Growing globally: Is it reasonable for Logoplaste to enter the Colombian rigid plastic packaging market?

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Strategy of Logoplaste in Mozambique's flexible plastic packaging industry

Logoplaste is a specialist in operating in-house industrial sites for manufacturing rigid plastic packaging containers. In developing countries, especially in Africa, the low income of consumers does not allow a widespread adoption of products typically sold in rigid plastic containers. In these countries the flexible packages are usually adopted as they allow for better ratios of cost/litter of product, particularly in smaller packages. Should Logoplaste offer this type of technology in order to expand into developing countries?

Genome-scale metabolic network reconstruction of Polaromonas sp. strain JS666: analysis of cDCE degradation rates and design of experiments for bioremediation improvement

Release of chloroethene compounds into the environment often results in groundwater contamination, which puts people at risk of exposure by drinking contaminated water. cDCE (cis-1,2-dichloroethene) accumulation on subsurface environments is a common environmental problem due to stagnation and partial degradation of other precursor chloroethene species. Polaromonas sp. strain JS666 apparently requires no exotic growth factors to be used as a bioaugmentation agent for aerobic cDCE degradation. Although being the only suitable microorganism found capable of such, further studies are needed for improving the intrinsic bioremediation rates and fully comprehend the metabolic processes involved. In order to do so, a metabolic model, iJS666, was reconstructed from genome annotation and available bibliographic data. FVA (Flux Variability Analysis) and FBA (Flux Balance Analysis) techniques were used to satisfactory validate the predictive capabilities of the iJS666 model. The iJS666 model was able to predict biomass growth for different previously tested conditions, allowed to design key experiments which should be done for further model improvement and, also, produced viable predictions for the use of biostimulant metabolites in the cDCE biodegradation.