20 research outputs found

    Assessment of Aesthetic Results of 100 Patients Who Underwent Rhinoplasty - Rhinoplasty Outcome Evaluation

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    Background: To assess the long-term aesthetic results of rhinoplasty and predict the final outcome. Methods: The sample was composed of 100 patients (34 men and 66 women) between 23 and 57 years old (mean, 34.8) operated on exclusively for aesthetic reasons. The time elapsed from the operation ranged from 3 to 13 years with a mean of 6.8 years. The study used Rhinoplasty Outcome Evaluation questionnaire, a simple, reliable, validated, and widely used inventory. Results: The vast majority of patients (93%) were satisfied postoperatively with scores > 50% (67 patients had scores > 80%). Only 7 patients had scores less than 50%. The mean score was 82.4 ± 1.7% with a median of 87%. In addition, it seems that the results of the operation remain high through time with a small decline along age groups and years elapsed. Women were found more satisfied than men (P = 0.03). Conclusions: The study concludes that the results of aesthetic rhinoplasty, if performed by skilled and experienced surgeons, are very satisfying and stable throughout time. © 2017 The Authors

    The causal nexus of government spending and revenue in Finland: a bootstrap approach

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    Applying VAR(5), a bootstrap simulation approach and a multivariate Rao's F-test indicate that government revenue Granger-causes spending in Finland. This does not agree with Barr's tax smoothing hypothesis. This explanation of this is due to the institutional factors that are specific for Finland.

    Time-varying causality between research output and economic growth in US

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    This main purpose of this paper is to investigate the causal relationship between knowledge (research output) and economic growth in US over 1981–2011. To overcome the issues of ignoring possible instability and hence, falsely assuming a constant relationship through the years, we use bootstrapped Granger non-causality tests with fixedsize rolling-window to analyze time-varying causal links between two series. Instead of just performing causality tests on the full sample which assumes a single causality relationship, we also perform Granger causality tests on the rolling sub-samples with a fixedwindow size. Unlike the full-sample Granger causality test, this method allows us to capture any structural shifts in the model, as well as, the evolution of causal relationships between sub-periods, with the bootstrapping approach controlling for small-sample bias. Full-sample bootstrap causality tests reveal no causal relationship between research and growth in the US. Further, parameter stability tests indicate that there were structural shifts in the relationship, and hence, we cannot entirely rely on full-sample results. The bootstrap rolling-window causality tests show that during the sub-periods of 2003–2005 and 2009, GDP Granger caused research output; while in 2010, the causality ran in the opposite direction. Using a two-state regime switching vector smooth autoregressive model, we find unidirectional Granger causality from research output to GDP in the full sample.http://link.springer.com/journal/11192hb201
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