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In addition to improving antimicrobial use and patient care (including tracking of antibiotic resistance patterns), such systems can improve surveillance of hospital-acquired infections and adverse drug events when compared to manual surveillance methods [ 30, 31].
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The virtually infinite variety of behavior patterns of such systems due to control inputs and environmental influences further complicates system characterization and fault diagnosis.
This paper presents an information-theoretic approach to identification of statistical patterns in such systems, where the main objective is to enhance structural integrity and operation reliability.
Patterns of such systems are mostly host-parasite systems with protozoan parasites or worm parasites.
Our aim is to additionally reason about properties of spatial patterns in such systems, and to quantify how these properties change over time.
The results generally exhibit significant scatter that is attributed to the inherent asymmetry of the deformation pattern in such systems.
The remaining gene neighborhoods were examined for specific template patterns such as TA systems.
This is largely attributable to inheritance of past inequitable systems and allocation patterns that ensued from such systems.
With the help of a high-speed photography system, flow patterns such as bubbly flow, slug flow (including two sub-regimes, Taylor flow and unstable slug flow), slug-annular flow, churn flow and annular flow were observed in these microchannels.
By using a high-speed photography system, flow patterns such as bubbly flow, slug and unstable slug flow, churn flow, slug-annular and annular flow are observed and identified on the flow regime maps.
Yet countries differ in their demographic characteristics, patterns of social contact, healthcare systems, and the cost structure of such systems.
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CEO of Professional Science Editing for Scientists @ prosciediting.com