study of the spatial distribution of a pest and its natural enemies provides better decision tool for integrated pest management. the spatial distribution and seasonal activity of panonychus ulmi (koch) and its predator zetzellia mali (ewing) were studied in an apple orchard in khoramdareh (zanjan province, iran) during 2007. the interaction (density dependence) between the prey and its predato...

The Effect of Migration and Spatial Connectivity on Regional Skill Endowments across Europe: 1988-2010 This paper investigates the effects of labour migration and openness to trade on regional skill endowments across the European Union at a time of increased economic integration. Using regional data from Eurostat’s Regio database and the open web source Openflight for the period 1998-2010 we te...

Background: A variable resolution X-ray (VRX) CT scanner provides a great increase in the spatial resolution. In VRX CT scanners, the spatial resolution of the system and its field of view (FOV) can be changed according to the object size. One of the main factors that limit the spatial resolution of VRX CT scanner is the effect of the X-ray focal spot. Materials and Methods: A theoreti...

Evolutionary dynamics are affected by population structure, mutation rates and update rules. Spatial or network structure facilitates the clustering of strategies, which represents a mechanism for the evolution of cooperation. Mutation dilutes this effect. Here we analyze how mutation influences evolutionary clustering on graphs. We introduce new mathematical methods to evolutionary game theory...

Front propagation described by Huygens’ principle is a fundamental mechanism of spatial spreading of a property or an effect, occurring in optics, acoustics, ecology and combustion. If the local front speed varies randomly due to inhomogeneity or motion of the medium (as in turbulent premixed combustion), then the front wrinkles and its overall passage rate (turbulent burning velocity) increase...

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such a...

In the usual statistical approach of spatial classification, it is assumed that the feature observations are independent conditionally on class labels (conditional independence). Discarding this popular assumption, we consider the problem of statistical classification by using multivariate stationary Gaussian Random Field (GRF) for modeling the conditional distribution given class labels of fea...

Motivated by a space-time study on forest health with damage state of trees as the response, we propose a general class of structured additive regression models for categorical responses, allowing for a flexible semiparametric predictor. Nonlinear effects of continuous covariates, time trends, and interactions between continuous covariates are modeled by penalized splines. Spatial effects can b...

This paper considers the problem of prediction in a panel data regression model with spatial autocorrelation. In particular, we consider a simple demand equation for cigarettes based on a panel of 46 states over the period 1963-1992. The spatial autocorrelation due to neighboring states and the individual heterogeneity across states is taken explicitly into account. We derive the best linear un...