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Reported system will form the basis for the advanced real-time multiphase fluid composition monitoring platform.
Our research has shown that short-term plant composition monitoring is a necessary but insufficient predictor of long-term restoration success.
Composition monitoring and control play an essential role during a batch distillation cycle, but on-line composition analyzers are expensive, difficult to maintain and give delayed responses.
Body composition monitoring (BCM) is currently used mainly for assessing overhydratation in hemodialysis patients, but it also offers the possibility of evaluating nutrition status.
Long-term and short-term water composition monitoring research was carried out within a purple soil watershed in China's Sichuan Province.
We propose that vegetation composition monitoring be combined with one or more ecological process indicators reflecting changes in three fundamental ecosystem attributes on which restoration success depends: soil and site stability, hydrologic function and biotic integrity.
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Body composition measurement was carried out using a body composition monitor (Fresenius Medical Care, Bad Homburg (vor der Höhe), Germany).
The soil must be weeded and irrigated, its chemical composition monitored to keep acidity balanced, and insects and fungi must be warded off.
The ability of L. plantarum to survive transit through the goat gastrointestinal tract and to modulate selected constituents of the gut microbiota composition, monitored at faecal level was assessed.
To evaluate whether body composition monitor (BCM) could be a practical instrument for nephrologists to assess nutritional status in patients on hemodialysis (HD) and whether it is more effective in identifying patients at highest risk of developing protein-energy wasting (PEW) alone or in combination with other tools currently used for that purpose.
The methods were based on multivariate models using either (1) fatty acid composition monitored by GC-FID or (2) fluorescence landscape signals analysed using the PARAFAC model and in both cases predicting dioxin content as pg PCDD/F TEQ-WHO/g lipid.
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