Markov evolutions and hierarchical equations in the continuum I. One-component systems

General birth-and-death as well as hopping stochastic dynamics of infinite particle systems in the continuum are considered. We derive corresponding evolution equations for correlation functions and generating functionals. General considerations are illustrated in a number of concrete examples of Markov evolutions appearing in applications.Comment: 47 page

Spatial pattern and neighbour effects on Helianthemum squamatum seedlings in a Mediterranean gypsum community

Question: Do, in a semi-arid gypsum environment, neighbours condition the spatial patterns of emergence, survival and height of Helianthemum squamatum seedlings ? Location: Vicinity of Chinchón, province of Madrid, Spain (40°11'N, 3° 35'W, 550 m a.s.l.) Methods: We evaluated the effects of neighbours on the survival and growth of naturally emerging Helianthemum seedlings in a semi-arid area during a two-year period. We followed a two-fold approach based on the use of neighbour models for seedling survival and growth and spatial point pattern analyses for seedling emergence, taking into account the germination date. Results: Seedlings appeared clumped in the vicinity of mature Helianthemum individuals. The neighbour models fitted showed that interactions with neighbours were extremely important for the survival and growth of Helianthemum seedlings. These models also suggest that the effects of neighbours on these variables vary with changes in spatial scale and in the abiotic conditions. Some species exerted negative or positive effects on Helianthemum seedlings only at certain spatial scales, and others exerted negative or positive effects at earlier stages of seedling development, but none later and vice versa. Conclusions: We suggest that the observed patterns are mainly influenced by small-scale modifications in soil conditions and microclimate created by neighbours, which change in time and space

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd

Domestic Animals and Epidemiology of Visceral Leishmaniasis, Nepal

Proximity of Leishmania donovani–positive goats is a risk factor for human infection

Some models for multitype spatial point processes, with remarks on analysing multitype patterns

Two classes of ergodic stationary multitype spatial point processes are constructed. These processes have the property that interactions between the types exist, but cannot be detected using standard second-order methods of analysis. Simulations indicate that the interactions can, however, be detected by using ‘empty space' techniques.</jats:p

Implementation of BridgeWatch™: A Program for Monitoring Scour Critical and Unknown Foundation Bridges; Using BridgeWatch to Monitor Road Overtopping

This presentation will highlight the implementation of the patented BridgeWatch® technology in four very diverse geographic locations across the United States. The selected locations include Georgia, Tennessee, Iowa, and Idaho. Each having the full functionality of the BridgeWatch web-based application but each also having unique features ranging from coastal structure monitoring of hurricane storm surge to snow melt occurring in the mountainous regions in North West Idaho. The implementation of BridgeWatch has provided improved forecasting allowing field personnel to concentrate their efforts specifically on bridges at vulnerable sites, rather than entire counties and drainage basins. When alerts are received, monitoring can begin immediately giving personnel valuable time to evaluate specific bridges for scour and erosion activities. Since 2001, The U.S. Departments of Transportation have used the BridgeWatch web-based solution to enable engineers to collectively contribute to more timely and informed decision-making. This allows the engineers to be pro-active in protecting the traveling public from the potentially harmful effects of scour and erosion