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BACKGROUND AND OBJECTIVES: A huge number of solutions based on computational systems have been recently developed for the classification of cognitive abnormalities in older people, so that individuals at high risk of developing neurodegenerative diseases, such as Cognitive Impairment and Alzheimer?s disease, can be identified before the manifestation of the diseases. Several factors are related to these pathologies, making the diagnostic process a hard problem to solve. This paper proposes a computational model based on the artificial neural network to classify data patterns of older adults. METHODS: The proposal takes into account the several parameters as diagnostic factors as gender, age, the level of education, study time, and scores from cognitive tests (Mini-Mental State Examination, Semantic Verbal Fluency Test, Clinical Dementia Rating and Ascertaining Dementia). This non-linear regression model is designed to classify healthy and pathological aging with machine learning techniques such as neural networks, random forest, SVM, and stochastic gradient boosting. We deployed a simple linear regression model for the sake of comparison. The primary objective is to use a regression model to analyze the data set aiming to check which parameters are necessary to achieve high accuracy in the diagnosis of neurodegenerative disorders. RESULTS: The analysis demonstrated that the usage of cognitive tests produces median values for the accuracy greater than 90%. The ROC analysis shows that the best sensitivity performance is above 98% and specificity of 96% when the configurations have only cognitive tests. CONCLUSIONS: The presented approach is a valuable tool for identifying patients with dementia or MCI and for supporting the clinician in the diagnostic process, by providing an outstanding support decision tool in the diagnostics of neurodegenerative diseases.

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OBJECTIVE: To analyze venous thrombotic complications in transplanted patients as a function of their body mass index (BMI). MATERIALS AND METHODS: This single-center, observational retrospective study of individuals undergoing liver transplantation between January 2008 and December 2014 analyzed the frequency of pretransplant portal thrombosis, post-transplant venous complications (early and late portal thrombosis), deep vein thrombosis, pulmonary thromboembolism and the survival outcomes as a function of World Health Organization BMI class. RESULTS: Liver transplantation was performed in 208 patients during the study period. No statistically significant differences in study variables were found as a function of BMI in bivariate analyses (P < .05), and Kaplan-Meier survival analysis results were also nonsignificant. CONCLUSION: No differences in the rate of venous thrombotic complications or survival were found as a function of the BMI class of these liver transplant recipients. These findings are in line with previous reports that complication rates are not higher in obese patients and support the proposal that obesity should not be considered a contraindication for liver transplantation based on the risk of venous complications.

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The thermal decomposition of chrome tanned leather before and after a soaking treatment with NaOH was studied using thermogravimetric analysis (TGA). The effect of the solution concentration (0.2M and 0.5M) and the soaking time (5min and 15min) was evaluated. TGA experiments at four heating rates (5, 10, 15 and 20°Cmin(-1)) were run in a nitrogen atmosphere for every treatment condition. A kinetic model was developed considering the effect of the three variables studied, i.e.: the NaOH solution concentration, the soaking time and the heating rate. The proposed model for chrome tanned leather pyrolysis involves a set of four reactions, i.e.: three independent nth order reactions, yielding the corresponding products and one of them undergoing a successive cero order reaction. The model was successfully applied simultaneously to all the experimental data obtained. The evaluation of the kinetic parameters obtained (activation energy, pre-exponential factor and reaction order) allowed a better understanding of the effect of the alkali treatment on these wastes.

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Varnish wastes based on polyurethane were burnt in a laboratory scale furnace at different residence time of gases and temperatures and with a fuel-rich atmosphere and with an excess of oxygen. The yields of CO, CO(2), six light hydrocarbons (methane, ethylene, etc. ) and 31 semivolatile+volatile compounds (benzene, toluene, naphthalene, dibezofuran, etc.) were determined with stoichiometric factors of the oxygen between 0.6 and 0.9, nominal temperatures of the reactor between 750-1050 degrees C and residence times of the volatiles evolved and formed between 2 and 6 s. The collection of the volatiles evolved was carried out with a Tedlar bag and by XAD-4 resin, comparing the data obtained in both cases. The maximum emission factors or yields of volatiles+semivolatiles were obtained at 850-950 degrees C, with values above 0.5% for benzene, naphthalene, acenaphthylene, phenantrene and fluoranthene. The thermal behaviour of different compounds was analysed. Naphthalene, benzene and toluene were also detected in the excess oxygen runs.

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