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When irradiated with blue light in the presence of a Lewis base (L), [CpW(CO) 3 ] 2 undergoes metal–metal bond cleavage followed by a disproportionation reaction to form [CpW(CO) 3 L] + and [CpW(CO) 3 ] − . Here, we show that in the presence of pyridinium tetrafluoroborate, [CpW(CO) 3 ] − reacts further to form a metal hydride complex CpW(CO) 3 H. The rection was monitored through in situ photo 1 H NMR spectroscopy experiments and the mechanism of light-driven hydride formation was investigated by determining quantum yields of formation. Quantum yields of formation of CpW(CO) 3 H correlate with I −1/2 (I = photon flux on our sample tube), indicating that the net disproportionation of [CpW(CO) 3 ] 2 to form the hydride precursor [CpW(CO) 3 ] − occurs primarily through a radical chain mechanism. 

Fecal contamination is a significant source of water quality impairment globally. Aquatic ecosystems can provide an important ecosystem service of fecal contamination removal. Understanding the processes that regulate the removal of fecal contamination among river networks across flow conditions is critical. We applied a river network model, the Framework for Aquatic Modeling in the Earth System (FrAMES-Ecoli), to quantify removal of fecal indicator bacteria by river networks across flow conditions during summers in a series of New England watersheds of different characteristics. FrAMES-Ecoli simulates sources, transport, and riverine removal of Escherichia coli (E. coli). Aquatic E. coli removal was simulated in both the water column and the hyporheic zone, and is a function of hydraulic conditions, flow exchange rates with the hyporheic zone, and die-off in each compartment. We found that, at the river network scale during summers, removal by river networks can be high (19–99%) with variability controlled by hydrologic conditions, watershed size, and distribution of sources in the watershed. Hydrology controls much of the variability, with 68–99% of network scale inputs removed under base flow conditions and 19–85% removed during storm events. Removal by the water column alone could not explain the observed pattern in E. coli, suggesting that processes such as hyporheic removal must be considered. These results suggest that river network removal of fecal indicator bacteria should be taken into consideration in managing fecal contamination at critical downstream receiving waters. 

Helminths are parasites that cause disease at considerable cost to public health and present a risk for emergence as novel human infections. Although recent research has elucidated characteristics conferring a propensity to emergence in other parasite groups (e.g. viruses), the understanding of factors associated with zoonotic potential in helminths remains poor. We applied an investigator-directed learning algorithm to a global dataset of mammal helminth traits to identify factors contributing to spillover of helminths from wild animal hosts into humans. We characterized parasite traits that distinguish between zoonotic and non-zoonotic species with 91% accuracy. Results suggest that helminth traits relating to transmission (e.g. definitive and intermediate hosts) and geography (e.g. distribution) are more important to discriminating zoonotic from non-zoonotic species than morphological or epidemiological traits. Whether or not a helminth causes infection in companion animals (cats and dogs) is the most important predictor of propensity to cause human infection. Finally, we identified helminth species with high modelled propensity to cause zoonosis (over 70%) that have not previously been considered to be of risk. This work highlights the importance of prioritizing studies on the transmission of helminths that infect pets and points to the risks incurred by close associations with these animals. This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’. 

The economic production and integration of nanomaterial-based wearable energy storage devices with mechanically-compliable form factors and reliable performance will usher in exciting opportunities in emerging technologies such as consumer electronics, pervasive computing, human–machine interface, robotics, and the Internet of Things. Despite the increased interests and efforts in nanotechnology-enabled flexible energy storage devices, reducing the manufacturing and integration costs while continuously improving the performance at the device and system level remains a major technological challenge. The inkjet printing process has emerged as a potential economic method for nanomanufacturing printed electronics, sensors, and energy devices. Nevertheless, there have been few reports reviewing the scalable nanomanufacturing of inkjet printed wearable energy storage devices. To fill this gap, here we review the recent advances in inkjet printed flexible energy storage technologies. We will provide an in-depth discussion focusing on the materials, manufacturing process integration, and performance issues in designing and implementing the inkjet printing of wearable energy storage devices. We have also compiled a comprehensive list of the reported device technologies with the corresponding processing factors and performance metrics. Finally, we will discuss the challenges and opportunities associated with related topics. The rapid and exciting progress achieved in many emerging and traditional disciplines is expected to lead to more theoretical and experimental advances that would ultimately enable the scalable nanomanufacturing of inkjet printed wearable energy storage devices.