Sentence examples for min when compared from inspiring English sources

Exact(31)

In addition, a significant decrease in the total analysis time was achieved (from 10 h to 30 min), when compared to the standard method.

The results confirm the thiol ene reaction mechanism showing a very fast cis/trans-isomerization (<1.0 min) when compared with the total disappearance of unsaturations, indicating that the rate-limiting step controlling the reaction is the hydrogen transfer from the thiol involved in the formation of product.

With 22% TETRO showed a significantly higher washout from the LV in the time interval from 10 to 60 min when compared to MIBI (11%, p = 0.004).

In contrast, in the LASP-KD5 cells, there is an apparent increase in basal activation of p130 CAS as observed by an increase in pY249 at 0 min when compared to the non-silencing (ns) control.

Studies with bis-ANS and UVB-exposed ALDH3A1 revealed a decrease of bis-ANS fluorescence in the early stages of exposure (up to 5 min) when compared to the initial degree of bis-ANS fluorescence (Figure 7A).

The product amplified at 58.5°C yielded positive result at 52 min when compared to other temperatures.

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Similar(29)

Unfortunately, we found that too many patients still hesitate to immediately call the EMS, contributing to a delayed symptom-to-diagnosis interval of 38 min when comparing EMS and SHD as the patient's first choice.

Without Bonferroni correction (i.e., p < 0.05), subjects reported significantly greater total symptom severity at 80, 100, 120, and 165 min when comparing the 0.05-ppm to the 5-ppm exposure conditions (not shown).

Cardiorespiratory monitoring was done at baseline, after induction of ALI, and every 30 min up to 120 min. When compared with control animals, PLV resulted in significant better oxygenation, significant lower dead space ventilation, and significant better CO and DO2.

Maximum concentrations after intramuscular application of carbetocin were obtained almost 20 min later when compared to intravenous administration of oxytocin.

The deep learning computer algorithm achieved a best sleep/wake classification accuracy of 96.5%, and sleep episode on/offset detection F1 scores (measuring detection exactness and completeness) of 0.86 and 0.84 with mean errors of 5.0 and 5.5 min respectively, when compared to the labels based on human scored actigraphy with sleep diaries.

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