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In brain-computer interface (BCI) systems, challenges are presented by the recognition of motor imagery (MI) brain signals. Established recognition approaches have achieved favorable performance from patterns like SSVEP, AEP, and P300, whereas the classification methods for MI need to be improved. Hence, seeking a classification method that exhibits high accuracy and robustness for application in MI-BCI systems is essential. In this study, the Sparrow search algorithm (SSA)-optimized Deep Belief Network (DBN), called SSA-DBN, is designed to recognize the EEG features extracted by the Empirical Mode Decomposition (EMD). The performance of the DBN is enhanced by the optimized hyper-parameters obtained through the SSA. Our method's efficacy was tested on three datasets: two public and one private. Results indicate a relatively high accuracy rate, outperforming three baseline methods. Specifically, on the private dataset, our approach achieved an accuracy of 87.83%, marking a significant 10.38% improvement over the standard DBN algorithm. For the BCI IV 2a dataset, we recorded an accuracy of 86.14%, surpassing the DBN algorithm by 9.33%. In the SMR-BCI dataset, our method attained a classification accuracy of 87.21%, which is 5.57% higher than that of the conventional DBN algorithm. This study demonstrates enhanced classification capabilities in MI-BCI, potentially contributing to advancements in the field of BCI. [ABSTRACT FROM AUTHOR]

The identification of phosphorus (P) fractions is essential for understanding the transformation and availability of P in paddy soils. To investigate the soil P fractions associated with soil properties under long-term fertilization, we selected three fertilization treatments, including no fertilization (CK), chemical fertilizers (NPK) and chemical fertilizers combined with manure (NPKM), from three long-term experiments located in Nanchang (NC), Jinxian (JX) and Ningxiang (NX). The results showed that chemical fertilizers combined with manure (NPKM) significantly (P ≤ 0.05) increased the soil total phosphorus, Olsen P and soil organic matter (SOM) by 2, 3 and 1 times, respectively, compared with the NPK treatment, and by 4, 17 and 2 times, respectively, compared with the CK treatment. NPKM significantly increased the grain yield compared with CK and NPK at all sites. The apparent P balance with NPK was higher in NC and NX but lower in JX compared with NPKM. Hedley fractionation revealed the predominance of most of the organic and inorganic phosphorus (Po and Pi) fractions with long-term fertilization, especially with the NPKM treatment, at all sites. The nonlabile P pool decreased by 14% and 18% whereas the moderately labile P pool proportions increased by 3 and 6 times with the NPK and NPKM treatments, respectively, compared to the CK treatment. The labile P pool showed a significant positive relationship with the SOM, total P and Olsen P contents. The moderately labile P was positively correlated with the total P and Olsen P. A significant positive correlation was observed between soil pH and the nonlabile P pool. Redundancy analysis revealed that the moderately labile P fraction (HCl dil. Pi fraction) was remarkably increased by the NPKM treatment and significantly correlated with the soil pH and total P concentration. The labile P fraction (NaHCO3-Pi) showed a strong relationship with the Olsen P and total P. However, the residual P fraction was negatively correlated with the HCl. dil. Pi fraction. We concluded that NPKM application improved P availability by many folds compared to NPK, which could lead to environmental pollution; therefore, the rate of combined application of manure and chemical fertilizer should be reduced compared to chemical fertilizer inputs to minimize the wastage of resources and environmental P losses.

The microbial fermentation of plants is a promising approach for enhancing the yield of polysaccharides with increased activity. In this study, ten microbial strains, Lactiplantibacillus plantarum CCFM8661, Limosilactobacillus reuteri CCFM8631, Lactobacillus helveticus M10, Lacticaseibacillus rhamnosus CCFM237, Lactilactobacillus sakei GD17-9, Lacticaseibacillus casei CCFM1073, Bacillus subtilis CCFM1162, Bacteroides cellulosilyticus FTJSI-E-2, Bacteroides stercoris FNMHLBEIK-4, and Saccharomyces cerevisiae HN7-A5, were used to ferment Dendrobium officinale. The skin care activity of the resulting polysaccharides (F-DOP) was evaluated in cultured HaCaT and RAW 264.7 cells, and a mouse model. The results indicated that D. officinale medium promoted strain proliferation, and fermentation significantly enhanced polysaccharide yield (up to 1.42 g/L) compared to that without fermentation (0.76 g/L). Moreover, F-DOPs, especially after CCFM8631 fermentation, exhibited an excellent ability to attenuate sodium dodecyl sulfate-induced HaCaT cell injury (from 69.04 to 94.86%) and decrease nitric oxide secretion (from 42.86 to 22.56 μM) in lipopolysaccharide-stimulated RAW 264.7 cells. In vivo, CCFM8631-FDOP reduced the transdermal water loss rate, skin epidermal thickness, and interleukin 6, and enhanced the expression of filaggrin, improving 2,4-dinitrofluorobenzene-induced skin damage. Therefore, considering viable cell counts, polysaccharide yields, and skin care efficacy in vitro and in vivo, CCFM8631 is the most suitable strain to enhance the skin care activity of DOPs and possesses promising potential for applications in the cosmetics industry. [ABSTRACT FROM AUTHOR]

The coffee shell waste produced by the processing of Yunnan Arabica Coffee was used as raw material, and its hydrothermal liquefaction was catalyzed by iron and the liquefaction products were extracted by solvent to obtain the coffee shell bio-oils and the residual biochars. The light bio-oil extracted from the aqueous phase with ether and the heavy bio-oil extracted from the solid phase with ethanol were analysed by gas chromatography-mass spectrometry. It was identified that the light oil yield was around 7%, mainly containing more than 50% furfural and its derivatives, more than 10% phenol and its derivatives, while heavy oil yield was around 14%, mainly containing 36.19% caffeine, 41.3% fatty acids and other substances. The solid residue was a biochar rich in oxygen-containing functional groups and uniformly embedded with nano-zero valent iron, which had the performance of catalyzing the oxidative degradation of tetracycline by persulfate, and the biochar could remove about 80% of tetracycline in water within 150 min. [ABSTRACT FROM AUTHOR]