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As a result, the peculiarity of adsorptive interaction between system components was uncovered.
In the clinical experiments, safety of the various system components was demonstrated and partograms were compared to manual measurements.
First, addressing the need for integrated urban modeling approaches, a Mixed Integer Linear Programing (MILP) optimization model representing both urban and energy system components was developed.
The renal gene expression of the renin angiotensin system components was also evaluated, aiming to find some correlation between salt intake, sodium homeostasis and blood pressure increase.
One follows a simple system selection approach where no formal consideration on the dependencies between the system components was considered (non-causal approach).
In this study, the whole life cycle ("cradle to grave") of the system components was extended only up to the use phase of the system and especially for a period of 20 years.
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Furthermore, system components are often distributed over multiple physical locations, hardware platforms and communication networks.
All system components are controlled by Python scripts and generic microcontrollers that together enable the system to function completely autonomously.
If the interactions between the system components are short-ranged, the dynamics are well understood and relatively straightforward to compute.
When system components are physically apart, this assumption becomes inappropriate.
Initially the system components are described behaviorally as ideal elements.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com