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In the present paper we like to demonstrate an advanced culture technique, which allows to generate tubular elements derived from renal stem cells.
For complete morphometry, we suggest 22 parameters and statistical approach, which allows to generate 12 parameters based on regression analysis of already measured 10 parameters from anteroposterior (AP) radiographic projection.
A decomposed modelling approach with separate energy-flow, energy-integration and economic models is presented and coupled to multi-objective optimisation, which allows to generate a set of optimal process flowsheets that constitute a sound basis for the synthesis of a viable process.
Extensions of our model, which allows to generate directed networks with a tunable power-law exponents and some other interesting properties, will be discussed in "Model modifications" section.
The prototype of the interface has been implemented using the Axure prototyping tool which allows to generate an interactive and responsive interface which can be run as the web application within the application of choice.
To identify the trend of the power consumption for a server, we adopted the lookbusyd software tool, which allows to generate synthetic workload on a server in a tractable way, based on a wide set of parameters (e.g. CPU usage, memory usage, IO operations, etc).
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We present a couple of programs (over C and Mathematica) which allow to generate the syntactic and the semantics representations of a ROSA (ReasoningOnStochasticAlgebras) process.
As an alternative to such derivations, we present here simulation methods which allow to generate stochastic approximations of statistical distributions.
In addition to the canonical Csnk2b, Ly6g5 and Csnk2b-Ly6g5b transcripts with a coherent ORF, other transcripts detected in our study present exon skipping as well as intron retention events which allow to generate, assuming that all these transcripts could be translated into protein by using canonical start codon, truncated or aberrant proteins.
A unique feature of auxin is its tightly regulated cell-to-cell polar transport, which allows auxin to generate gradients and maxima in a particular tissue and contribute to tissue patterning in a dose-dependent manner (Peer et al., 2011).
First, PSM is used to extend the training data space, which allows us to generate ideal strong classifiers without having to collect a large number of training samples.
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