Sentence examples for 1 discomfort from inspiring English sources

Table 6 Adverse events Adverse event during treatment Number of episodes Nasal Discomfort/Pain due to catheter 3 Nasal discomfort due to cooling 2 Hypertension 2 Mild epistaxis 1 Discomfort due to excess fluid dripping from nose 2 Adverse Event Following Treatment Transient recurrent sneezing 2 Runny nose 2 Strange taste 1 Strange smell 1 Dry eyes 1 Dizziness 1 Sinus pressure 1.

This yielded two factors which were labelled as follows: Factor 1 – discomfort and distress (8 items; ά = 0.746), and Factor 2 – sociability (3 items; ά = 0.694).

The two factors derived were as follows: Factor 1 – discomfort and distress (9 items; ά = 0.71) and Factor 2 – sociability (2 items; ά = 0.749).

These were labelled as follows: Factor 1 – discomfort and distress (8 items; ά = 0.746); Factor 2 – emotional state (4 items; ά = 0.496); Factor 3 – sociability (2 items; ά = 0.749).

This differed from the two-factor solution for family carers only in that for family carers item 1, 'smiles', loaded onto Factor 1 (discomfort and distress) rather than Factor 2 (sociability).

Multiplying the above frequency score (0, 1.5, 3.5, 5, 10) by the discomfort score (1, 2, 3) and the interference score (1, 2, 3) gives the discomfort score.

For example, during the prime minister's 15 minute party conference speech in 2003 Brown gave off 322 "discomfort tells" including touching his hair, fiddling with his cuffs and looking at the floor.

Lack of privacy 5.4 ± 2.4 1. Lack of moral support 6.1 ± 2.2* Discomfort sources were evaluated by caregivers on a sliding scale, from 0 (not responsible for discomfort) to 10 (responsible for major discomfort).

Previous studies have also shown that migraineurs have lower sound [3] and light [34, 35] discomfort thresholds compared with normal controls.

We studied the performance differences of 3D discomfort prediction models that rely on three disparity calculation algorithms having different complexity levels.

Towards filling these gaps, we begin by studying the performance differences of S3D discomfort prediction models using three nominal disparity algorithms having different levels of complexity.