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While particle-resolved methods have substantial benefits for highly detailed simulations, these techniques suffer from high computational cost, motivating efforts to improve their algorithmic efficiency.
Altogether, these methods have substantial limitations in terms of large-scale field application and may raise ethical concerns, especially for human landing catches.
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When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels = 24 m; StreetMap USA = 28 m; TIGER = 37 m).
In addition, computer simulations investigating the performance of methods in detecting selective loci under divergent selection with markers such as AFLPs shows that, despite the methods having substantial uncertainty, the average distance between detected outlier markers and true selective loci ranges between 7 and 18 cM [ 68], in agreement with empirical observations.
This method has substantial limitations since the manufacturing capacity is restricted by the availability of eggs, which may be insufficient to meet the urgent requirements for vaccine during a pandemic [1], [2].
From a computational standpoint, the L1 method has substantial advantages over the random permutation method (beginning with the uncertainty of how many genes to sample at a time in the random permutation/bootstrap method) and is likely to become even more valuable when larger data sets involving more individuals and more irrelevant features (larger CpG arrays) become available.
For all 5 processes in Table 1, a sizeable core of genes is identified by all three methods, but the different methods also have substantial idiosyncrasies.
Recently, sparse reconstruction methods have attracted substantial attention because the signals impinging on an array are intrinsically sparse in the spatial domain [4, 5].
During this period, ex situ surface analysis methods have made substantial progress and new in situ methods for the study of passive films with atomic resolution have been introduced, giving real time information on film chemistry and growth.
More recently, Bayesian phylogeographic methods have generated substantial interest [19], [20], though criticisms of such approaches also exist [21].
For instance, Tu et al used empirical results from periodontal research to demonstrate that different statistical methods have a substantial impact on study power.
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