In the context of climate change and population growth, aquaculture plays an important role for food security, employment and economic development. Intensive recirculating aquaculture systems (RAS) allow to treat and recycle fish effluents to reduce waste concentration in outflow water thereby reducing environmental contamination. RAS sustainability may be further improved using aquaponics, a circular productive system in which RAS wastewater is recovered for crop cultivation and recycled back to the fish tanks. In this study, water metabolism of a catfish RAS was assessed and the opportunity to produce lettuce with the RAS effluent was tested. Crop growth and water consumption in aquaponics were compared to those experienced in hydroponics at three nutrient solution concentration (EC of 1.6, 2.0 and 3.0 dS•m −1 ), also considering water-(WUE) and nitrogen-use efficiency (NUE). A scenario for converting the RAS in a catfish-lettuce aquaponic system was, then, proposed.The RAS water balance included an input of 555 L•day -1 , out of which 32 L•day -1 were lost by evaporation from the tubs whereas 460 L•day -1 were discarded. The lettuce yield, NUE and WUE in aquaponics were respectively 20.3%, 22.3% and 20.6% lower than those obtained in hydroponics. Best performances in 2 hydroponics were achieved with EC of 2.0 dS m -1 . No difference in term of water consumption arose between the treatments, with average water use of 46 mL•plant -1 •day -1 .Considering the current RAS productivity of 329 kg year -1 , a 10 m 2 raft system hosting 160 lettuces would satisfy the nitrogen filtration demand. Once closed the water loop between the two productive sub-units, the current water input of 532 L•day -1 could be reduced to the amount needed to replace the water lost by evaporation (50 L•day -1 ) and the RAS water output would decrease from 555 to 103 L•day -1 .

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The generation of fast models for device level circuit descriptions is a very active area of research. Model order reduction is an attractive technique for dynamical models size reduction. In this paper, we propose an approach based on clustering, curve-fitting, linearization and Krylov space projection to build reduced models for nonlinear analog circuits. We demonstrate our model order reduction method for three nonlinear circuits: a voltage controlled oscillator, an operational amplifier and a digital frequency divider. Our experimental results show that the reduced models lead to an improvement in simulation speed while guaranteeing the representation of the behavior of the original circuit design.