ABSTRACT
Elevated concentrations of heavy metals result in soil degradation, a reduction in plant yields, and a lower quality of agricultural products, which directly endangers people, animals, and the ecosystem. The potential of three clones of Salix alba (347, NS 73/6, and B-44) and one genotype of S. viminalis for the phytoextraction of heavy metals was investigated, with the aim of identifying the most physiologically suitable willow genotypes for use in soil phytoremediation. The experiment was placed on the contaminated soil substrate collected in Kolubara Mining Basin (Serbia), enriched by high loads of heavy metal salts, and a control medium. Significant differences in the concentrations of heavy metals were recorded between the contaminated and control plant material, especially when it comes to nickel (Ni), copper (Cu), cadmium (Cd), and lead (Pb), confirming that S. alba and S. viminalis are hyperaccumulator species of heavy metals. Clone 347 shows the greatest uptake of Cd and chromium (Cr), and clone B-44 takes up these metals only to a lesser extent, while clone NS 73/6 shows a less pronounced uptake of Cr. The roots have the greatest ability to accumulate Ni and Pb, Cu is absorbed by all plant organs, while Cd is absorbed by the leaves. The organ that showed the greatest ability to accumulate heavy metals was the root, which means that willows have a limited power to translocate heavy metals to above-ground organs. The studied genotypes of S. alba have a higher potential for the phytostabilization of Cu and Cd, as well as the phytoextraction of Cd, compared with S. viminalis. The results confirm the assumption of differences between different willow genotypes in terms of the ability to phytoextract certain heavy metals from soil, which is important information when selecting genotypes for soil phytoremediation.
ABSTRACT
Understanding the brain is a fascinating challenge, captivating the scientific community and the public alike. The lack of effective treatment for most brain disorders makes the training of the next generation of neuroscientists, engineers and physicians a key concern. Over the past decade there has been a growing effort to introduce neuroscience in primary and secondary schools, however, hands-on laboratories have been limited to anatomical or electrophysiological activities. Modern neuroscience research labs are increasingly using computational tools to model circuits of the brain to understand information processing. Here we introduce the use of neurorobots - robots controlled by computer models of biological brains - as an introduction to computational neuroscience in the classroom. Neurorobotics has enormous potential as an education technology because it combines multiple activities with clear educational benefits including neuroscience, active learning, and robotics. We describe a 1-week introductory neurorobot workshop that teaches high school students how to use neurorobots to investigate key concepts in neuroscience, including spiking neural networks, synaptic plasticity, and adaptive action selection. Our do-it-yourself (DIY) neurorobot uses wheels, a camera, a speaker, and a distance sensor to interact with its environment, and can be built from generic parts costing about $170 in under 4 h. Our Neurorobot App visualizes the neurorobot's visual input and brain activity in real-time, and enables students to design new brains and deliver dopamine-like reward signals to reinforce chosen behaviors. We ran the neurorobot workshop at two high schools (n = 295 students total) and found significant improvement in students' understanding of key neuroscience concepts and in students' confidence in neuroscience, as assessed by a pre/post workshop survey. Here we provide DIY hardware assembly instructions, discuss our open-source Neurorobot App and demonstrate how to teach the Neurorobot Workshop. By doing this we hope to accelerate research in educational neurorobotics and promote the use of neurorobots to teach computational neuroscience in high school.
