Bioavailability, Accumulation and Distribution of Toxic Metals (As, Cd, Ni and Pb) and Their Impact on Sinapis alba Plant Nutrient Metabolism.

This study presents the behavior of white mustard seedlings Sinapis alba grown for three months in laboratory polluted soil containing As, Cd, Ni and Pb. Four different experiments were performed in which As was combined with the other three toxic metals in different combinations (As, AsCd, AsCdNi, AsCdNiPb), keeping the same concentrations of As and Cd in all tests and following the national soil quality regulations. The effects of these metals were monitored by the analytical control of metal concentrations in soil and plants, bioavailability tests of mobile metal fractions using three different extracting solutions (DTPA + TEA + CaCl2-DTPA, DTPA + CaCl2-CAT, and CH3COONH4 + EDTA-EDTA) and calculation of bioaccumulation and translocation factors. Additionally, micro, and macro-nutrients both in soil and plant (root, stem, leaves, flowers and seeds) were analyzed in order to evaluate the impact of toxic metals on plant nutrient metabolism. Metals were significantly and differently accumulated in the plant tissues, especially under AsCdNi and AsCdNiPb treatments. Significant differences (p < 0.05) in the concentration of both As and Cd were highlighted. Translocation could be influenced by the presence of other toxic metals, such as Cd, but also of essential metals, through the competition and antagonism processes existing in plant tissues. Significantly, more Cd and Ni levels were detected in leaves and flowers. Cd was also detected in seeds above the WHO limit, but the results are not statistically significant (p > 0.05). The extraction of metallic nutrients (Zn, Cu, Mn, Ni, Mg, K, Fe, Ca, Cr) in the plant was not influenced by the presence of toxic metal combinations, on the contrary, their translocation was more efficient in the aerial parts of the plants. No phytotoxic effects were recorded during the exposure period. The most efficient methods of metal extraction from soil were for As-CAT; Cd-all methods; Pb and Ni-DTPA. The Pearson correlations (r) between applied extraction methods and metal detection in plants showed positive correlations for all toxic metals as follows: As-CAT > DTPA > EDTA, Cd-DTPA > CAT > EDTA, Ni-EDTA = DTPA > CAT, Pb-EDTA = DTPA = CAT). The results revealed that Sinapis alba has a good ability to accumulate the most bioavailable metals Cd and Ni, to stabilize As at the root level and to block Pb in soil.

Using Neural Networks in Order to Analyze Telework Adaptability across the European Union Countries: A Case Study of the Most Relevant Scenarios to Occur in Romania.

Our study addresses the issue of telework adoption by countries in the European Union and draws up a few feasible scenarios aimed at improving telework's degree of adaptability in Romania. We employed the dataset from the 2020 Eurofound survey on Living, Working and COVID-19 (Round 2) in order to extract ten relevant determinants of teleworking on the basis of 24,123 valid answers provided by respondents aged 18 and over: the availability of work equipment; the degree of satisfaction with the experience of working from home; the risks related to potential contamination with SARS-CoV-2 virus; the employees' openness to adhering to working-from-home patterns; the possibility of maintaining work-life balance objectives while teleworking; the level of satisfaction on the amount and the quality of work submitted, etc. Our methodology entailed the employment of SAS Enterprise Guide software to perform a cluster analysis resulting in a preliminary classification of the EU countries with respect to the degree that they have been able to adapt to telework. Further on, in order to refine this taxonomy, a multilayer perceptron neural network with ten input variables in the initial layer, six neurons in the intermediate layer, and three neurons in the final layer was successfully trained. The results of our research demonstrate the existence of significant disparities in terms of telework adaptability, such as: low to moderate levels of adaptability (detected in countries such as Greece, Croatia, Portugal, Spain, Lithuania, Latvia, Poland, Italy); fair levels of adaptability (encountered in France, Slovakia, the Czech Republic, Hungary, Slovenia, or Romania); and high levels of adaptability (exhibited by intensely digitalized economies such Denmark, Sweden, Finland, Germany, Ireland, the Netherlands, Belgium, etc.).