public SamplingType() Deprecated Use the fromString(String name) factory method. Creates a new instance of SamplingType value.Method Details fromString public static SamplingType fromString(String name) Creates or finds a SamplingType from its string representation. Parameters: name - a name to ...
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Past efforts at neuronal classification were hindered by severe biases and under-sampling, but newly developed high-throughput techniques allow this limitation to be circumvented. For some regions of the central nervous system, particularly the retina and cerebral cortex, a complete cell census appears...
294–297 Enhanced sampling methods (with controlled error estimates) will help both proliferate and standardize the results of enhanced sampling methods.298 In this respect, machine learned potentials offer an opportunity for improved statistics, although sampling in and around transitions states is still...
A complete description of the different particle production methods is beyond the scope of the present chapter, but most of the techniques can be classified as being either a direct dual-supply method or an indirect template-assisted method [32]. In the direct dual-supply method, the Janus par...
The XMLType resulting from applying an XPath through extract() need not be a well-formed XML document but can contain a set of nodes or simple scalar data. You can use the getStringVal() or getNumberVal() methods on XMLType to extract the scalar data. For example, the XPath expression...
Creates a new instance of CredentialsType value.Method Details fromString public static CredentialsType fromString(String name) Creates or finds a CredentialsType from its string representation. Parameters: name - a name to look for. Returns: the corresponding CredentialsType.values...
Figure 3. (a) Geological map of the Dapai Fe polymetallic deposit (modified from Feng et al., 2015); and (b–d) simplified cross-sections and drill-core log of Dapai showing the occurrence of the Pb–Zn–Cu–Fe–Mo orebodies and ore-related granites and sampling location. DownLoad: ...
Our results demonstrate the importance of sampling large numbers of loci, each of which has a sufficient number of sites to provide robust estimates of gene trees. Low-coverage whole genome sequencing, as we did here, represents a cost-effective means to generate the very large data sets that...
In general, the methods used for the estimation of biasing parameters have been adapted similarly to those used in linear regression models. On the other hand, the use of estimators with two biasing parameters has become increasingly widespread in recent years. However, one of the most important...