Population Redistribution among Multiple Electronic States of Molecular Nitrogen Ions in Strong Laser Fields

We carry out a combined theoretical and experimental investigation on the population distributions in the ground and excited states of tunnel ionized N2 molecules at various driver wavelengths in the near- and mid-infrared range. Our results reveal that efficient couplings (i.e., population exchanges) between the ground state and the excited states occur in strong laser fields. The couplings result in the population inversion between the ground and the excited states at the wavelengths near 800 nm, which is verified by our experiment by observing the amplification of a seed at ~391 nm. The result provides insight into the mechanism of free-space nitrogen ion lasers generated in remote air with strong femtosecond laser pulses.Comment: 18 pages, 4 figure

Soil microbial community parameters affected by microplastics and other plastic residues

Introduction: The impact of plastics on terrestrial ecosystems is receiving increasing attention. Although of great importance to soil biogeochemical processes, how plastics influence soil microbes have yet to be systematically studied. The primary objectives of this study are to evaluate whether plastics lead to divergent responses of soil microbial community parameters, and explore the potential driving factors. Methods: We performed a meta-analysis of 710 paired observations from 48 published articles to quantify the impact of plastic on the diversity, biomass, and functionality of soil microbial communities. Results and discussion: This study indicated that plastics accelerated soil organic carbon loss (effect size = −0.05, p = 0.004) and increased microbial functionality (effect size = 0.04, p = 0.003), but also reduced microbial biomass (effect size = −0.07, p < 0.001) and the stability of co-occurrence networks. Polyethylene significantly reduced microbial richness (effect size = −0.07, p < 0.001) while polypropylene significantly increased it (effect size = 0.17, p < 0.001). Degradable plastics always had an insignificant effect on the microbial community. The effect of the plastic amount on microbial functionality followed the “hormetic dose–response” model, the infection point was about 40 g/kg. Approximately 3564.78 μm was the size of the plastic at which the response of microbial functionality changed from positive to negative. Changes in soil pH, soil organic carbon, and total nitrogen were significantly positively correlated with soil microbial functionality, biomass, and richness (R2 = 0.04–0.73, p < 0.05). The changes in microbial diversity were decoupled from microbial community structure and functionality. We emphasize the negative impacts of plastics on soil microbial communities such as microbial abundance, essential to reducing the risk of ecological surprise in terrestrial ecosystems. Our comprehensive assessment of plastics on soil microbial community parameters deepens the understanding of environmental impacts and ecological risks from this emerging pollution

Soil microbial community parameters affected by microplastics and other plastic residues

IntroductionThe impact of plastics on terrestrial ecosystems is receiving increasing attention. Although of great importance to soil biogeochemical processes, how plastics influence soil microbes have yet to be systematically studied. The primary objectives of this study are to evaluate whether plastics lead to divergent responses of soil microbial community parameters, and explore the potential driving factors.MethodsWe performed a meta-analysis of 710 paired observations from 48 published articles to quantify the impact of plastic on the diversity, biomass, and functionality of soil microbial communities.Results and discussionThis study indicated that plastics accelerated soil organic carbon loss (effect size = −0.05, p = 0.004) and increased microbial functionality (effect size = 0.04, p = 0.003), but also reduced microbial biomass (effect size = −0.07, p &lt; 0.001) and the stability of co-occurrence networks. Polyethylene significantly reduced microbial richness (effect size = −0.07, p &lt; 0.001) while polypropylene significantly increased it (effect size = 0.17, p &lt; 0.001). Degradable plastics always had an insignificant effect on the microbial community. The effect of the plastic amount on microbial functionality followed the “hormetic dose–response” model, the infection point was about 40 g/kg. Approximately 3564.78 μm was the size of the plastic at which the response of microbial functionality changed from positive to negative. Changes in soil pH, soil organic carbon, and total nitrogen were significantly positively correlated with soil microbial functionality, biomass, and richness (R2 = 0.04–0.73, p &lt; 0.05). The changes in microbial diversity were decoupled from microbial community structure and functionality. We emphasize the negative impacts of plastics on soil microbial communities such as microbial abundance, essential to reducing the risk of ecological surprise in terrestrial ecosystems. Our comprehensive assessment of plastics on soil microbial community parameters deepens the understanding of environmental impacts and ecological risks from this emerging pollution

Magnetic field regression using artificial neural networks for cold atom experiments

Accurately measuring magnetic fields is essential for magnetic-field sensitive experiments in fields like atomic, molecular, and optical physics, condensed matter experiments, and other areas. However, since many experiments are conducted in an isolated vacuum environment that is inaccessible to experimentalists, it can be challenging to accurately determine the magnetic field. Here, we propose an efficient method for detecting magnetic fields with the assistance of an artificial neural network (NN). Instead of measuring the magnetic field directly at the desired location, we detect magnetic fields at several surrounding positions, and a trained NN can accurately predict the magnetic field at the target location. After training, we achieve a relative error of magnetic field magnitude (magnitude of error over the magnitude of magnetic field) below 0.3$\%$, and we successfully apply this method to our erbium quantum gas apparatus. This approach significantly simplifies the process of determining magnetic fields in isolated vacuum environments and can be applied to various research fields across a wide range of magnetic field magnitudes.Comment: 7 pages, 4 figure

Catalytic Conversion of 5-Hydroxymethylfurfural and Fructose to 5-Ethoxymethylfurfural over Sulfonated Biochar Catalysts

5-Hydroxymethylfurfural (HMF) is a key platform compound that can be produced by the dehydration of typical carbohydrates like glucose and fructose. Among the derivatives of HMF, 5-ethoxymethylfurfural (EMF) is the etherification product of HMF with ethanol. Owing to some advantages (i.e., high energy density), EMF has been regarded as a potential liquid fuel. Therefore, catalytic conversion of   HMF and fructose to EMF is of significance, especially using heterogeneous catalysts. In this paper, we demonstrated the preparation of biomass-based catalysts for the synthesis of EMF from HMF and fructose. Some sulfonated biochar catalysts were prepared by the carbonization of biomass-based precursors at high temperature in N2, followed by the subsequent sulfonation process employing concentered H2SO4 as sulfonation reagent. The obtained catalysts were characterized by scanning electron microscope (SEM), Fourier transform infrared spectrometer (FT-IR), X-ray diffraction (XRD), and element analysis. The catalytic conversion of HMF to EMF was carried out in ethanol, providing a 78% yield with complete conversion at 120 °C. The catalytic activity of the used catalyst showed slight decrease for the etherification of HMF. Moreover, the catalysts were effective for the direct conversion of fructose towards EMF in 64.9% yield. Copyright © 2023 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0)

Attention-controlled assistive wrist rehabilitation using a low-cost EEG sensor

It is essential to make sure patients be actively involved in motor training using robot-assisted rehabilitation to achieve better rehabilitation outcomes. This paper introduces an attention-controlled wrist rehabilitation method using a low-cost EEG sensor. Active rehabilitation training is realized using a threshold of the attention level measured by the low-cost EEG sensor as a switch for a flexible wrist exoskeleton assisting wrist flexion/extension and radial/ulnar deviation. We present a prototype implementation of this active training method and provide a preliminary evaluation. The feasibility of the attention-based control was proven with the overall actuation success rate of 95%. The experimental results also proved that the visual guidance was helpful for the users to concentrate on the wrist rehabilitation training: two types of visual guidance, namely, looking at the hand motion shown on a video and looking at the user's own hand had no significant performance difference. A general threshold of a certain group of users can be utilized in the wrist robot control rather than a customized threshold to simplify the procedure