3,352 research outputs found
Condensate wave function and elementary excitations of bosonic polar molecules: beyond the first Born approximation
We investigate the condensate wave function and elementary excitations of
strongly interacting bosonic polar molecules in a harmonic trap, treating the
scattering amplitude beyond the standard first Born approximation (FBA). By
using an appropriate trial wave function in the variational method, effects of
the leading order correction beyond the FBA have been investigated and shown to
be significantly enhanced when the system is close to the phase boundary of
collapse. How such leading order effect of going beyond the FBA can be observed
in a realistic experiment is also discussed.Comment: 7 pages, 4 figure
Biodiversity shapes tree species aggregations in tropical forests
Spatial patterns of conspecific trees are considered as the consequences of biological interactions and environmental influences. They also reflect species interactions in plant communities. However, biological attributes are often neglected while deliberating the factors shaping species distributions. As rising attentions are paid to spatial patterns of tropical forest trees, we noticed that seven Center of Tropical Forest Sites and four Forest Dynamic Plots in Asia and America have presented analogously high proportions of species with aggregated conspecific individuals coincidently. This phenomenon is distinctive and repudiates fundamental ecology hypotheses which suggested dispersed distributions of conspecific tropical trees due to intensive density and natural enemy pressures in tropical forests. We believe that similar aggregation patterns shared by these tropical forests implies the existence of structuring forces in biogeographical scale instead of habitat heterogeneity in local community scales as scientists have considered. To approach the factors contributing to this cross-continent spatial pattern of trees, we obtained and reviewed ecosystem attributes, including topography, temperature, precipitation, biodiversity, density, and biomass, of these forests. Here we show that the proportions of aggregated species are actually constants independent of any ecosystem attributes regardless the nature of these tropical forests. However, local biodiversity are the major factor determining the number of aggregated species and the aggregation of large individuals of these forests. Aggregation of large trees declines along rising biodiversity, while the numbers of aggregated species increase permanently along lifting biodiversity. We propose a possible equilibrium and saturated status of the tropical forests in accommodating aggregated species. Furthermore, the tight correlations of biodiversity and species aggregation strongly imply the importance of overlooked biological interactions in shaping the spatial patterns in the tropical forests
Privacy Preserving Utility Mining: A Survey
In big data era, the collected data usually contains rich information and
hidden knowledge. Utility-oriented pattern mining and analytics have shown a
powerful ability to explore these ubiquitous data, which may be collected from
various fields and applications, such as market basket analysis, retail,
click-stream analysis, medical analysis, and bioinformatics. However, analysis
of these data with sensitive private information raises privacy concerns. To
achieve better trade-off between utility maximizing and privacy preserving,
Privacy-Preserving Utility Mining (PPUM) has become a critical issue in recent
years. In this paper, we provide a comprehensive overview of PPUM. We first
present the background of utility mining, privacy-preserving data mining and
PPUM, then introduce the related preliminaries and problem formulation of PPUM,
as well as some key evaluation criteria for PPUM. In particular, we present and
discuss the current state-of-the-art PPUM algorithms, as well as their
advantages and deficiencies in detail. Finally, we highlight and discuss some
technical challenges and open directions for future research on PPUM.Comment: 2018 IEEE International Conference on Big Data, 10 page
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