Assisted Phytostabilization of Mine-Tailings with Prosopis laevigata (Fabaceae) and Biochar.

Phytoremediation is a cost-effective technique to remediate heavy metal (HM) polluted sites. However, the toxic effects of HM can limit plant establishment and development, reducing phytoremediation effectiveness. Therefore, the addition of organic amendments to mine wastes, such as biochar, improves the establishment of plants and reduces the bioavailability of toxic HM and its subsequent absorption by plants. Prosopis laevigata can establish naturally in mine tailings and accumulate different HM; however, these individuals show morphological and genetic damage. In this study, the effect of biochar on HM bioaccumulation in roots and aerial tissues, HM translocation, morphological characters and plant growth were evaluated, after three and six months of exposure. Plants grown on mine tailings with biochar presented significantly higher values for most of the evaluated characters, in respect to plants that grew on mine tailing substrate. Biochar addition reduced the bioaccumulation and translocation of Cu, Pb, and Cd, while it favored the translocation of essential metals such as Fe and Mn. The addition of biochar from agro-industrial residues to mine tailings improves the establishment of plants with potential to phytoextract and phytostabilize metals from polluted soils. Using biochar and heavy metal accumulating plants constitutes an assisted phytostabilization strategy with great potential for HM polluted sites such as Cd and Pb.

HRpI System Based on Wavenet Controller with Human Cooperative-in-the-Loop for Neurorehabilitation Purposes.

There exist several methods aimed at human-robot physical interaction (HRpI) to provide physical therapy in patients. The use of haptics has become an option to display forces along a given path so as to it guides the physiotherapist protocol. Critical in this regard is the motion control for haptic guidance to convey the specifications of the clinical protocol. Given the inherent patient variability, a conclusive demand of these HRpI methods is the need to modify online its response with neither rejecting nor neglecting interaction forces but to process them as patient interaction. In this paper, considering the nonlinear dynamics of the robot interacting bilaterally with a patient, we propose a novel adaptive control to guarantee stable haptic guidance by processing the causality of patient interaction forces, despite unknown robot dynamics and uncertainties. The controller implements radial basis neural network with daughter RASP1 wavelets activation function to identify the coupled interaction dynamics. For an efficient online implementation, an output infinite impulse response filter prunes negligible signals and nodes to deal with overparametrization. This contributes to adapt online the feedback gains of a globally stable discrete PID regulator to yield stiffness control, so the user is guided within a perceptual force field. Effectiveness of the proposed method is verified in real-time bimanual human-in-the-loop experiments.