3-Ethyl-5-(4-meth­oxy­phen­oxy)-2-(pyridin-4-yl)-3H-imidazo[4,5-b]pyridine

In the title compound, C20H18N4O2, the imidazopyridine fused ring system is almost perpendicular to the benzene ring [dihedral angle = 87.6 (5)°]. The pyridine ring makes a dihedral angle of 35.5 (5)° with the mean plane of the imidazopyridine fragment. The crystal structure is stabilized by an aromatic π–π stacking inter­action between the phenyl rings of neighbouring mol­ecules [centroid–centroid distance = 3.772 (2) Å, inter­planar distance = 3.546 (2) Å and slippage = 1.286 (2) Å]

L\u2019identificazione dello stato di un processo mediante l\u2019uso di reti neurali

Un qualsiasi processo \ue8 detto in controllo se i parametri della distribuzione di probabilit\ue0 della variabile si mantengono costanti. Il metodo normalmente utilizzato per verificare lo stato di un processo fa uso delle carte di controllo. Con tale metodologia si mettono in evidenza comportamenti anomali del sistema quali particolari sequenze, e cio\ue8 comportamenti che hanno bassa probabilit\ue0 di verificarsi per processi in controllo. L\u2019identificazione dello stato del sistema \ue8 generalmente eseguito mediante l\u2019esame visivo della carta: l\u2019operatore alla qualit\ue0 deve pertanto essere articolarmente addestrato per tenere conto delle numerose regole identificative dello stato di fuori controllo. Il presente lavoro propone l\u2019utilizzazione delle reti neurali artificiali per il riconoscimento automatico dello stato di un processo. La metodologia proposta, basata su una idonea codifica dei dati, ha mostrato un alto grado di efficienza, consentendo l\u2019identificazione di situazioni anomali pi\uf9 velocemente e correttamente di quanto non avviene se ci si basa solamente sull\u2019analisi visiva della carta di controllo. La metodologia ingloba altres\uec i vantaggi delle diverse tipologie di carte utilizzate per rispondere a particolari esigenze

Mathematical modeling of lactobacillus paracasei cba l74 growth during rice flour fermentation performed with and without ph control

The mathematical modeling of fermentation processes allows for the formulation of predictions about the kinetics of biomass growth and metabolite production as well as setting or verifying the best operative conditions in view of the economical convenience of the process. For this purpose, we performed a kinetic study of a rice flour fermentation process using Lactobacillus paracasei CBA L74 with and without pH control; the pH value was set to 5.8 under pH control. Monod, Logistic, and Contois models were proposed to describe the bacterial growth rate in both conditions. The best mathematical model, which was able to describe the experimental data obtained without pH control, was the Contois model, as the specific growth rate was influenced by both the glucose reduction (from 14.31 g/L to 10.22 g/L) and the biomass production (2 log growth) that occurred during fermentation. Conversely, when pH control was implemented, both Monod and Contois models satisfactorily described the specific growth rate trend. The estimated kinetic parameters confirmed that biomass production (2 log growth) and glucose consumption (from 14.31 g/L to 6.06 g/L) did not affect the microorganism’s growth capacity when the fermenting medium was maintained at an optimal pH. The lactic acid production rate described by the Luedeking–Piret model did not appear to be linked to growth in the absence of pH control while, on the other hand, this model was unsuitable for describing the experimental lactic acid concentration when pH control was applied. The kinetic modeling of lactic acid production and the percentage of added glucose in the protocol with controlled pH will be optimized in the future

Lactic fermentation of cooked navy beans by Lactobacillus paracasei CBA L74 aimed at a potential production of functional legume-based foods

The feasibility of developing a dry legume-based functional product using a fermentation process carried out on a 10% w/v navy bean suspension, in a lab-scale stirred batch reactor was studied. After soaking and cooking dried navy beans, the fermentation tests performed on the resulting medium using Lactobacillus paracasei CBA L74 showed a maximum bacterial count of 109 CFU/mL after 20 hr and a maximum lactic acid concentration of 1.9 g/L after 16 hr of process time. A freeze-drying process was conducted on the fermented bean suspension, showing a two-log microbial reduction and a bacterial viability in the resulting probiotic powder of 3.7 × 108 CFU/g