Sweeteners are compounds that give the sweet taste to foods, drinks and drugs. Aspartame is one of the most used today; its metabolism produces phenylalanine, aspartic acid and methanol. The purpose of this research was to review the scientific literature about the levels of consumption considered safe, toxicology and epidemiological data of aspartame. The European Parliament approved it as a food additive in 1994 and the FDA did it in 1996. Joint FAO / WHO Expert Committee on Food Additives and FDA set the Acceptable Daily Intake at 40 and 50 mg / kg bw / day, respectively. The sweetener and its degradation products have been evaluated for over 30 years with the involvement of numerous international organizations. However, there is still controversy over its use because there are researches whose results attribute to it neuropsychiatric side effects, brain tumors, carcinogenic properties for different organs, damage to the fetus during pregnancy, development of lymphomas and leukemia, while other researchers say their use is harmless to humans if consumption is less than the Acceptable Daily Intake. It is not recommended for people with phenylketonuria and pregnant women.

The relationship between color development with anthocyanins and chlorophyll content at different stages of maturity of mortiño (Vaccinum floribundum) was studied. The fruits were harvested by surface color from 100% green to 100% black. The color scale was measured according to CIE L* a* b* and color difference (∆E) was determined. The anthocyanin and chlorophyll content was performed by UV-VIS spectrophotometry. The following scale was used to establish the stage of maturity: (1) green, (2) green/pink, (3) pink, (4) pink/black and (5) black; It was observed that increasing the maturation stage, the brightness and color saturation decrease. Results showed positive values of a* and negative of b* for maturity stages 3, 4 and 5 (red and blue); and negative values ​​of a * and positive of b * for states 1 and 2 (green and yellow). Smallest differences in color (∆E) were found between states 4 and 5. Among the states 1 and 5 was evident a decreased of 0,052 mg/g in chlorophyll content and an increase of 13700mg/kg in anthocyanins. The degree of maturity of the fruit has a direct relationship between the color tone and content of components with antioxidant activity constituting a precedent for future researches and its use of this fruit in different stages of maturity.

The environment is still affected by the inappropriate use of organic matter waste, but a culture of recycling and reuse has been promoted in Ecuador to reduce carbon footprint. The composting, a technique to digest organic matter, which traditionally takes 16-24 weeks, is still inefficient to use. Therefore, this paper concerns the optimization of the composting process in both quality and production time. The variables studied were: type of waste (fruits and vegetables) and type of bioaccelerator (yeast and indigenous microorganisms). By using a full factorial random design 22, a quality compost was obtained in 7 weeks of processing. Quality factors as temperature, density, moisture content, pH and carbon-nitrogen ratio allowed the best conditions for composting in the San Gabriel del Baba community (Santo Domingo de los Colorados, Ecuador). As a result of this study, a mathematical surface model which explains the relationship between the temperature and the digestion time of organic matter was obtained.

In this paper a review and analysis of the major theories and models that address the prediction of corporate bankruptcy and insolvency is made. Neural networks are a tool of most recent appearance, although in recent years have received considerable attention from the academic and professional world, and have started to be implemented in different models testing organizations insolvency based on neural computation. The purpose of this paper is to yield evidence of the usefulness of Artificial Neural Networks in the problem of bankruptcy prediction insolence or so compare its predictive ability with the methods commonly used in that context. The findings suggest that high predictive capabilities can be achieved using artificial neural networks, with qualitative and quantitative variables.