point‐scale soil moisture measurements, the WC11 field was found to be more time stable (TS) than the WC12 field. The common TS points using data across the 3 year period (2002–2005) were mostly located at moderate to high elevations in both the fields. Furthermore, the soil texture at these locations consists of either loam or clay loam soil. Drainage features and cropping practices also affected the field‐scale soil moisture variability in the WC fields. In Oklahoma, the field having a flat topography (LW21) showed the worst TS features compared to the fields having gently rolling topography (LW03 and LW13). The LW13 field (silt loam) exhibited better time stability than the LW03 field (sandy loam) and the LW21 field (silt loam). At the RS footprint scale, in Iowa, the analysis of variance (ANOVA) tests show that the percent clay and percent sand are better able to discern the TS features of the footprints compared to the soil texture. The best soil indicator of soil moisture time stability is the loam soil texture. Furthermore, the hilltops (slope ∼0%–0.45%) exhibited the best TS characteristics in Iowa. On the other hand, in Oklahoma, ANOVA results show that the footprints with sandy loam and loam soil texture are better indicators of the time stability phenomena. In terms of the hillslope position, footprints with mild slope (0.93%–1.85%) are the best indicators of TS footprints. Also, at both point and footprint scales in both the regions, land use–land cover type does not influence soil moisture time stability

Chemical composition and anti-diabetic properties of Cytisus multiflorus

Bakground and aims: The interest on plants with potential medicinal properties has been increasing worldwide. In the Iberian Peninsula there are some endemic species known by the population for their pharmacologic activity with valorization potential that have not been yet characterized. The white Spanish broom (Cytisus multiflorus) is described as having anti-diabetic effect [1] and in a preliminary the hypoglycemic and hyper-insulinemic effect of an aqueous extract has been shown [2]. The aim of this work was to fractionate and analyse the composition of the aqueous extract of C. multiflorus flowering parts and evaluate its potential as an anti-diabetic agent. Materials and methods: The aqueous extract was primarily fractionated by SPE using water:methanol (W:Me) eluent (a 10% step-wise gradient W:Me from 100:0 to 0:100) followed by high performance liquid chromatography with diode array detector (HPLC-DAD). The most relevant fraction were analysed by LC-MS to determine the chemical composition. Total fenol content was determined by a modified Folin-Ciocalteau method and the anti-oxidant activity was evaluated by the DPPH mehod. Finally, the hipoglicemic potential was evaluated in vivo using glucose intolerant rats (GIR). Results: Eleven fractions of the bulk extract were obtained. Seven of these fractions (10, 30, 40, 50, 60, 70 e 80% Me) were found to have a relevant compounds, mostly flavonoid compounds, namely, rutin (50, 60 and 70% Me fractions), ferrulic acid (30% Me), referred as having hypoglicemic effect. The fractions obtained with 50 and 70% Me showed the highest content in phenol equivalents and the highest anti-oxidant effect were found in the 50 and 60% Me fractions. The 30 and 60% Me fraction had no effect on the post-prandial glicemia. Conclusions: The 30, 50, 60 and 70% Me fractions, due to their chemical composition and anti-oxidant effects were the most promising to have anti-diabetic effect. However, the 30 and 60% Me were found to be ineffective. The 50% Me fraction showed both a high content of flavonoid compounds and the highest anti-oxidant power which suggest that it may constitute the most promising one. The anti-diabetic properties of this fraction should be investigated. [1] Camejo-Rodrigues J. et al. (2003). J. Ethnopharmacol, 89, 199-209 [2] Célia M. Antunes, Laurinda R. Areias, Inês P. Vieira, Ana C. Costa, M. Teresa Tinoco, & Júlio Cruz-Morais (2009). Rev. Fitoterapia 9 (Supl.1): 91

A Validated Reversed-Phase HPLC Method for the Determination of Atorvastatin Calcium in Tablets

A Reversed-Phase Liquid Chromatographic (RP-LC) assay method was developed for the quantitative determination of atorvastatin calcium in the presence of its degradation products. The assay involved an isocratic elution of atorvastatin calcium in a LiChroCARTR 250*4 mm HPLC Cartridge LiChrospherR 100 RP-18 (5 μm) column using a mobile phase consisting of 0.1% acetic acid solution: acetonitrile (45:55, v/v), pH = 3.8. The flow rate was 0.8 mL/min and the analytes monitored at 246 nm. The assay method was found to be linear from 8.13 to 23.77 μg/mL. All the validation parameters were within the acceptance range. The developed method was successfully applied to estimate the amount of atorvastatin calcium in tablets.Fil: Simionato, Laura Daniela. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Tecnología Farmacéutica; ArgentinaFil: Ferello, L.. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Tecnología Farmacéutica; ArgentinaFil: Stamer. S.. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Tecnología Farmacéutica; ArgentinaFil: Repetto, M. F.. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Tecnología Farmacéutica; ArgentinaFil: Zubata, P. D.. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Tecnología Farmacéutica; ArgentinaFil: Segall, Adriana Ines. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Tecnología Farmacéutica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentin

Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithm: 1. Conceptual modeling

We used a genetic algorithm (GA) to identify soil water retention (h) and hydraulic conductivity K(h) functions by inverting a soil-water-atmosphere-plant (SWAP) model using observed near-surface soil moisture (0-5 cm) as search criterion. Uncertainties of parameter estimates were estimated using multipopulations in GA and considering data and modeling errors. Three hydrologic cases were considered: (1) homogenous free-draining soil column, (2) homogenous soil column with shallow water table, and (3) heterogeneous soil column under free-drainage condition, considering three different rainfall patterns in northern Texas. Results (cases 1 and 2) showed the identifiability of soil hydraulic parameters improving at coarse and fine scales of the soil textural class. Medium-textured soils posed identifiability problems when the soil is dry. Nonlinearity in (h) and K(h) is greater at drier conditions, and some parameters are less sensitive for estimation. Flow regimes controlled by upward fluxes were found less successful, as the information content of observed near-surface data may no longer influence the hydrologic processes in the subsurface. The identifiability of soil hydraulic parameters was found better when the soil profile is predominantly draining. In case 3, top soil layer hydraulic properties were defined using near-surface data alone as criterion. Adding evapotranspiration (ET) improved identification of the second soil layer, although not all parameters were identifiable. Under uncertainties, (h) was found to be well defined while K(h) is more uncertain. Finally, we applied the method to a validation site in Little Washita watershed, Oklahoma, where derived effective soil hydraulic properties closely matched the measured ones at the field site

Parameter conditioning with a noisy Monte Carlo genetic algorithm for estimating effective soil hydraulic properties from space

The estimation of effective soil hydraulic parameters and their uncertainties is a critical step in all large-scale hydrologic and climatic model applications. Here a scale-dependent (top-down) parameter estimation (inverse modeling) scheme called the noisy Monte Carlo genetic algorithm (NMCGA) was developed and tested for estimating these effective soil hydraulic parameters and their uncertainties. We tested our method using three case studies involving a synthetic pixel (pure and mixed) where all modeling conditions are known, and with actual airborne remote sensing (RS) footprints and a satellite RS footprint. In the synthetic case studies under pure (one soil texture) and mixed-pixel (multiple soil textures) conditions, NMCGA performed well in estimating the effective soil hydraulic parameters even with pixel complexities contributed by various soil types and land management practices (rain-fed/irrigated). With the airborne and satellite remote sensing cases, NMCGA also performed well for estimating effective soil hydraulic properties so that when applied in forward stochastic simulation modeling it can mimic large-scale soil moisture dynamics. The results also suggest a possible scaling down of the effective soil water retention curve (h) at the larger satellite remote sensing pixel compared with the airborne remote sensing pixel. However, it did not generally imply that all effective soil hydraulic parameters should scale down like the soil water retention curve. The reduction of the soil hydraulic parameters was most profound in the saturated soil moisture content ( sat) as we relaxed progressively the soil hydraulic parameter search spaces in our satellite remote sensing studies. Overall, the NMCGA framework was found to be very promising in the inverse modeling of remotely sensed near-surface soil moisture for estimating the effective soil hydraulic parameters and their uncertainties at the remote sensing footprint/climate model grid

Evaluation of economic forecasts for Austria

In this paper, we evaluate macroeconomic forecasts for Austria and analyze the effects of external assumptions on forecast errors. We consider the growth rates of real GDP and the demand components as well as the inflation rate and the unemployment rate. The analyses are based on univariate measures like RMSE and Theil’s inequality coefficient and also on the Mahalanobis distance, a multivariate measure that takes the variances of and the correlations between the variables into account. We compare forecasts generated by the two leading Austrian economic research institutes, the Institute for Advanced Studies (IHS) and the Austrian Institute of Economic Research (WIFO), and additionally consider the forecasts produced by the European Commission. The results indicate that there are no systematic differences between the forecasts of the two Austrian institutes, neither for the traditional measures nor for the Mahalanobis distance. Generally, forecasts become more accurate with a decreasing forecast horizon, as expected; they are unbiased for forecast horizons of less than a year considering traditional measures and for the shortest forecast horizon considering the Mahalanobis distance. Finally, we find that mistakes in external assumptions, in particular regarding EU GDP and the oil price, translate into forecast errors for GDP and inflation