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For the demonstration, we use the RoSAS business scenario presented in this book.
In our demonstration we use Panda to integrate, process, and analyze actual education data from multiple sources.
As a demonstration, we use perspiration prediction as a case to elaborate the health analysis and prediction in the long term care environment.
For demonstration, we use a simple packet loss model on link :, where is the distance between and, and is the maximum transmission range.
In a first demonstration, we use the system for imaging human skin at an A-scan rate of 109 kHz.
For this demonstration, we use example data downloaded from the Gene Expression Omnibus database (Edgar et al., 2002, GSE10364).
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In the previous demonstration we used acoustic trapping as a useful tool for confining and concentrating particles, which strongly enhances the applicability of optical trapping with our macro-tweezers setup for practical purposes.
As an application demonstration, we used the information of link flow sources and composition to quantitatively identify the impact area of a road closure.
As a demonstration, we used NextBio to detect and explore the biology of brown fat, to compare its expression profile to those of other tissues and cell types, and to discover connectivities with different disease states and chemical and genetic perturbations.
For this demonstration, we used normal PBMC derived DNA template and normalised the expression of these 3 target genes to GAPDH.
For example, in our first demonstrations we used CD45 + CD20 + and CD45 + CD3 + to characterize B- and T-cells, respectively, which are examples of Boolean AND logic over two markers, respectively, CD45ANDCD20 and CD45ANDCD3.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com