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P2-Na0.67Ni0.33Mn0.67O2 is a promising cathode for sodium-ion batteries in large-scale energy storage applications due to their advantages of low cost, high energy density, superior sodium ion conductivity, and good air stability, whereas their structural rearrangement at high voltage above 4.2 V and the appearance of Na+/vacancy ordering result in fast capacity decay and poor rate capability, which lead to unsatisfactory performance that fails to meet practical demands. In this paper, we propose a dual-ion doping strategy coupling both cations and anions. Thanks to their collaborative effect, the optimized cathode material P2-Na0.67Ni0.33Mn0.57Ti0.1O1.95F0.05 exhibits greatly improved stability in the voltage range of 2.3–4.3 V at a high rate. Specifically, it retains 79.59% of its initial capacity after 500 cycles at 5C, in contrast to 19.91% of the undoped material. Experimental and theoretical investigations on working mechanisms illustrate that Ti4+ and F− dual-ion doping effectively suppresses the P2–O2 phase transition and facilitates sodium ion diffusion kinetics. Moreover, a P2-Na0.67Ni0.33Mn0.57Ti0.1O1.95F0.05//hard carbon full cell delivers a high reversible capacity of 122 mA h g−1 with a high energy density of 365 W h kg−1 based on the mass of the cathode material. This study provides an efficient strategy to promote the application of layered oxide cathodes in practical sodium-ion batteries. [ABSTRACT FROM AUTHOR]

Oral diseases stemming from oral pathogenic bacteria pose a significant global health concern, and current methods for managing these pathogens have limitations. Plasma‐activated water (PAW), containing various reactive species, emerges as a promising disinfectant with impressive inactivation capabilities. In this study, PAW prepared by mixed‐mode plasma‐activated gases was applied to inactivate oral pathogenic bacteria, including Streptococcus mutans and Porphyromonas gingivalis. The PAW could reduce more than 6.1‐log10 planktonic bacteria and 4.1‐log10 bacteria within biofilm, respectively, and PAW treatment of planktonic bacteria effectively inhibited biofilm formation. Compared to chlorhexidine, PAW exhibited superior inactivation effects in both planktonic bacteria and biofilm. This study presented a potent strategy for bacteria eradication to reduce the incidence of oral diseases. [ABSTRACT FROM AUTHOR]

Plasma is highly efficient in the inactivation of microorganisms and is tried to be applied to the treatment of wounds. The gas activated by plasma, named plasma-activated gas, can also effectively inactivate microorganisms and get rid of the limitations of direct plasma treatment. However, the details of the interaction of plasma-activated gas on the tissue are still unclear. In this study, the agarose gel models in the presence of microorganisms to simulate the infected tissues were used to study the inactivation effects and mechanisms of plasma-activated gas. The inactivation depths in the gel models in the presence of microorganisms were related to the types of plasma-activated gas and the species of microorganisms. The Mixed-gas exhibited the strongest inactivation effects, and the inactivation depths in the gel models in the presence of bacteria were deeper than those in the presence of fungi. The long-lived species in the plasma-activated gas penetrated to more than 5.2 mm while the short-lived species only penetrated less than 2.3 mm, demonstrating the distinct roles of reactive species in the inactivation process. Moreover, the pig muscle was covered on the gel models to assess the penetration depths of the plasma-activated gas in muscle tissue and the focused plasma-activated gas could penetrate 1–1.5 mm of pig muscle. This study explored the inactivation effects and mechanisms on the gel models and the penetration depths in the real tissues of plasma-activated gas, which supplied the theoretical basis for the further application of plasma-activated gas in biomedical fields. [ABSTRACT FROM AUTHOR]

The canopy height model (CHM) derived from LiDAR point cloud data is usually used to accurately identify the position and the canopy dimension of single tree. However, local invalid values (also called data pits) are often encountered during the generation of CHM, which results in low-quality CHM and failure in the detection of treetops. For this reason, this paper proposes an innovative method, called "pixels weighted differential gradient", to filter these data pits accurately and improve the quality of CHM. First, two characteristic parameters, gradient index (GI) and Z-score value (ZV) are extracted from the weighted differential gradient between the pit pixels and their eight neighbors, and then GIs and ZVs are commonly used as criterion for initial identification of data pits. Secondly, CHMs of different resolutions are merged, using the image processing algorithm developed in this paper to distinguish either canopy gaps or data pits. Finally, potential pits were filtered and filled with a reasonable value. The experimental validation and comparative analysis were carried out in a coniferous forest located in Triangle Lake, United States. The experimental results showed that our method could accurately identify potential data pits and retain the canopy structure information in CHM. The root-mean-squared error (RMSE) and mean bias error (MBE) from our method are reduced by between 73% and 26% and 76% and 28%, respectively, when compared with six other methods, including the mean filter, Gaussian filter, median filter, pit-free, spike-free and graph-based progressive morphological filtering (GPMF). The average F1 score from our method could be improved by approximately 4% to 25% when applied in single-tree extraction. [ABSTRACT FROM AUTHOR]