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In this study, combining the nanoparticle embedded sensors with lateral flow assays, a novel strategy for ensuring the quality of signalling in lateral flow assays (LFAs) was developed. A LFA for reactive oxygen species (ROS) is reported that is based on horse radish peroxidase (HRP) which is co-entrapped with Texas Red dextran inside porous polyacrylamide nanoparticles. In this system, enzymes are protected in the porous matrix of polyacrylamide which freely allows the diffusion of the analyte. The sensor is rapid and sensitive for quantification of hydrogen peroxide concentrations. A test solution of hydrogen peroxides was quantified with this novel LFA-ROS sensor to obtain a linear range between 1 and 25 μM. Nanoparticle embedding of enzymes is proposed here as a general strategy for developing enzyme-based lateral flow assays, eliminating adverse effects associated with biological samples.

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Essential forest ecosystem services can be assessed by better understanding the diversity of vegetation, specifically those of Mediterranean region. A species level classification of maquis would be useful in understanding vegetation structure and dynamics, which would be an indicator of degradation or succession in the region. Although remote sensing was regularly used for classification in the region, maquis are simply represented as one to three categories based on density or height. To fill this gap, we test the capability of Sentinel-2 imagery, together with selected ancillary variables, for an accurate mapping of the dominant maquis formations. We applied Recursive Feature Selection procedure and used a Random Forest classifier. The algorithm is tested using ground truth collected from site and reached 78% and 93% overall accuracy at species level and physiognomic level, respectively. Our results suggest species level characterization of dominant maquis is possible with Sentinel-2 spatial resolution.