The classic problem of finding the shortest path over a network has been the target of many research efforts over the years. These research efforts have resulted in a number of different algorithms and a considerable amount of empirical findings with respect to performance. Unfortunately, prior research does not provide a clear direction for choosing an algorithm when one faces the problem of computing shortest paths on real road networks. Most of the computational testing on shortest path algorithms has been based on randomly generated networks, which may not have the characteristics of real road networks. In this paper, we provide an objective evaluation of 15 shortest path algorithms using a variety of real road networks. Based on the evaluation, a set of recommended algorithms for computing shortest paths on real road networks is identified. This evaluation should be particularly useful to researchers and practitioners in operations research, management science, transportation, and Geographic Information Systems.

The assessment of personal exposure to air pollution is a critical component of epidemiological studies associating air pollution and health effects. This paper critically reviewed 157 studies over 29 years that utilized one of five categories of exposure methods (proximity, air dispersion, hybrid, human inhalation, and biomarkers). Proximity models were found to be a questionable technique as they assume that closer proximity equates to greater exposure. Inhalation models and biomarker estimates were the most effective in assessing personal exposure, but are often cost prohibitive for large study populations. This review suggests that: (i) factors such as uncertainty, validity, data availability, and transferability related to exposure assessment methods should be considered when selecting a model; and (ii) although an entirely discreet new class of approach is not necessary, significant progress could be made through the development of a 'hybrid' model utilizing the strengths of several existing methods. Future work should systematically evaluate the performance of hybrid models compared to other individual exposure assessment methods utilizing geospatial information technologies (e.g. geographic information systems (GIS) and remote sensing (RS)) to more robustly refine estimates of ambient exposure and quantify the linkages and differences between outdoor, indoor and personal exposure estimates.

In this work, we report the simple solid-state formation of porous Co3O4 with a hexagonal sheetlike structure. The synthesis is based on controlled thermal oxidative decomposition and recrystallization of precursor Co(OH)2 hexagonal nanosheets. After thermal treatment, the hexagonal sheetlike morphology can be completely preserved, despite the fact that there is a volume contraction accompanying the process: Co(OH)2-->Co3O4. Because of the intrinsic crystal contraction, a highly porous structure of the product is simultaneously created. Importantly, when evaluated as electrode materials for lithium-ion batteries, the as-prepared porous Co3O4 nanosheets exhibit superior Li-battery performance with good cycle life and high capacity (1450 mAh g(-1)) due to their porous sheetlike structure and small size. As far as we know, the performance of the Co3O4-based anode materials for lithium batteries presented here is the best up to now. Considering the improved performance and cost-effective synthesis, the as-prepared porous Co3O4 nanosheets might be suitable as anode electrodes for next-generation lithium-ion batteries.

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