In addition, it is known that auto-correlated sequences such as oligo(U) show increased variance, i.e. there is a higher probability of observing higher or lower word counts than expected [ 30].
We also observed a higher probability of transition from employment to unemployment for both genders residing in territories that are the most disadvantaged in terms of GDP per capita compared to people who live in the most economically advanced areas.
We observed a higher probability of being hospitalized among those who reported using energy healing, chiropractic, relaxation, or massage therapies.
We observed a higher probability of hip fracture surgery within 48 h during Period 2 than during Period 1 by hospital payment type (local health unit: adjusted RR = 2.07, p < 0.001; public and teaching hospitals: adjusted RR = 1.42, p < 0.001; classified hospitals: adjusted RR = 2.00, p < 0.001; private hospitals: adjusted RR = 2.80, p < 0.001).
Health facility delivery was strongly correlated to the type of attendant at birth (Pearson's coefficient = 0.95, 95% CI: 93-97) and we observed a higher probability of facility delivery among nulliparous mothers (48%) compared to multiparous mothers (33%) with a RR = 1.25 (95% CI: 1.1-1.45).
Additionally, we observe a higher probability of transitioning from employment to unemployment for workers of both genders residing in the most disadvantaged regions in terms of GDP per capita (second plot of the first rows of Figs. 8 and 9) compared to people who live in the richest areas.
Values exceeding 0.5 indicate that, in that week, we are observing a higher probability of being in an epidemic phase than of being in a non-epidemic one, and so an alarm could be triggered if considered necessary.
We also experimentally observed the highest probability to pattern homogeneous droplets at the reservoir concentration of 1.0×105 cells/ml.
The calculated time depends upon the probability of observing high energy levels.
However, the proportion is usually unknown in practice, making it difficult to determine the optimal R and G parameters.> -wrap-foot> positivetive prediction value, NPV negative prediction value In scenario F, poorer prediction performances of all algorithms were observed due to the higher probabilities set for u10 = u01 in scenario 6.
