Enhanced lead phytoextraction and soil health restoration through exogenous supply of organic ligands: Geochemical modeling".

Phytoremediation of lead (Pb) contaminated soil is a green technology to reduce Pb exposure and root exudates-derived organic acids play a vital role in this treatment process. In this study, Pb hyperaccumulator Pelargonium hortorum was chosen to investigate root-induced organic acid secretions and their subsequent role in Pb phytoextraction. In the first step, root exudation of P. hortorum was investigated in hydroponic experiments (0.2X Hoagland solution) under control and Pb stress conditions. Possible chemical interactions between Pb and the observed root exudates were then analyzed using Visual MINTEQ modeling. In the next step, the effects of the exogenous application of organic acids on Pb phytoextraction and soil enzymatic activities were studied in a pot experimental setup. Results indicated significant exudation of malic acid > citric acid > oxalic acid > tartaric acid in root exudates of P. hortorum under 50 mg L-1 Pb. Visual MINTEQ modeling results revealed that organic acids directly affect Pb dissolution in the nutrient solution by modulation of solution pH. Experimental results revealed that malic acid and citric acid significantly increased available Pb contents (7.2- and 6.7-folds) in the soil with 1500 mg kg-1 Pb contamination. Whereas, in shoot and root, the highest increase in Pb concentration was observed with citric acid (2.01-fold) and malic (3.75-fold) supplements, respectively. Overall, Pb uptake was notably higher when malic acid was applied (2.8-fold) compared to other organic acids, followed by citric acid (2.7-fold). In the case of soil enzymatic activities, oxalic acid significantly improved dehydrogenase, alkaline phosphatase, and microbial biomass by 1.6-, 1.4- and 1.3-folds, respectively. The organic acids were successful in reviving enzyme activity in Pb-contaminated soil, and might thus be used for long-term soil regeneration.

AI-driven adaptive reliable and sustainable approach for internet of things enabled healthcare system.

Artificial Intelligence (AI) driven adaptive techniques are viable to optimize the resources in the Internet of Things (IoT) enabled wearable healthcare devices. Due to the miniature size and ability of wireless data transfer, Body Sensor Networks (BSNs) have become the center of attention in current medical media technologies. For a long-term and reliable healthcare system, high energy efficiency, transmission reliability, and longer battery lifetime of wearable sensors devices are required. There is a dire need for empowering sensor-based wearable techniques in BSNs from every aspect i.e., data collection, healthcare monitoring, and diagnosis. The consideration of protocol layers, data routing, and energy optimization strategies improves the efficiency of healthcare delivery. Hence, this work presents some key contributions. Firstly, it proposes a novel avant-garde framework to simultaneously optimize the energy efficiency, battery lifetime, and reliability for smart and connected healthcare. Secondly, in this study, an Adaptive Transmission Data Rate (ATDR) mechanism is proposed, which works on the average constant energy consumption by varying the active time of the sensor node to optimize the energy over the dynamic wireless channel. Moreover, a Self-Adaptive Routing Algorithm (SARA) is developed to adopt a dynamic source routing mechanism with an energy-efficient and shortest possible path, unlike the conventional routing methods. Lastly, real-time datasets are adopted for intensive experimental setup for revealing pervasive and cost-effective healthcare through wearable devices. It is observed and analysed that proposed algorithms outperform in terms of high energy efficiency, better reliability, and longer battery lifetime of portable devices.

Lead availability and phytoextraction in the rhizosphere of Pelargonium species.

Availability of lead (Pb) in soil is a major factor controlling the phytoremediation efficiency of plants. This study was focused on investigating the plant-induced changes in rhizosphere and corresponding effect on bioavailable fraction of Pb and accumulation in different plant parts. For rhizosphere study, special cropping device was designed locally. Two Pb accumulator plants Stigmatocarpum criniflorum (L. f.) L. Bolus and Pelargonium × hortorum L.H. Bailey were grown in cropping device setup containing Pb spiked soil (500, 1000, 1500, and 2000 mg kg-1) for a period of 3 weeks. Further plants were also analyzed for Pb-induced oxidative stress. The results indicated higher ability of soil adjustment for Pb uptake by P. hortorum. The soil pH was (p < 0.05) decreased (ΔpH = - 0.22 pH), and dissolved organic carbon (DOC) content was significantly increased (by 1.7-fold) in rhizosphere of P. hortorum. The bioavailable fraction of Pb was twofold higher in rhizosphere of P. hortorum than S. criniflorum at the same soil Pb concentration (2000 mg kg-1). Maximum Pb concentration in root and shoot of S. criniflorum was 755 ± 99 and 207 ± 12 mg Pb/kg DW and for P. hortorum was 1281 ± 77 and 275 ± 7 mg Pb/kg DW. P. hortorum uptakes more Pb per plant by threefold compared with S. criniflorum. The oxidative stress results indicated higher Pb tolerance and suitability of P. hortorum for phytoextraction of Pb-contaminated soil.