Sentence examples for reactivity process from inspiring English sources

The reactivity process involves an interaction between CaCl2 (calcium chloride) and sodium alginate whose potential distributions were computed and are shown in Fig. 12a, b respectively.

Moreover, attributed to the chemical reactivity processed by cool flame, the flame propagation of the cases within NTC regime is even faster than those beyond NTC regime.

However, cognitive control and defensive reactivity processes are often studied in isolation and rarely examined in early childhood.

Our findings highlighted the importance of understanding the link between cognitive control and defensive reactivity processes in young children.

Importantly, the primary implication of our findings is that future studies investigating cognitive control and/or defensive reactivity processes should incorporate multiple measures within these constructs of interest.

The use of multiple assessments may help delineate the type of top-down control that is related to regulating defensive reactivity processes.

As cognitive control and defensive reactivity processes co-develop over time, their interaction contributes to a wide range of functional outcomes.

Such an approach also takes advantage of the maturing field of theoretical/computational chemistry in understanding important molecular recognition and reactivity processes (both qualitatively and quantitatively) for chemicals that can underlie their biological/toxicological activity.

Specifically, we assessed two event-related potentials thought to index cognitive control processes – the error-related negativity (ERN) and error positivity (Pe) – measured across two tasks, and two markers of defensive reactivity processes – startle reflex and resting parietal asymmetry – in a sample of 3- to 7-year old children.

Given that individual differences in the ability to engage in these cognitive control processes develop rapidly during early childhood (Diamond, 2013), it is critical that future research examines how these changes interact with ongoing changes in defensive reactivity processes to better understand the underlying dynamics of these major neural networks.

Narrow-cut data were used to develop a generalized feedstock characteristic index, KR, that correlates well with the feedstock hydrocarbon constituents and can be used to assess feedstock reactivity and process capability.