We report the synthesis of MnO nanoparticles (AI-MnO NAPs) using biological molecules of Abutilon indicum leaf extract. Further, they were evaluated for antibacterial and cytotoxicity activity against different pathogenic microbes (Escherichia coli, Bordetella bronchiseptica, Staphylococcus aureus, and Bacillus subtilis) and HeLa cancerous cells. Synthesized NAPs were also investigated for photocatalytic dye degradation potential against methylene blue (MB), and adsorption activity against Cr(VI) was also determined. Results from Scanning electron microscope (SEM), X-ray powder diffraction (XRD), Energy-dispersive X-ray (EDX), and Fourier-transform infrared spectroscopy (FTIR) confirmed the successful synthesis of NAPs with spherical morphology and crystalline nature. Biological activity results demonstrated that synthesized AI-MnO NAPs exhibited significant antibacterial and cytotoxicity propensities against pathogenic microbes and cancerous cells, respectively, compared with plant extract. Moreover, synthesized AI-MnO NAPs demonstrated the comparable biological activities results to standard drugs. These excellent biological activities results are attributed to the existence of the plant’s biological molecules on their surfaces and small particle size (synergetic effect). Synthesized NAPs displayed better MB-photocatalyzing properties under sunlight than an ultraviolet lamp. The Cr(VI) adsorption result showed that synthesized NAPs efficiently adsorbed more Cr(VI) at higher acidic pH than at basic pH. Hence, the current findings suggest that Abutilon indicum is a valuable source for tailoring the potential of NAPs toward various enhanced biological, photocatalytic, and adsorption activities. Consequently, the plant’s biological molecule-mediated synthesized AI-MnO NAPs could be excellent contenders for future therapeutic applications.

Autonomous vehicles offer greater passenger convenience and improved fuel efficiency. However, they are likely to increase road transport activity and life cycle greenhouse emissions, due to several rebound effects. In this study, we investigate tradeoffs between improved fuel economy and rebound effects from a life-cycle perspective. Our results show that autonomy introduces an average 21.2% decrease in operation phase emissions due to improved fuel economy while manufacturing phase emissions can surge up to 40%. Recycling efforts can offset this increase, cutting emissions by 6.65 tons of Carbon dioxide equivalent per vehicle. However, when examining the entire life cycle, autonomous electric vehicles might emit 8% more greenhouse gas emissions on average compared to nonautonomous electric vehicles. To address this, we suggest; (1) cleaner and more efficient manufacturing technologies, (2) ongoing fuel efficiency improvements in autonomous driving; (3) renewable energy adoption for charging, and (4) circular economy initiatives targeting the complete life cycle.

In most manufacturing processes, we face sudden outliers, and in such situations, median control charts are more outliers-resistant than mean control charts. In ideal circumstances, a median chart presents less efficiency than a mean chart. In order to overcome the efficiency loss in uncontaminated environments by maintaining its resistance ability in contaminated environments, we have suggested an auxiliary information–based set of median type control charts using the coefficient of variation and coefficient of kurtosis of auxiliary characteristics for efficient process monitoring. The performances of these control charts are evaluated in terms of average run length (ARL) and extra quadratic loss (EQL) under the univariate, bivariate, and trivariate normally distributed process environments. The effects of contaminated environments are also examined on the ARL performance of different median-based charting structures. The illustrative examples concerning median type control structures are also provided for procedural details.