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The effect of floating plant on water purification: Comparison of the water purification capability of Water Hyacinth, Duckweed, and Azolla

Park et al. | Nov 21, 2020

The effect of floating plant on water purification: Comparison of the water purification capability of Water Hyacinth, Duckweed, and Azolla

Clean water is a necessity for every household, yet water pollution is a serious problem in many parts of the world and plays a major role in compromising water security in the 21st century. In this paper, the authors address the utility of several plants as natural water purifiers. They estimate the effectiveness of duckweed, hyacinth, and azolla in improving the quality of water from the Mithi river in India by measuring several metrics. They conclude that all three plants are effective in improving water quality, suggesting that these plants as eco-friendly options for water treatment.

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Electrocatalytic oxidation of furfural on Co3O4/nickel foam catalyst: performance and mechanistic study

Song et al. | Jul 19, 2026

Electrocatalytic oxidation of furfural on Co<sub>3</sub>O<sub>4</sub>/nickel foam catalyst: performance and mechanistic study
Image credit: Shraga kopstein

In this study, the authors hypothesized that the unique redox properties of cobalt oxide (Co3O4), combined with the conductive nature of the nickel foam (NF) substrate, synergistically enhances the catalytic performance for furfural oxidation. The study showed successful synthesis of Co3O4 nanoflowers directly grown on NF and tested their capacity to serve as a highly efficient electrocatalyst for furfural oxidation. Beyond furfural oxidation, this study also offers broader implications for sustainable chemistry by establishing design principles for efficient nucleophilic oxidation reaction catalysts, demonstrating an energy-saving alternative to conventional oxygen evolution reaction-coupled processes, and showcasing how biomass conversion can be integrated with renewable energy systems.

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Leveraging transfer learning with convolutional neural networks for cardiovascular disease detection

Chen et al. | May 25, 2026

Leveraging transfer learning with convolutional neural networks for cardiovascular disease detection
Image credit: Stephen Andrews

This study shows the efficacy of leveraging transfer learning, specifically from residual networks, to detect CVDs and possible signs of CVDs. The findings indicate that leveraging transfer learning from residual networks alongside medical professionals is a highly promising approach for CVD detection and diagnosis, warranting further investigation.

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Influence of induction heating on static recrystallization kinetics of AISI 4130 steel

Chen et al. | Apr 30, 2026

Influence of induction heating on static recrystallization kinetics of AISI 4130 steel

This article investigates whether induction heating can speed up static recrystallization in AISI 4130 steel compared with traditional radiant heating. It was found that induction-heated samples recrystallized faster, softened more quickly, and showed earlier microstructural changes like grain nucleation and pearlite spheroidization, suggesting induction heating could be a more efficient alternative for industrial metal heat treatments.

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Bacteriophage TLS sensitizes Escherichia coli to antibiotics

Emann et al. | Mar 04, 2026

Bacteriophage TLS sensitizes <i>Escherichia coli</i> to antibiotics

Antibiotic resistance is a growing global health threat, and one strategy to combat it is using bacteriophages to enhance the effectiveness of existing antibiotics. This study tested whether targeting the TolC protein in E. coli with the TLS bacteriophage would increase bacterial sensitivity to antibiotics.

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