The temperature influence on the oxidation stability of biodiesel from ternary mixture of vegetable oil and animal fat (50% of soybean oil, 20% of beef tallow, and 30% of poultry fat) was evaluated at temperatures ranging from 110 to 130 °C applying the Arrhenius and Eyring equations. The kinetics and thermodynamics parameters determined, considering first-order reaction rate kinetics, were rate constant (k), varying from 0.5479 to 1.7110 h −1 , activation energy (E a ) of 72.01 kJ mol −1 , preexponential factor (A) of 3.84 × 10 9 h −1 , enthalpy of activation (ΔH ‡ ) of 68.75 kJ mol −1 , entropy of activation (ΔS ‡ ) of −72.05 J K −1 mol −1 , and Gibb's free energy of activation (ΔG ‡ ) average of 97.08 kJ mol −1 . Based on the activation complex theory (ACT), the thermodynamic activation parameters indicated a nonspontaneous, endergonic, and endothermic process: ΔG ‡ > 0, ΔH ‡ > 0, and ΔS ‡ < 0, with estimated storage time of 149.82 d at 25 °C.

Considering the limited availability of technology for the production of rice vinegar and also due to the potential consumer product market, this study aimed to use alcoholic fermented rice (rice wine (Oryza sativa L.)) for vinegar production. An alcoholic solution with 6.28% (w/v) ethanol was oxidized by a submerged fermentation process to produce vinegar. The process of acetic acid fermentation occurred at 30 ± 0.3°C in a FRINGS  Acetator (Germany) for the production of vinegar and was followed through 10 cycles. The vinegar had a total acidity of 6.85% (w/v), 0.17% alcohol (w/v), 1.26% (w/v) minerals and 1.78% (w/v) dry extract. The composition of organic acids present in rice vinegar was: cis-aconitic acid (6 mg/L), maleic acid (3 mg/L), trans-aconitic acid (3 mg/L), shikimic + succinic acid (4 mg/L), lactic acid (300 mg/L), formic acid (180 mg/L), oxalic acid (3 mg/L), fumaric acid (3 mg/L) and itaconic acid (1 mg/L).Keywords: submerged fermentation; microfiltration; acetic acid bacteria; vinegar.Practical Application: Vinegar rice produced by a submerged fermentation process from alcoholic fermented rice.

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Infinite factors can influence the spread of COVID-19. Evaluating factors related to the spread of the disease is essential to point out measures that take effect. In this study, the influence of 14 variables was assessed together by Artificial Neural Networks (ANN) of the type Self-Organizing Maps (SOM), to verify the relationship between numbers of cases and deaths from COVID-19 in Brazilian states for 110 days. The SOM analysis showed that the variables that presented a more significant relationship with the numbers of cases and deaths by COVID-19 were influenza vaccine applied, Intensive Care Unit (ICU), ventilators, physicians, nurses, and the Human Development Index (HDI). In general, Brazilian states with the highest rates of influenza vaccine applied, ICU beds, ventilators, physicians, and nurses, per 100,000 inhabitants, had the lowest number of cases and deaths from COVID-19, while the states with the lowest rates were most affected by the disease. According to the SOM analysis, other variables such as Personal Protective Equipment (PPE), tests, drugs, and Federal funds, did not have as significant effect as expected.