Numerical analysis of the impact of charcoal production on soil hydrological behavior, runoff response and erosion susceptibility

The impact of charcoal production on soil hydraulic properties, runoff response and erosion susceptibility were studied in both field and simulation experiments. Core and composite samples, from 12 randomly selected sites within the catchment of Kotokosu were taken from the 0-10 cm layer of a charcoal site soil (CSS) and adjacent field soils (AFS). These samples were used to determine saturated hydraulic conductivity (Ksat), bulk density, total porosity, soil texture and color. Infiltration, surface albedo and soil surface temperature were also measured in both CSS and AFS. Measured properties were used as entries in a rainfall runoff simulation experiment on a smooth (5 % slope) plot of 25 x 25 m grids with 10 cm resolutions. Typical rainfall intensities of the study watershed (high, moderate and low) were applied to five different combinations of Ks distributions that could be expected in this landscape. The results showed significantly (p < 0.01) higher flow characteristics of the soil under charcoal kilns (increase of 88 %). Infiltration was enhanced and runoff volume reduced significantly. The results showed runoff reduction of about 37 and 18 %, and runoff coefficient ranging from 0.47-0.75 and 0.04-0.39 or simulation based on high (200 mm h-1) and moderate (100 mm h-1) rainfall events over the CSS and AFS areas, respectively. Other potential impacts of charcoal production on watershed hydrology were described. The results presented, together with watershed measurements, when available, are expected to enhance understanding of the hydrological responses of ecosystems to indiscriminate charcoal production and related activities in this region.

Analysis of S-rich CuIn(S,Se)2 layers for photovoltaic applications: Influence of the sulfurization temperature on the crystalline properties of electrodeposited and sulfurized CuInSe2 precursors

This paper reports the microstructural analysis of S-rich CuIn(S,Se)2 layers produced by electrodeposition of CuInSe2 precursors and annealing under sulfurizing conditions as a function of the temperature of sulfurization. The characterization of the layers by Raman scattering, scanning electron microscopy, Auger electron spectroscopy, and XRD techniques has allowed observation of the strong dependence of the crystalline quality of these layers on the sulfurization temperature: Higher sulfurization temperatures lead to films with improved crystallinity, larger average grain size, and lower density of structural defects. However, it also favors the formation of a thicker MoS2 interphase layer between the CuInS2 absorber layer and the Mo back contact. Decreasing the temperature of sulfurization leads to a significant decrease in the thickness of this intermediate layer and is also accompanied by significant changes in the composition of the interface region between the absorber and the MoS2 layer, which becomes Cu rich. The characterization of devices fabricated with these absorbers corroborates the significant impact of all these features on device parameters as the open circuit voltage and fill factor that determine the efficiency of the solar cells.

Analysis by optical absorption and transmission electron microscopy of the strain inhomogeneities in InGaAs/InP strained layers

Optical absorption spectra and transmission electron microscopy (TEM) observations on InGaAs/InP layers under compressive strain are reported. From the band¿gap energy dispersion, the magnitude of the strain inhomogeneities. Is quantified and its microscopic origin is analyzed in view of the layer microstructure. TEM observations reveal a dislocation network at the layer interface the density of which correlates with ¿¿. It is concluded that local variations of dislocation density are responsible for the inhomogeneous strain field together with another mechanism that dominates when the dislocation density is very low.

Defect study of SnO2 nanostructures by cathodoluminescence analysis: Application to nanowires

Defects in SnO2 nanowires have been studied by cathodoluminescence, and the obtained spectra have been compared with those measured on SnO2 nanocrystals of different sizes in order to reveal information about point defects not determined by other characterization techniques. Dependence of the luminescence bands on the thermal treatment temperatures and pre-treatment conditions have been determined pointing out their possible relation, due to the used treatment conditions, with the oxygen vacancy concentration. To explain these cathodoluminescence spectra and their behavior, a model based on first-principles calculations of the surface oxygen vacancies in the different crystallographic directions is proposed for corroborating the existence of surface state bands localized at energy values compatible with the found cathodoluminescence bands and with the gas sensing mechanisms. CL bands centered at 1.90 and 2.20 eV are attributed to the surface oxygen vacancies 100° coordinated with tin atoms, whereas CL bands centered at 2.37 and 2.75 eV are related to the surface oxygen vacancies 130° coordinated. This combined process of cathodoluminescence and ab initio calculations is shown to be a powerful tool for nanowire defect analysis.

Raman microstructural analysis of silicon-on-insulator formed by high dose oxygen ion implantation: As-implanted structures

A microstructural analysis of silicon-on-insulator samples obtained by high dose oxygen ion implantation was performed by Raman scattering. The samples analyzed were obtained under different conditions thus leading to different concentrations of defects in the top Si layer. The samples were implanted with the surface covered with SiO2 capping layers of different thicknesses. The spectra measured from the as-implanted samples were fitted to a correlation length model taking into account the possible presence of stress effects in the spectra. This allowed quantification of both disorder effects, which are determined by structural defects, and residual stress in the top Si layer before annealing. These data were correlated to the density of dislocations remaining in the layer after annealing. The analysis performed corroborates the existence of two mechanisms that generate defects in the top Si layer that are related to surface conditions during implantation and the proximity of the top Si/buried oxide layer interface to the surface before annealing.

Agglomeration and labour productivity in Spanish industry: a long-term analysis

This paper analyzes the relationship between spatial density of economic activity and interregional differences in the productivity of industrial labour in Spain during the period 1860-1999. In the spirit of Ciccone and Hall (1996) and Ciccone (2002), we analyze the evolution of this relationship over the long term in Spain. Using data on the period 1860-1999 we show the existence of an agglomeration effect linking the density of economic activity with labour productivity in the industry. This effect was present since the beginning of the industrialization process in the middle of the 19th century but has been decreasing over time. The estimated elasticity of labour productivity with respect to employment density was close to 8% in the subperiod 1860-1900, reduces to a value of around 7% in the subperiod 1914-1930, to 4% in the subperiod 1965-1979 and becomes insignificant in the final subperiod 1985-1999. At the end of the period analyzed there is no evidence of the existence of net agglomeration effects in the industry. This result could be explained by an important increase in the congestion effects in large industrial metropolitan areas that would have compensated the centripetal or agglomeration forces at work. Furthermore, this result is also consistent with the evidence of a dispersion of industrial activity in Spain during the last decades.

How to assign a likelihood ratio in a footwear mark case: an analysis and discussion in the light of R v T

This article analyses and discusses issues that pertain to the choice of relevant databases for assigning values to the components of evaluative likelihood ratio procedures at source level. Although several formal likelihood ratio developments currently exist, both case practitioners and recipients of expert information (such as judiciary) may be reluctant to consider them as a framework for evaluating scientific evidence in context. The recent ruling R v T and ensuing discussions in many forums provide illustrative examples for this. In particular, it is often felt that likelihood ratio-based reasoning amounts to an application that requires extensive quantitative information along with means for dealing with technicalities related to the algebraic formulation of these approaches. With regard to this objection, this article proposes two distinct discussions. In a first part, it is argued that, from a methodological point of view, there are additional levels of qualitative evaluation that are worth considering prior to focusing on particular numerical probability assignments. Analyses will be proposed that intend to show that, under certain assumptions, relative numerical values, as opposed to absolute values, may be sufficient to characterize a likelihood ratio for practical and pragmatic purposes. The feasibility of such qualitative considerations points out that the availability of hard numerical data is not a necessary requirement for implementing a likelihood ratio approach in practice. It is further argued that, even if numerical evaluations can be made, qualitative considerations may be valuable because they can further the understanding of the logical underpinnings of an assessment. In a second part, the article will draw a parallel to R v T by concentrating on a practical footwear mark case received at the authors' institute. This case will serve the purpose of exemplifying the possible usage of data from various sources in casework and help to discuss the difficulty associated with reconciling the depth of theoretical likelihood ratio developments and limitations in the degree to which these developments can actually be applied in practice.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Irrigation with domestic wastewater: a multivariate analysis of main soil changes

Irrigation with treated domestic sewage wastewater (TSE) is an agricultural practice to reduce water requirements of agroecossystems and the nutrient load impact on freshwaters, but adverse effects on soil chemical (salinization, sodification, etc.) and soil physical properties (alteration in soil porosity and hydraulic conductivity, etc.) have been reported. This study aimed to define some relationships among these changes in an Oxisol using multivariate analysis. Corn (Zea mays L.) and sunflower (Helianthus annuus L.) were grown for two years, irrigated with TSE. The following soil properties were determined: Ca2+; Mg2+; Na+; K+ and H + Al contents, cationic exchangeable capacity (CEC), sum of bases (SB), base saturation (V), texture (sand, silt and clay), macro-, micro-, and cryptoporosity (V MA, V MI and V CRI), water content at soil saturation (θS) and at field capacity (θFC), residual water content (θR), soil bulk density (d s), water dispersed clay (WDC) and saturated hydraulic conductivity (K SAT). Factor analysis revealed the following six principal factors: Fine Porosity (composed of Na+; K+; WDC, θR, θRFC, and V CRI); Large Porosity (θS, d s, V MA, Vs); Soil CEC (Ca2+; Mg2+; CEC, SB, V); Soil Acidity (H + Al); and Soil Texture (factors 5 and 6). A dual pore structure appears clearly to the factors 1 and 2, with an apparent relationship between fine porosity and the monovalent cations Na+ and K+. The irrigation (with potable sodic tap water or sewage wastewater) only had a significant effect on Fine Porosity and Large Porosity factors, while factors 3 and 4 (Soil CEC and Soil Acidity) were correlated with soil depth. The main conclusion was a shift in pore distribution (large to fine pores) during irrigation with TSE, which induces an increase of water storage and reduces the capacity of drainage of salts.

Density modes in spherical 4He shells

We compute the density-fluctuation spectrum of spherical 4HeN shells adsorbed on the outer surface of Cn fullerenes. The excitation spectrum is obtained within the random-phase approximation, with particle-hole elementary excitations and effective interaction extracted from a density-functional description of the shell structure. The presence of one or two solid helium layers adjacent to the adsorbing fullerene is phenomenologically accounted for. We illustrate our results for a selection of numbers of adsorbed atoms on C20, C60, and C120. The hydrodynamical model that has proven successful to describe helium excitations in the bulk and in restricted geometries permits to perform a rather exhaustive analysis of various fluid spherical systems, namely, spheres, cavities, free bubbles, and bound shells of variable size.

Spanning avalanches in the three-dimensional Gaussian random-field Ising model with metastable dynamics: Field dependence and geometrical properties

Spanning avalanches in the 3D Gaussian Random Field Ising Model (3D-GRFIM) with metastable dynamics at T=0 have been studied. Statistical analysis of the field values for which avalanches occur has enabled a Finite-Size Scaling (FSS) study of the avalanche density to be performed. Furthermore, a direct measurement of the geometrical properties of the avalanches has confirmed an earlier hypothesis that several types of spanning avalanches with two different fractal dimensions coexist at the critical point. We finally compare the phase diagram of the 3D-GRFIM with metastable dynamics with the same model in equilibrium at T=0.

How can we teach EBM in clinical practice? : an analysis of barriers to implementation of on-the-job EBM teaching and learning.

Introduction: Evidence-based medicine (EBM) improves the quality of health care. Courses on how to teach EBM in practice are available, but knowledge does not automatically imply its application in teaching. We aimed to identify and compare barriers and facilitators for teaching EBM in clinical practice in various European countries. Methods: A questionnaire was constructed listing potential barriers and facilitators for EBM teaching in clinical practice. Answers were reported on a 7-point Likert scale ranging from not at all being a barrier to being an insurmountable barrier. Results: The questionnaire was completed by 120 clinical EBM teachers from 11 countries. Lack of time was the strongest barrier for teaching EBM in practice (median 5). Moderate barriers were the lack of requirements for EBM skills and a pyramid hierarchy in health care management structure (median 4). In Germany, Hungary and Poland, reading and understanding articles in English was a higher barrier than in the other countries. Conclusion: Incorporation of teaching EBM in practice faces several barriers to implementation. Teaching EBM in clinical settings is most successful where EBM principles are culturally embedded and form part and parcel of everyday clinical decisions and medical practice.

Topologies for poin distributions

The concepts of void and cluster for an arbitrary point distribution in a domain D are defined and characterized by some parameters such as volume, density, number of points belonging to them, shape, etc. After assigning a weight to each void and clusterwhich is a function of its characteristicsthe concept of distance between two point configurations S1 and S2 in D is introduced, both with and without the help of a lattice in the domain D. This defines a topology for the point distributions in D, which is different for the different characterizations of the voids and clusters.

Soil infiltration based on bp neural network and grey relational analysis

Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.