Abstract-Due to adverse aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with Mobility Prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on its predicted mobility pattern. Anchor nodes with known locations in the network will control the whole localization process in order to balance the tradeoff between localization accuracy, localization coverage and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.

Abstract-Due to adverse aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with Mobility Prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on its predicted mobility pattern. Anchor nodes with known locations in the network will control the whole localization process in order to balance the tradeoff between localization accuracy, localization coverage and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.

Abstract. The reliable assessment of hazards or risks arising from water contamination problems and the design of efficient and effective techniques to mitigate these problems require the capability to predict the behavior of chemical contaminants in flowing water. Most attempts at quantifying contaminant transport have relied on a solution of some form of the advection-dispersion-reaction equation. In this paper, the Backward Beam Equation (BBE) method is studied and enhanced to solve the Advection-Dispersion Equation (ADE) within a contaminant source identification context. Even though the BBE has been applied successfully to parabolic problems before, it has never been applied to solving the ADE with heterogeneous parameters. The BBE employed in this work is capable of recovering the time history and spatial distribution of a groundwater contaminant plume from measurements of its current position. Using examples involving deterministic heterogeneous dispersion coefficients, we show that the method is robust enough to handle heterogeneous parameters. By altering the method, to produce a hybrid between a marching and a jury method called the Marching-Jury Backward Beam Equation (MJBBE), we were also able to make the problem practical to solve. IntroductionGroundwater amounts to about half of the U. Furthermore, by accurately identifying pollution sources, the time and cost requirements associated with the complex and lengthy process of remediation can be dramatically reduced. Most attempts at quantifying contaminant transport have relied on solving some form of a well-known governing equation referred to as advection-dispersion-reaction equation. In identifying the source of pollution we have to solve the governing equations backward in time. Modeling contaminant transport using reverse time is an ill-posed problem since the process, being dispersive, is irreversible. Because of this illposedness, the problems have discontinuous dependence on data and are sensitive to the errors in data. A problem is categorized as a well-posed problem if (1) the solution exists, (2) the solution is unique, and (3) the problem is stable [Tikhonov and Arsenin, 1977]. Problems that do not satisfy these criteria are called ill-posed. For the groundwater contamination problem the plume has to have originated from someplace, therefore, physically, the plume exists. However, in mathematically rigorous terms, the fact that we have a presentday plume concentration does not necessarily mean that we satisfy the existence criterion. The solution exists only when we have perfect and consistent model and data that satisfy extremely restrictive conditions. Meeting the stability criterion is a difficult task to accomplish since numerical schemes that are 2113

Bacterial diversity in soil is high relative to more homogeneous environments (e.g., freshwater or marine habitats). Isolation imparted by fragmented aquatic microhabitats in unsaturated soil likely plays a large role in creating this diversity. We evaluate the role of soil texture, which determines the extent and connectivity of microhabitats, in constraining bacterial diversity. Soil samples with a range of textures were collected from sixteen sites across Connecticut and Massachusetts. Soil particle size distributions were measured to determine soil texture (% sand, % silt and % clay). Soil chemical characteristics (e.g., pH, % , %N) that might influence diversity were quantified for each site. Terminal restriction fragment length polymorphism (T-RFLP) analysis was performed to characterize the diversity (richness, Shannon's H , and evenness) of soil bacterial communities. Bacterial species richness increased significantly (p = 0.04) with the coarseness of the soil, quantified as % sand. No trend in H or E were observed; all communities exhibited high diversity and evenness. The increase in species richness in coarser soils is likely due to the increased number of isolated water films in soils with larger pores, suggesting that pore-scale hydrologic regime constrains bacterial richness in soil.

BackgroundChildhood diarrhea continues to be a public health problem in developing countries, including Ethiopia. Detecting clusters and trends of childhood diarrhea is important to designing effective interventions. Therefore, this study aimed to investigate spatiotemporal clustering and seasonal variability of childhood diarrhea in northwest Ethiopia.MethodsRetrospective record review of childhood diarrhea was conducted using quarterly reported data to the district health office for the seven years period beginning July 1, 2007. Thirty three districts were included and geo-coded in this study. Spatial, temporal and space-time scan spatial statistics were employed to identify clusters of childhood diarrhea. Smoothing using a moving average was applied to visualize the trends and seasonal pattern of childhood diarrhea. Statistical analyses were performed using Excel® and SaTScan programs. The maps were plotted using ArcGIS 10.0.ResultsChildhood diarrhea in northwest Ethiopia exhibits statistical evidence of spatial, temporal, and spatiotemporal clustering, with seasonal patterns and decreasing temporal trends observed in the study area. A most likely purely spatial cluster was found in the East Gojjam administrative zone of Gozamin district (LLR = 7123.89, p <0.001). The most likely spatiotemporal cluster was detected in all districts of East Gojjam zone and a few districts of the West Gojjam zone (LLR = 24929.90, p<0.001), appearing from July 1, 2009 to June 30, 2011. One high risk period from July 1, 2008 to June 30, 2010 (LLR = 9655.86, p = 0.001) was observed in all districts. Peak childhood diarrhea cases showed a seasonal trend, occurring more frequently from January to March and April to June.ConclusionChildhood diarrhea did not occur at random. It has spatiotemporal variation and seasonal patterns with a decreasing temporal trend. Accounting for the spatiotemporal variation identified in the study areas is advised for the prevention and control of diarrhea.