Background: An accurate understanding of co-occurrence and comorbidity of alcohol use disorders (AUD) in Colombia is crucial for public health. Objective: A secondary analysis was conducted, using a 2003/2004 government´s population database to determine the lifetime associations between AUD and other mental and addictive disorders in people of Colombia aged 18-65 years. Methods: Several statistical analysis were performed: testing prevalence difference in mental disorders by whether the individual had an AUD; a stratified analysis by gender and logistic regression analyses accounting for differences in demographic, socio-economic, behavioral and self-reported health status variables. Results: People with AUD comprised 9% of the population, of which 88% were males and on average 37 years old. They were more likely to be males, be working, and be current smokers; and less likely to be at home or retired. The population with AUD had greater chance to comply with criteria for all disorders but minor depressive disorder, post-traumatic stress disorder, nicotine dependence, and oppositional defiant disorder. Conclusion: This study demonstrates a high prevalence of mental disorders in the adult population with AUD in Colombia. The findings highlight the importance of comorbidity as a sign of disease severity and impact on public health and supports the need for training of more professionals and developing appropriate interventions and services.

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Mesoamerica and the Caribbean are low-latitude regions at risk for the effects of climate change. Global climate models provide large-scale assessment of climate drivers, but, at a horizontal resolution of 100 km, cannot resolve the effects of topography and land use as they impact the local temperature and precipitation that are keys to climate impacts. We developed a robust dynamical downscaling strategy that used the WRF regional climate model to downscale at 4 -12 km resolution GCM results. Model verification demonstrates the need for such resolution of topography in order to properly simulate temperatures. Precipitation is more difficult to evaluate, being highly variable in time and space. Overall, a 36 km resolution is inadequate; 12 km appears reasonable, especially in regions of low topography, but the 4 km resolution provides the best match with observations. This represents a tradeoff between model resolution and the computational effort R. Oglesby et al. 203needed to make simulations. A key goal is to provide climate change specialists in each country with the information they need to evaluate possible future climate change impacts.

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This paper presents a virtual laboratory for the computer processing of digital imaging. This software application is designed to enhance/reconstruct high-resolution images in order to analyze the implemented algorithms as well as their optical features. The application is conceived as a virtual laboratory for mechatronic, biomedical and electronic engineering students. The presented case studies demonstrate the accuracy of the processing chain used in this virtual laboratory, and how the students could better understand topics related to remote sensing, computer vision, biomedical engineering, among others.

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