Sentence examples for headspace model from inspiring English sources

The most frequently used experimental approach to hypoxia-induced MTB dormancy is the defined headspace model of non-replicating persistence (NRP) described by Lawrence Wayne and colleagues [17], [30], [31].

It is an expected component of the headspace model of service delivery and staff are provided training in the use of the assessment.

The classical model used to study the physiology of hypoxic non-replicating mycobacteria is the defined headspace model described by Wayne and colleagues.

The concentrations of volatile fatty acids (VFA) and alcohols were also measured using a gas chromatography system GC-20100, Shimadzu, Japan) that was equipped with FID and COMBI-PAL headspace injection (AOC 5000 model) and a HP-INNOWAX column (30 m × 0.25 mm i.d. × 0.25  µm film thickness) [ 26]. Figure 2 shows glucose conversion as a function of the HRT variation in the reactors.

The measured content of oxygen in the headspace was incorporated in the model and the interaction between measured oxygen content in the headspace and the product to headspace volume ratio was found to be crucial.

Carbon dioxide was measured in the headspace using a Shimadzu GC model GC -17A (Shimadzu Scientific Instruments, Columbia, MD), with a thermal conductivity detector and a 168 mm HaySep 100/120 column.

Gas samples were obtained by withdrawing 300 μL of gas from the bottle headspace using a gas-tight syringe (model 1750 Hamilton, Reno, NV).

Hydrogen concentrations in the gas headspace were measured using an SRI Instruments model 310 gas chromatograph (Torrence, CA) equipped with a thermal conductivity detector and molecular sieve column (Alltech Molesieve 5A 80/100) as described previously ([van Ginkel et al., 2001]).

Ethanol analysis of the fermentation broth was carried out using a gas chromatograph (GC, model 7890A, Agilent Technologies) through a headspace sampler (HS, model 7694E, Agilent Technologies) using an external standard for calibration.

A computational methodology was developed incorporating the effects of mixing and headspace pressure to simulate the drying profile using a modified model framework within the Dynochem software.

Real time APCI-MS headspace data may be used to validate mathematical modelling of flavour release.