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Such applications arise, for example, in experimental physics, where the data in question is generated by accelerators, and in simulation science, where the data is generated by supercomputers.
With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.
For example, in experimental environments, children initially reorient themselves mainly by using geometric information, while the ability to use landmark information develops later in life [36], [37].
For example, in Experimental Applications II and III, our analyses based on SWISS agreed with results found in the literature, such as Affymetrix having the best intersite reproducibility [23] and one lane of RNA-Seq being comparable to a single gene expression microarray [27].
For example, in experimental mice, brief exposure to light during the night rapidly increases the expression of the core clock genes Per1-2 and their protein products [ 15].
For example, in experimental models the transfer of regulatory cells can prevent arthritis [ 52], while the depletion of said cells results in accelerated disease [ 53].
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Referring to several examples in experimental studies [24] [29], Speed [23] suggested that a stable attack number greater than 0 on a defended prey is rather common.
For example, studies in experimental animals show that disruption of astrocyte-specific Na+,K+-ATPase results in increased anxiety-related behavior and impaired spatial learning in mice [ 154], and that astrocyte influences on synaptic functions are important in reward circuits, and may contribute to drug addiction [ 145].
For example, in an experimental treatment for chronic lymphocytic leukemia, researchers designed a virus to induce the expression on patient T cells of antibody receptors that identified and attached to antigens on malignant B cells and that activated the T cells, prompting them to destroy the B cells.
Finally, the proposed approach is illustrated by an attitude estimation example in an experimental case of noisy measurements which shows the efficiency of the proposed algorithm.
For example, in their experimental paper, De Arcangelis et al. (2015) find that additional remitting due to education labels largely occurs within the most closely connected household in the Philippines.
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