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Polyurethanes (PU) are one of the most-used classes of synthetic polymers in Europe, having a considerable impact on the plastic waste management in the European Union. Therefore, they represent a major challenge for the recycling industry, which requires environmentally friendly strategies to be able to re-utilize their monomers without applying hazardous and polluting substances in the process. In this work, enzymatic hydrolysis of a polyurethane-polyester (PU-PE) copolymer using Humicola insolens cutinase (HiC) has been investigated in order to achieve decomposition at milder conditions and avoiding harsh chemicals. PU-PE films have been incubated with the enzyme at 50 °C for 168 h, and hydrolysis has been followed throughout the incubation. HiC effectively hydrolysed the polymer, reducing the number average molecular weight (Mn) and the weight average molecular weight (Mw) by 84% and 42%, respectively, as shown by gel permeation chromatography (GPC), while scanning electron microscopy showed cracks at the surface of the PU-PE films as a result of enzymatic surface erosion. Furthermore, Fourier Transform Infrared (FTIR) analysis showed a reduction in the peaks at 1725 cm−1, 1164 cm−1 and 1139 cm−1, indicating that the enzyme preferentially hydrolysed ester bonds, as also supported by the nuclear magnetic resonance spectroscopy (NMR) results. Liquid chromatography time-of-flight/mass spectrometry (LC-MS-Tof) analysis revealed the presence in the incubation supernatant of all of the monomeric constituents of the polymer, thus suggesting that the enzyme was able to hydrolyse both the ester and the urethane bonds of the polymer.

The digitalisation, automation and robotisation of road inspection and maintenance technologies make it possible to collect bigger volumes of data and additional types of information about road infrastructure. Methodologies and tools to support road asset management decision-making are needed to exploit this new information, progressing towards predictive maintenance and improving different aspects of road asset management. This study presents a Digital Twin-based Decision Support Tool to assist road operators in road inspection, maintenance and upgrade. The goal of the paper is twofold. First, the architecture of the Digital Twin-based Decision Support Tool is presented, describing the main components and functionalities. The system is based on a Digital Twin (DT) that mirrors real road assets to integrate different sources of data and support the processing of low-level data into high-level information. The decision support tool (DST) is able to analyse the collected information and compute the road pavement condition to derive optimal intervention plans, addressing road section conditions, human and technical resources and other external constraints. Second, the application of the proposed architecture to road pavement maintenance is described, considering the Italian highway A24 and its connections with Rome´s ring road, managed by Strada dei Parchi SpA. Road pavement data, such as the International Roughness Index (IRI) and the Sideway Force Coefficient (SFC), are integrated into the DT to be analysed through Artificial Intelligence-clustering techniques to perform the sectioning and clustering of road sections according to their status and quality index. The paper shows the benefits derived from the integration of DT technologies with DSTs for improving processes of road maintenance. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 955269.

En este trabajo indagamos el modo en que la ecología se dirige a su objeto de estudio, la naturaleza. "Ilustramos" este modo de estudiar la naturaleza mediante una crítica a la objetividad desarrollada por Theodore Roszak. Destacando que la ecología opera, en el contexto de la problemática ambiental, <<como sí>> fuese objetiva. En este marco, problematizamos: (i) cómo se construye un significado de la naturaleza desde la ecología, (ii) cómo se silencia la experiencia del ecólogo en la naturaleza, (iii) cómo se da el vínculo entre valores (espirituales, estéticos o recreativos) y conocimiento ecosistémico y finalmente (iv) abordamos el carácter <<nómade>> del conocimiento ecosistémico y su posición hegemónica en el contexto de la problemática ambiental. En líneas generales, las conclusiones del presente trabajo se dirigen a relegar al conocimiento ecosistémico a un lugar más modesto dentro de la actual crisis ambiental.

The UK economy has experienced significant macroeconomic adjustments following the 2016 referendum on its withdrawal from the European Union. This paper develops and estimates a small open economy model with tradable and non-tradable sectors to characterise these adjustments. We demonstrate that many of the effects of the referendum result can be conceptualised as news about a future slowdown in productivity growth in the tradable sector. Simulations show that the responses of the model economy to such news are consistent with key patterns in UK data. While overall economic growth slows, an immediate permanent fall in the relative price of non-tradable output (the real exchange rate) induces a temporary 'sweet spot' for tradable producers before the slowdown in tradable sector productivity associated with Brexit occurs. Resources are reallocated towards the tradable sector, tradable output growth rises and net exports increase. These developments reverse after the productivity decline in the tradable sector materialises. The negative news about tradable sector productivity also leads to a decline in domestic interest rates relative to world interest rates and to a reduction in investment growth, while employment remains relatively stable. As a by-product of our analysis, we provide a quantitative analysis of the UK business cycle.