Sentence examples for term since it from inspiring English sources

That could make Fording vulnerable to further weakness in the short term, since it sells its coking coal directly to the steel industry.”.

However, Dan Berenbaum, a MKM Partners analyst, says Texas Instruments may have a muted appetite in the near term, since it is still digesting its acquisition of National Semiconductor and has been very focused on its analog portfolio.

Orchestration is somewhat the narrower term, since it is frequently used to describe the art of instrumentation as related to the symphony orchestra.

However, cerumen impaction is the preferred term since it is consistently used in clinical practice and in the published literature to describe symptomatic cerumen or cerumen that prevents assessment of the ear.

Reading Smith without studying economics, he said, was like reading Euclid without studying maths.Hayek wrote that liberalism was too confusing a term, since it had different meanings in Victoria's England and Roosevelt's America.

Cutting taxes might have some impact on the supply of gasoline in the long term, since it would increase profits for oil companies, but I think the effect would be marginal at best.

Even though they had avoided the term since its inception, it was at this point the band actively began trying to shed the term "emo", a word that had defined them for years but had come to mean something different.

Congress undoubtedly thought that both groups of aliens, inadmissible aliens at the threshold and criminal aliens under final order of removal, could be constitutionally detained on the same terms, since it provided the authority to detain both groups in the very same statutory provision.

The amount your local authority spends on you on average has fallen by 8.4% in real terms since it reached a peak in 2009/10.

Moreover, as opposed to (2), (5) is formulated in model-theoretic terms, since it incorporates a claim about the nonexistence of a certain model.

The Adaboost may induce overfitting problem when training data include heavy noisy terms, since it explicitly emphasizes data that are difficult to classify [8, 10].