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Comparative studies of these patterns will also be imperative in studying other seasonal disturbances, related to, for example, Easter, Chanukah, or Diwali.
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So, we focus in this study on these patterns of long-range dependence across release years.
The study of these patterns is called technical analysis because it tends to be done with mathematical rigor and considerable agnosticism.
The study of these patterns is the goal of our research, starting with the development of a new detection method based on next-generation sequencing, a Bayesian genotyper, and stringent error filters.
PCA is widely used in dietary studies to describe dietary patterns and to study the associations of these patterns (factors) with health outcome (Kant 2004).
One obstacle to the study of these network patterns is the limited ability to record the participating neurons.
However, there are few detailed, prospective, descriptive data from large studies describing these patterns of use in the critically ill.
Additionally, it would be very interesting to study the development of these patterns and local virus and siRNA levels in time-series.
Further study of the patterns is undergoing.
Although the mechanisms generating plant spatial patterns have been widely studied, few studies concentrated on the consequences of these patterns on belowground macrofauna.
Many studies evaluate the influence of these patterns on biodiversity and assess their contribution to the stability of the ecosystem, but the outcomes are ambiguous and, in parts, contradictory (e.g. Dunne et al. 2002; Vieira and Almeida-Neto 2015).
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