In Xuan Wei County, Yunnan Province, lung cancer mortality is among China's highest and, especially in females, is more closely associated with indoor burning of "smoky" coal, as opposed to wood or "smokeless" coal, than with tobacco smoking. Indoor air samples were collected during the burning of all three fuels. In contrast to wood and smokeless coal emissions, smoky coal emission has high concentrations of submicron particles containing mutagenic organics, especially in aromatic and polar fractions. These studies suggested an etiologic link between domestic smoky coal burning and lung cancer in Xuan Wei.

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Abstract-Location is an important feature for many applications, and wireless networks can better serve their clients by anticipating client mobility. As a result, many location predictors have been proposed in the literature, though few have been evaluated with empirical evidence. This paper reports on the results of the first extensive empirical evaluation of location predictors, using a two-year trace of the mobility patterns of over 6,000 users on Dartmouth's campus-wide Wi-Fi wireless network.We implemented and compared the prediction accuracy of several location predictors drawn from two major families of domain-independent predictors, namely Markov-based and compression-based predictors. We found that low-order Markov predictors performed as well or better than the more complex and more space-consuming compression-based predictors. Predictors of both families fail to make a prediction when the recent context has not been previously seen. To overcome this drawback, we added a simple fallback feature to each predictor and found that it significantly enhanced its accuracy in exchange for modest effort. Thus the Order-2 Markov predictor with fallback was the best predictor we studied, obtaining a median accuracy of about 72% for users with long trace lengths. We also investigated a simplification of the Markov predictors, where the prediction is based not on the most frequently seen context in the past, but the most recent, resulting in significant space and computational savings. We found that Markov predictors with this recency semantics can rival the accuracy of standard Markov predictors in some cases. Finally, we considered several seemingly obvious enhancements, such as smarter tie-breaking and aging of context information, and discovered that they had little effect on accuracy. The paper ends with a discussion and suggestions for further work.

Objective To estimate the risk of lung cancer associated with the use of different types of coal for household cooking and heating.Setting Xuanwei County, Yunnan Province, China.Design Retrospective cohort study (follow-up 1976-96) comparing mortality from lung cancer between lifelong users of "smoky coal" (bituminous) and "smokeless coal" (anthracite).Participants 27 310 individuals using smoky coal and 9962 individuals using smokeless coal during their entire life.Main outcome measures Primary outcomes were absolute and relative risk of death from lung cancer among users of different types of coal. Unadjusted survival analysis was used to estimate the absolute risk of lung cancer, while Cox regression models compared mortality hazards for lung cancer between smoky and smokeless coal users.Results Lung cancer mortality was substantially higher among users of smoky coal than users of smokeless coal. The absolute risks of lung cancer death before 70 years of age for men and women using smoky coal were 18% and 20%, respectively, compared with less than 0.5% among smokeless coal users of both sexes. Lung cancer alone accounted for about 40% of all deaths before age 60 among individuals using smoky coal. Compared with smokeless coal, use of smoky coal was associated with an increased risk of lung cancer death (for men, hazard ratio 36 (95% confidence interval 20 to 65); for women, 99 (37 to 266)). ConclusionsIn Xuanwei, the domestic use of smoky coal is associated with a substantial increase in the absolute lifetime risk of developing lung cancer and is likely to represent one of the strongest effects of environmental pollution reported for cancer risk. Use of less carcinogenic types of coal could translate to a substantial reduction of lung cancer risk.

We consider here scalar aggregation queries in databases that may violate a given set of functional dependencies. We deÿne consistent answers to such queries to be greatest-lowest/leastupper bounds on the value of the scalar function across all (minimal) repairs of the database. We show how to compute such answers. We provide a complete characterization of the computational complexity of this problem. We also show how tractability can be improved in several special cases (one involves a novel application of Boyce-Codd Normal Form) and present a practical hybrid query evaluation method.