Simulation of surface waves in porous media

We present a novel numerical algorithm for the simulation of seismic wave propagation in porous media, which is particularly suitable for the accurate modelling of surface wave-type phenomena. The differential equations of motion are based on Biot's theory of poro-elasticity and solved with a pseudospectral approach using Fourier and Chebyshev methods to compute the spatial derivatives along the horizontal and vertical directions, respectively. The time solver is a splitting algorithm that accounts for the stiffness of the differential equations. Due to the Chebyshev operator the grid spacing in the vertical direction is non-uniform and characterized by a denser spatial sampling in the vicinity of interfaces, which allows for a numerically stable and accurate evaluation of higher order surface wave modes. We stretch the grid in the vertical direction to increase the minimum grid spacing and reduce the computational cost. The free-surface boundary conditions are implemented with a characteristics approach, where the characteristic variables are evaluated at zero viscosity. The same procedure is used to model seismic wave propagation at the interface between a fluid and porous medium. In this case, each medium is represented by a different grid and the two grids are combined through a domain-decomposition method. This wavefield decomposition method accounts for the discontinuity of variables and is crucial for an accurate interface treatment. We simulate seismic wave propagation with open-pore and sealed-pore boundary conditions and verify the validity and accuracy of the algorithm by comparing the numerical simulations to analytical solutions based on zero viscosity obtained with the Cagniard-de Hoop method. Finally, we illustrate the suitability of our algorithm for more complex models of porous media involving viscous pore fluids and strongly heterogeneous distributions of the elastic and hydraulic material properties.

Summer ozone cycles in the Lisbon metropolitan area and its relation to some meteorological variables

The aim of this work is to study the tropospheric ozone concentrations and daily peak cycles in the Lisbon MetropolitanArea (LMA) during the summer season (June, July and August, JJA) covering the 4-yr study period 2002-2005. Theresults show that all the stations have the same pattern: a minimum in the early morning followed by an increase at 1000UTC reaching to a peak at 1300-1400 UTC, dropped again to minimum values 1800 UTC but with different concentrationsdue to regional and local wind circulations and complex dynamic interactions. We identified in Lisbon city the ozone “weekendeffect”. Finally, we studied an episode of very high levels of tropospheric ozone and related daily ozone concentrationswith some meteorological variables.

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

Effects of nutrients and turbulence on the production of transparent exopolymer particles: a mesocosm study

The production of transparent exopolymer particles (TEP) in response to several environmental variables was studied in 2 mesocosm experiments. The first (Expt 1) examined a gradient of 4 nutrient levels; the second (Expt 2) examined different conditions of silicate availability and zooplankton presence. Tanks were separated in 2 series, one subjected to turbulence and the other not influenced by turbulence. In tanks with nutrient addition, TEP were rapidly formed, with net apparent production rates closely linked to chl a growth rates, suggesting that phytoplankton cells were actively exuding TEP precursors. High nutrient availability increased the absolute concentration of TEP; however, the relative quantity of TEP produced was found to be lower, as TEP concentration per unit of phytoplankton biomass was inversely related to the initial nitrate dose. In Expt 1, an increase in TEP volume (3 to 48 µm equivalent spherical diameter) with nutrient dose was observed; in Expt 2, both silicate addition and turbulence enhanced TEP production and favored aggregation to larger TEP (>48 µm). The presence of zooplankton lowered TEP concentration and changed the size distribution of TEP, presumably by grazing on TEP or phytoplankton. For lower nutrient concentrations, the ratio of particulate organic carbon (POC) to particulate organic nitrogen (PON) followed the Redfield ratio. At higher nutrient conditions, when nutrients were exhausted during the post-bloom, a decoupling of carbon and nitrogen dynamics occurred and was correlated to TEP formation, with a large flow of carbon channeled toward the TEP pool in turbulent tanks. TEP accounted for an increase in POC concentration of 50% in high-nutrient and turbulent conditions. The study of TEP dynamics is crucial to understanding the biogeochemical response of the aquatic system to forcing variables such as nutrient availability and turbulence intensity.

Major variables influencing correct antibiotic prescription by primary care physicians in acute pharyngitis: a cross-sectional study

Objectives:To analyse which are the main variables that influence primary care professionals, in the prescription of antibiotics in patients with acute pharyngitis.To analyse which is the diagnosis pattern used by primary care professionals towards cutepharyngitis. To recognize the clinical and analytical criteria that primary care professionals use, to determine antibiotic treatment in acute pharyngitis.To identify the main clinical variables related with the prescription of antibiotics by primary care professionals, in acute pharyngitis treatment. Design: Cross-­‐sectional study Participants:165 primary care professionals from the Sanitary Region of Girona not attending paediatric patients and randomly selected from 29 ABS managed by two of the main health care providers: Insitut Català de la Salut (ICS) and Institut d’Assistència Sanitària (IAS) Main outcome measures: Each participant will fill out a questionnaire with personal and workplace questions, as well as about knowledge and attitude in front of the acute pharyngitis caused by group A streptococci. They will also answer 4 clinical questions about correct treatment and diagnosis of acute pharyngitis caused by group A streptococci

Empirical study of correlated survival times for recurrent events with proportional hazards margins and the effect of correlation and censoring.

Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

What matters for predicting spatial distributions of trees: techniques, data, or species' characteristics?

Data characteristics and species traits are expected to influence the accuracy with which species' distributions can be modeled and predicted. We compare 10 modeling techniques in terms of predictive power and sensitivity to location error, change in map resolution, and sample size, and assess whether some species traits can explain variation in model performance. We focused on 30 native tree species in Switzerland and used presence-only data to model current distribution, which we evaluated against independent presence-absence data. While there are important differences between the predictive performance of modeling methods, the variance in model performance is greater among species than among techniques. Within the range of data perturbations in this study, some extrinsic parameters of data affect model performance more than others: location error and sample size reduced performance of many techniques, whereas grain had little effect on most techniques. No technique can rescue species that are difficult to predict. The predictive power of species-distribution models can partly be predicted from a series of species characteristics and traits based on growth rate, elevational distribution range, and maximum elevation. Slow-growing species or species with narrow and specialized niches tend to be better modeled. The Swiss presence-only tree data produce models that are reliable enough to be useful in planning and management applications.

Amino acid composition of soybean seeds as affected by climatic variables

The objective of this work was to perform a quantitative analysis of the amino acid composition of soybean seeds as affected by climatic variables during seed filling. Amino acids were determined from seed samples taken at harvest in 31 multi-environment field trials carried out in Argentina. Total amino acids ranged from 31.69 to 49.14%, and total essential and nonessential amino acids varied from 12.83 to 19.02% and from 18.86 to 31.15%, respectively. Variance components expressed as the percentage of total variation showed that the environment was the most important source of variation for all traits, followed by the genotype x environment interaction. Significant explanatory linear regressions were detected for amino acid content regarding: average daily mean air temperature and cumulative solar radiation, during seed filling; precipitation minus potential evapotranspiration, during the whole reproductive period; and the combinations of these climatic variables. Each amino acid behaves differently according to environmental conditions, indicating compensatory effects among them.

Variables físicas que explican la variabilidad de suelo aluvial y su comportamiento espacial

El objetivo de este trabajo fue utilizar el análisis de componentes principales y de semivarianza para seleccionar variables físicas que explicaran la variabilidad de un suelo aluvial, y establecer el comportamiento espacial de las variables seleccionadas, con el fin de definir técnicamente la localización de parcelas experimentales para estudiar los efectos de la abrasividad del suelo sobre el desgaste de herramientas agrícolas. Las pruebas de campo se realizaron en 2008, en un lote plano de 6.000 m² con suelos de textura media a pesada (Vertic Haplustepts). Se hizo un muestreo intensivo en cuadrícula de 10x14 m. Las variables que mayor peso tuvieron en los tres primeros componentes principales fueron los contenidos de limo, arena fina y media, gravilla media, la humedad a capacidad de campo y el coeficiente higroscópico. A excepción de la arena media y la capacidad de campo, las demás propiedades presentaron alta dependencia espacial y su distribución mostró que en el lote experimental se encuentran tres sectores de acumulación diferencial de limo y de arena fina. La combinación de los análisis de componentes principales y geoestadística permitió definir las propiedades del suelo involucradas en el desgaste de herramientas, su patrón espacial y la manera más adecuada de distribuir parcelas experimentales, para estudiar la abrasividad del suelo.

Calibrating predicted tree diameter distributions in Catalonia, Spain

Abstract

Stratified estimation of forest inventory variables using spatially summarized stratifications

Abstract

Análisis de la eficacia de los saques de esquina en la copa del mundo de fútbol 2010. Un intento de identificación de variables explicativas

In soccer, dead-ball moves are those in which the ball is returned to play from a stationary position following an interruption of play. The aim of this study was to analyse the effectiveness of one such dead-ball move, namely corner kicks, and to identify the key variables that determine the success of a shot or header following a corner, thereby enabling a model of successful corner kicks to be proposed. We recorded 554 corner kicks performed during the 2010 World Cup in South Africa and carried out a univariate, bivariate and multivariate analysis of the data. The results indicated that corners were of limited effectiveness in terms of the success of subsequent shots or headers. The analysis also revealed a series of variables that were significantly related to one another, and this enabled us to propose an explanatory model. Although this model had limited explanatory power, it nonetheless helps to understand the execution of corner kicks in practical terms.

Proxemics with multiple dynamic characters in an immersive virtual environment

An experiment was carried out to examine the impact on electrodermal activity of people when approached by groups of one or four virtual characters at varying distances. It was premised on the basis of proxemics theory that the closer the approach of the virtual characters to the participant, the greater the level of physiological arousal. Physiological arousal was measured by the number of skin conductance responses within a short time period after the approach, and the maximum change in skin conductance level 5 s after the approach. The virtual characters were each either female or a cylinder of human size, and one or four characters approached each subject a total of 12 times. Twelve male subjects were recruited for the experiment. The results suggest that the number of skin conductance responses after the approach and the change in skin conductance level increased the closer the virtual characters approached toward the participants. Moreover, these response variables were inversely correlated with the number of visits, showing a typical adaptation effect. There was some evidence to suggest that the number of characters who simultaneously approached (one or four) was positively associated with the responses. Surprisingly there was no evidence of a difference in response between the humanoid characters and cylinders on the basis of this physiological data. It is suggested that the similarity in this quantitative arousal response to virtual characters and virtual objects might mask a profound difference in qualitative response, an interpretation supported by questionnaire and interview results. Overall the experiment supported the premise that people exhibit heightened physiological arousal the closer they are approached by virtual characters.