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We investigated how a community of microbial decomposers adapted to a reference site responds to a sudden decrease in the water quality. For that, we assessed the activity and diversity of fungi and bacteria on decomposing leaves that were transplanted from a reference (E1) to a polluted site (E2), and results were compared to those from decomposing leaves either at E1 or E2. The two sites had contrasting concentrations of organic and inorganic nutrients and heavy metals in the stream water. At E2, leaf decomposition rates, fungal biomass, and sporulation were reduced, while bacterial biomass was stimulated. Fungal diversity was four times lower at the polluted site. The structure of fungal community on leaves decomposing at E2 significantly differed from that decomposing at E1, as indicated by the principal response curves analysis. Articulospora tetracladia, Anguillospora filiformis, and Lunulospora curvula were dominant species on leaves decomposing at E1 and were the most negatively affected by the transfer to the polluted site. The transfer of leaves colonized at the reference site to the polluted site reduced fungal diversity and sporulation but not fungal biomass and leaf decomposition. Overall, results suggest that the high diversity on leaves from the upstream site might have mitigated the impact of anthropogenic stress on microbial decomposition of leaves transplanted to the polluted site.

This work presents a crude bioethanol fueled integrated power system for backup and off-grid applications. The system is based on ethanol steam reformation to hydrogen that is used in polymer electrolyte fuel cells to produce electricity. We introduce the system design and overall system specifications, and report the experimental process of defining specifications for the produced hydrogen quality, a key variable affecting the final system cost, efficiency and durability. Results from development of individual subsystems are also presented together with discussion on the complete system integration.

A good process understanding is the foundation for process optimization, process monitoring, end-point detection, and estimation of the end-product quality. Performing good process measurements and the construction of process models will contribute to a better process understanding. To improve the process knowledge it is common to build process models. These models are often based on first principles such as kinetic rates or mass balances. These types of models are also known as hard or white models. White models are characterized by being generally applicable but often having only a reasonable fit to real process data. Other commonly used types of models are empirical or black-box models such as regression and neural nets. Black-box models are characterized by having a good data fit but they lack a chemically meaningful model interpretation. Alternative models are grey models, which are combinations of white models and black models. The aim of a grey model is to combine the advantages of both black-box models and white models. In a qualitative case study of monitoring industrial batches using near-infrared (NIR) spectroscopy, it is shown that grey models are a good tool for detecting batch-to-batch variations and an excellent tool for process diagnosis compared to common spectroscopic monitoring tools.

The European Project Semester (EPS) is a multicultural, multidisciplinary teamwork and project-based learning framework offered to engineering, business and product design undergraduates by a network of European Higher Education institutions, including the Instituto Superior de Engenharia do Porto (ISEP). In the spring of 2021, five EPS@ISEP students from distinct countries and fields of study joined efforts to address the smart and sustainable food production issue. This paper reports their research and development of Wormify, a solution based on vermicomposting. The main goal of the project was to design, simulate, test and build a prototype following ethical and sustainable practices. Wormify aims to minimize the problem of feeding the growing global population, and to prevent food waste from going to landfills. These objectives were pursued by designing a smart modular system for urban rooftops or small balconies. Several modules can be connected to form a place for residents to meet and socialize. The smart system allows monitoring through an app/website. This paper presents the background studies, the concept and design, the development and final results.

AbstractThis study presents the chiral resolution of flurbiprofen enantiomers by preparative liquid chromatography using the simulated moving bed (SMB) technology. Flurbiprofen enantiomers are widely used as nonsteroidal anti‐inflammatory drugs, and although demonstrate different therapeutic actions, they are still marketed as a racemic mixture. The results presented here clearly show the importance of the selection of the proper solvent composition for the preparative separation of flurbiprofen enantiomers. Chiral SMB separation is carried out using a laboratory‐scale unit (the FlexSMB‐LSRE®) with six columns, packed with the Chiralpak AD® stationary phase (20 μm). Results presented include the experimental measurement of equilibrium and kinetic data for two very different solvent compositions, a traditional high hydrocarbon content [10%ethanol/90%n‐hexane/0.01% trifluoroacetic acid (TFA)] and a strong polar organic composition (100%ethanol/0.01%TFA). Experimental data, obtained using the two mobile phase compositions, are used to predict and optimize the SMB operation. After selecting 10%ethanol/90%n‐hexane/0.01%TFA as the most appropriate solvent composition, three feed concentrations of racemic flurbiprofen were considered. Using 40 g/l of racemic flurbiprofen feed solution, the purities for both outlet streams were above 99.4%, the productivity was 13.1 gfeed/(Lbedh), and a solvent consumption of 0.41 Lsolvent/gfeedwas achieved. Chirality, 2011. © 2011 Wiley‐Liss, Inc.

Abstract P(VDF-TrFE), solid polymer electrolytes were prepared using the ionic liquid N,N,N-trimethyl-N-(2-hydroxyethyl)ammonium bis(trifluoromethylsulfonyl)imide, [N1 1 1 2(OH)][NTf2]. The morphology, polymer phase, and thermal and electrochemical properties have been determined by scanning electron microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), differential scanning calorimetry (DSC) and impedance spectroscopy, respectively. The addition of the ILs in P(VDF-TrFE) affects the microstructure, thermal stability and ionic conductivity of the polymer membrane. It was found that the ionic conductivity increases as the ionic liquid (IL) content increases with a maximum value at room temperature of 1.7 × 10− 5 S·cm− 1 for an IL composition of 32 wt.%. The temperature behavior in the ionic conductivity is thermally activated, following the Arrhenius equation, the high ionic conductivity resulting from the large carrier numbers of the IL. The electrochemical potential window shows 1.0 V at 4.0 V that these solid polymer electrolytes are adequate for energy storage devices.

Introduction: Active modes of transport can be defined as means of travel and transport at reduced speed, which take up little space on public roads and do not emit air pollutants or noise, being seen as an economic, social, and environmental asset, and a real alternative to motorized vehicles. Given its characteristics, the environmental benefits retrieved from active modes of transport should not serve only as a justification for its promotion but as a decisive and active factor in the scope of its actual use, which translates into the provision of pleasant and less polluted routes. Thus, the main objective of this paper is the development of a model for planning and generating urban routes for active modes that have a less negative influence on active users (pedestrians and cyclists) regarding their exposure to air and noise pollution. Methods: Conventional route planners are mostly designed to find the shortest, fastest, or less expensive route. In this research, the model to assign the best route will be presented for pedestrians and cyclists from an environmental point of view, by defining the least polluted, less noisy, and most health-friendly path. Based on the production of noise and air pollution maps, the model proposes the contamination of the network routes, which are used to determine healthoriented routes. The model is carried out through the calculation of the noise and pollution exposure for the routes found, compared to the shortest route. Conclusion: It was possible to conclude that less polluted routes may imply a small increase in the length of routes, but a significant gain in terms of reduction in exposure to PM10 and noise for active modes. Thus, the use of health-friendly routes can be seen as a matter of public health and a way for promoting more sustainable mobility. Available online 12 June 2022 (undefined)