Butt lengths differ by area deprivation level: a field study to explore intensive smoking.

We collected cigarette butts in a range of residential areas, to assess differences in the length of unburnt tobacco in the butts, and in proportions of roll-your-own (RYO) cigarettes. Two high, two medium, and two low deprivation areas, as classified by deciles of the New Zealand Deprivation Index, were selected for the Wellington region. Collected butts were systematically classified and measured. A mixed model of analysis, treating location clusters nested within deprivation level areas as a random effect, was used to assess differences in mean length of unburnt tobacco in the butts. A total of 6,262 cigarette butts and separate filters were collected, of which 3,509 (56.0%) were measurable manufactured cigarette butts, 1,069 were unmeasurable manufactured butts, 1,450 were RYO butts, and 236 were RYO filters. The RYO butts were not measured because of the extent of their degradation. The unburnt tobacco lengths in manufactured cigarette butts were significantly shorter in the most deprived areas, relative to the least deprived areas (p = .035). Deformed manufactured cigarette butts (i.e., that potentially were stubbed out) showed the same pattern (p = .011 between the most and least deprived areas). We found no significant difference between deprivation areas in the proportion of RYO material found. The shorter mean unburnt tobacco length in the most deprived areas is consistent with more intensive smoking among smokers in those areas. This finding is consistent with other evidence of increased price sensitivity among poorer smokers, and with basic economic theory. Further evidence on observed smoking behavior in the field is necessary to better interpret these preliminary findings.     

Phonon Scattering and Thermal Conductivity in p‐Type Nanostructured PbTe‐BaTe Bulk Thermoelectric Materials

Transmission electron microscopy studies show that a PbTe‐BaTe bulk thermoelectric system represents the coexistence of solid solution and nanoscale BaTe precipitates. The observed significant reduction in the thermal conductivity is attributed to the enhanced phonon scattering by the combination of substitutional point defects in the solid solution and the presence of high spatial density of nanoscale precipitates. In order to differentiate the role of nanoscale precipitates and point defects in reducing lattice thermal conductivity, a modified Callaway model is proposed, which highlights the contribution of point defect scattering due to solid solution in addition to that of other relevant microstructural constituents. Calculations indicate that in addition to a 60% reduction in lattice thermal conductivity by nanostructures, point defects are responsible for about 20% more reduction and the remaining reduction is contributed by the collective of dislocation and strain scattering. These results underscore the need for tailoring integrated length‐scales for enhanced heat‐carrying phonon scattering in high performance thermoelectrics.     

Surface chemistry of carbon nanotubes impacts the growth and expression of water channel protein in tomato plants

Specific properties of carbon nanotubes, such as their level of agglomeration in the medium and their surface characteristics, can be critical for the physiological response of plants upon application of carbon nanotubes. The correlations among the level of aggregation, the type of functional group on the surface of the carbon nanotubes, and the growth performance of tomato plants are documented.     

Multi-objective optimization based privacy preserving distributed data mining in Peer-to-Peer networks

This paper proposes a scalable, local privacy-preserving algorithm for distributed Peer-to-Peer (P2P) data aggregation useful for many advanced data mining/analysis tasks such as average/sum computation, decision tree induction, feature selection, and more. Unlike most multi-party privacy-preserving data mining algorithms, this approach works in an asynchronous manner through local interactions and it is highly scalable. It particularly deals with the distributed computation of the sum of a set of numbers stored at different peers in a P2P network in the context of a P2P web mining application. The proposed optimization-based privacy-preserving technique for computing the sum allows different peers to specify different privacy requirements without having to adhere to a global set of parameters for the chosen privacy model. Since distributed sum computation is a frequently used primitive, the proposed approach is likely to have significant impact on many data mining tasks such as multi-party privacy-preserving clustering, frequent itemset mining, and statistical aggregate computation.