Can 3D imaging and digital software increase the ability to predict dental arch form after orthodontic treatment?

Introduction: This study aimed to evaluate the ability of dental clinicians to predict posttreatment dental arch forms in patients with malocclusion with the aid of 3D imaging and digital software in comparison with a conventional method. Methods: Pretreatment and posttreatment dental plaster casts of 100 patients (200 maxillary models and 200 mandibular models) were selected. Three orthodontists selected the best-fitted archwires among 5 commercially available preformed nickel-titanium archwires using 2 methods. In the conventional method, they fit the archwires to pretreatment casts, and in the digital method, they fit the scanned wire to a 3D digital model, using Ortho-Aid, a locally developed 3D software, using clinical bracket points as reference for wire fitness. The predicted posttreatment archwire in each method was compared with the best-fit archwire on the actual posttreatment model of each patient in both methods, and the level of agreement was calculated. The interobserver agreement between the 3 orthodontists in each method was evaluated using intraclass correlation coefficient and the Dahlberg formula. Results: Orthodontists predicted the final treatment outcome in 50% of cases using the conventional method and 58% using the digital method. However, the range of method error was significantly higher in the conventional method (0.425-3.853 mm for the conventional vs 0.451-0.584 mm for the digital). Conclusions: Although the clinicians' ability to predict the final dental arch form after orthodontic treatment and the agreement between clinicians increased by the use of digital equipment, orthodontists can predict the final arch form in about 60% of patients

Climate change impact on wave energy in the Persian Gulf

Excessive usage of fossil fuels and high emission of greenhouse gases have increased the earth’s temperature, and consequently have changed the patterns of natural phenomena such as wind speed, wave height, etc. Renewable energy resources are ideal alternatives to reduce the negative effects of increasing greenhouse gases emission and climate change. However, these energy sources are also sensitive to changing climate. In this study, the effect of climate change on wave energy in the Persian Gulf is investigated. For this purpose, future wind data obtained from CGCM3.1 model were downscaled using a hybrid approach and modification factors were computed based on local wind data (ECMWF) and applied to control and future CGCM3.1 wind data. Downscaled wind data was used to generate the wave characteristics in the future based on A2, B1, and A1B scenarios, while ECMWF wind field was used to generate the wave characteristics in the control period. The results of these two 30-yearly wave modelings using SWAN model showed that the average wave power changes slightly in the future. Assessment of wave power spatial distribution showed that the reduction of the average wave power is more in the middle parts of the Persian Gulf. Investigation of wave power distribution in two coastal stations (Boushehr and Assalouyeh ports) indicated that the annual wave energy will decrease in both stations while the wave power distribution for different intervals of significant wave height and peak period will also change in Assalouyeh according to all scenarios.Full Tex