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Unlocking feedforward capabilities in Model Predictive Control algorithms to deal with measurable disturbances
Announce Type: new Abstract: Disturbance rejection is a central objective in process control, particularly when measurable disturbances can be exploited through feedforward action. Although Model Predictive Control (MPC) naturally incorporates disturbance models and prediction capabilities, standard formulations cannot achieve complete disturbance rejection since the cost function penalises control effort.
PETase Kubu enables near-complete enzymatic depolymerization of commercial PLA/PBAT blend mulch film
Agricultural mulch films improve crop productivity, but post-use recovery and recycling remain difficult because the films are thin, fragmented, dispersed across fields, and contaminated. Commercial PLA/PBAT blends are increasingly used as biodegradable mulch film materials, yet these films exhibit slow or incomplete degradation under environmental conditions. Here, we show that Kubu, a thermostable PETase from Kutzneria buriramensis, rapidly depolymerizes commercial PLA/PBAT mulch film...