Case-control study on risk factors of esophageal cancer

Objective: To explore the influencing factors of esophageal cancer in the trunk basin of Dawen river , Shandong province. Methods: A case- control study was carried out: 195 living cases of diagnosed esophageal cancer and 195 controls were matched by age and sex and surveyed by a unified inventory. Results: T he following items could rises the risk of esophageal cancer : hard dry diet, smoke homemade cigarettes, alcohol consumption> 500 ml/ day, relatives with tumor in history ( OR = 51850, OR = 161 158, OR = 111 513, OR = 11 827, respectively ) . While drinking tea may have protective effect against esophageal cancer ( OR = 01 311). Conclusion: The high incidence of esophageal cancer in the area is relative not only to the environment and dietary factors, but also to the family history of esophageal cancer.

Spatial prediction on a river network

This article develops methods for spatially predicting daily change of dissolved oxygen (Dochange) at both sampled locations (134 freshwater sites in 2002 and 2003) and other locations of interest throughout a river network in South East Queensland, Australia. In order to deal with the relative sparseness of the monitoring locations in comparison to the number of locations where one might want to make predictions, we make a classification of the river and stream locations. We then implement optimal spatial prediction (ordinary and constrained kriging) from geostatistics. Because of their directed-tree structure, rivers and streams offer special challenges. A complete approach to spatial prediction on a river network is given, with special attention paid to environmental exceedances. The methodology is used to produce a map of Dochange predictions for 2003. Dochange is one of the variables measured as part of the Ecosystem Health Monitoring Program conducted within the Moreton Bay Waterways and Catchments Partnership.

Characterization of alluvial formation by stochastic modelling of paleo-fluvial processes: The concept and method

Modelling fluvial processes is an effective way to reproduce basin evolution and to recreate riverbed morphology. However, due to the complexity of alluvial environments, deterministic modelling of fluvial processes is often impossible. To address the related uncertainties, we derive a stochastic fluvial process model on the basis of the convective Exner equation that uses the statistics (mean and variance) of river velocity as input parameters. These statistics allow for quantifying the uncertainty in riverbed topography, river discharge and position of the river channel. In order to couple the velocity statistics and the fluvial process model, the perturbation method is employed with a non-stationary spectral approach to develop the Exner equation as two separate equations: the first one is the mean equation, which yields the mean sediment thickness, and the second one is the perturbation equation, which yields the variance of sediment thickness. The resulting solutions offer an effective tool to characterize alluvial aquifers resulting from fluvial processes, which allows incorporating the stochasticity of the paleoflow velocity.