Basic oxygen furnace slag as a treatment material for pathogens: Contribution of inactivation and attachment in virus attenuation

Basic oxygen furnace (BOF) slag media were studied as a potential treatment material in on-site sanitation systems. Batch and column studies were conducted to evaluate attenuation of the bacteriophage PR772 and 0.190 mu m diameter microspheres by BOF media, and to delineate the relative contributions of two principle processes of virus attenuation: inactivation and attachment. In the batch studies, conducted at 4 degrees C, substantial inactivation of PR772 did not occur in the pH 7.6 and 9.5 suspensions. At pH 11.4, bimodal inactivation of PR772 was observed, at an initial rate of 2.1 log C/C(0) day(-1) for the first two days, followed by a much slower rate of 0.124 log C/C(0) day(-1) over the following 10 days. Two column studies were conducted at 4 degrees C at a flow rate of 1 pore volume day(-1) using two slag sources (Stelco, Ontario; Tubarao, Brazil) combined with sand and pea gravel. In both column experiments, the effluent microsphere concentration approached input concentrations over time (reductions of 0.1-0.2 log C/C(0)), suggesting attachment processes for microspheres were negligible. Removal of PR772 virus was more pronounced both during the early stages of the experiments, but also after longer transport times (0.5-1.0 log C/C(0)). PR772 reduction appeared to be primarily as a result of virus inactivation in response to the elevated pH conditions generated by the BOF mixture (10.6-11.4). On-site sanitation systems using BOF media should be designed to maintain sufficient contact time between the BOF media and the wastewater to allow sufficient residence time of pathogens at elevated pH conditions. (C) 2009 Published by Elsevier Ltd.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.