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The details of convolution will be explained in a short review of the physical principle of the methods that can estimate the reservoir properties based on the multiple flow periods being the principle of superposition.
The guiding principle of the methods is to represent the evolution of a forest ecosystem subject to various impact variables, such as prices and catastrophic disturbances, with Markov chains: probability matrices describing the frequencies of transition of each variable between discrete states.
Here, we summarize these methods for the identification of motif-based interactions (Fig. 1, Table 2); we introduce the basic principle of the methods and highlight recent advances in high-throughput analysis of domain-motif interactions.
The principle of the methods in developing non-genic diagnostic markers through whole genome sequencing and re-sequencing seen in this study is the same as that for DNA fingerprinting and genetic mapping in other crops, such as the SSR marker Xgwm382 for yellow rust disease resistance [ 13, 65] and a sequence-tagged microsatellite marker stem rust disease resistance gene Sr2 [ 66, 67] in wheat.
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A description of the principle of the method is provided.
We start by describing the principle of the method as shown in Fig. 1; it is fundamentally analogous to that of regular laboratory-based XCT.
The principle of the method implies that malignant structures are harder than benign ones.
The principle of the method and a brief survey of the relevant literature are presented.
The principle of the method comprises the calculation of semi-analytical response of a rectilinear reservoir with closed outer boundaries.
The underlying principle of the method is digitisation of the particles and packing space, enabling the generation of realistic structures.
The principle of the method is explained, details of the instrument are provided and the analytical procedure is described.
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