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The use of deep eutectic solvent (DES)/water mixtures were explored for the selective enzymatic synthesis of α‐monobenzoate glycerol (α‐MBG) from glycerol and benzoic acid as substrates. Experiments were performed with four DES, three of them containing choline chloride (ChCl), combined with urea (URA), glycerol (GLY), and ethylene glycol (ETA) (in all cases ChCl/HBD 1:2 mol ratio), and another one formed with methylammonium chloride and glycerol (MA/GLY 1:3 mol ratio). The best conversions (99 %) were achieved with immobilized lipase B from Candida antarctica (CAL‐B) when ChCl/GLY was used as the solvent and the substrate at the same time. The use of water as a cosolvent (8 % v/v) led to a significant decrease in the viscosity of the DES, and full conversions were then reached. Reusability studies of the biocatalyst revealed a 37 % decrease in activity after the first batch, but the activity remained mostly constant for the rest of the cycles.

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Despite their importance for stakeholders in the criminal justice system, few methods have been developed for determining which criminal behavior variables will produce accurate sentence predictions. Some approaches found in the literature resort to techniques based on indirect variables, but not on the social network behavior with exception of the work of Baker and Faulkner [ASR 58: 837–860, 1993]. Using information on the Caviar Network narcotics trafficking group as a real-world case, we attempt to explain sentencing outcomes employing the social network indicators. Specifically, we report the ability of centrality measures to predict a) the verdict (innocent or guilty) and b) the sentence length in years. We show that while the set of indicators described by Baker and Faulkner yields good predictions, introduction of the additional centrality measures generates better predictions. Some ideas for orienting future research on further improvements to sentencing outcome prediction are discussed.A pesar de la importancia para diferentes actores involucrados en el sistema judicial, se han desarrollados pocos métodos para determinar las variables del comportamiento organizado que permiten predecir las sentencias judiciales de redes criminales. Algunas aproximaciones encontradas en la literatura especializada usa variables indirectas al comportamiento organizado y no en el comportamiento en red de estas organizaciones. Nosotros usamos información real sobre un caso de red criminal real que operó en Montreal (Canadá) y analizamos la comunicación entre los miembros de la red para determinar si su comportamiento comunicacional permite predecir el veredicto así como los años de sentencia. Encontramos que los modelos de regresión obtenidos y las variables de centralidad nodal utilizadas por nosotros logra un mejor capacidad predictiva. Finalmente, se discuten algunas ideas dirigidas a mejorar la predicción de sentencias judiciales desde las medidas de redes sociales