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In this work, steam explosion (SE) was applied to prompt the rapid extraction of ergosterol and polysaccharides from Flammulina velutipes root (FVR) waste. Ultrasound-assisted saponification extraction (UASE) followed by water extraction was used to prepare ergosterol and polysaccharides. The results indicated that SE destroyed the complicated structure of FVR and increased its internal porosity and surface roughness. SE caused the thermal degradation of FVR’s structural components and increased the polysaccharide content 0.97-fold. As a result, the extraction yield and efficiency of ergosterol and polysaccharides were improved. The theoretical maximum extraction concentration (C∞) and diffusion coefficient (D) were increased by 34.10% and 78.04% (ergosterol) and 27.69% and 48.67% (polysaccharides), respectively. The extraction yields obtained within 20–30 min of extraction time exceeded those of untreated samples extracted after several hours. For polysaccharides, SE led to a significant reduction in the average molecular weight, increased the percentage of uronic acids and decreased the neutral sugar percentage. The monosaccharide composition was changed by SE, with an increase in the molar ratio of glucose of 64.06% and some reductions in those of other monosaccharides. This work provides an effective method for the processing of fungi waste and adds to its economic value, supporting its high-value utilization in healthcare products.

Canine distemper virus (CDV) can cause fatal infections in giant pandas. Vaccination is crucial to prevent CDV infection in giant pandas. In this study, two bacterium-like particle vaccines F3-GEM and H4-GEM displaying the trimeric F protein or tetrameric H protein of CDV were constructed based on the Gram-positive enhanced-matrix protein anchor (GEM-PA) surface display system. Electron microscopy and Western blot results revealed that the F or H protein was successfully anchored on the surface of GEM particles. Furthermore, one more bacterium-like particle vaccine F3 and H4-GEM was also designed, a mixture consisting of F3-GEM and H4-GEM at a ratio of 1:1. To evaluate the effect of the three vaccines, mice were immunized with F3-GEM, H4-GEM or F3 and H4-GEM. It was found that the level of IgG-specific antibodies and neutralizing antibodies in the F3 and H4-GEM group was higher than the other two groups. Additionally, F3 and H4-GEM also increased the secretion of Th1-related and Th2-related cytokines. Moreover, F3 and H4-GEM induce IgG and neutralizing antibodies’ response in dogs. Conclusions: In summary, F3 and H4-GEM can provoke better immune responses to CDV in mice and dogs. The bacterium-like particle vaccine F3 and H4-GEM might be a potential vaccine candidate for giant pandas against CDV infection.

Concerning the vision of achieving carbon neutral and peak carbon goals, wind energy is extremely important as a renewable and clean energy source. However, existing research ignores the implicit features of the data preprocessing technique and the role of the internal mechanism of the optimization algorithm, making it difficult to achieve high-accuracy prediction. To fill this gap, this study proposes a wind speed forecasting model that combines data denoising techniques, optimization algorithms, and machine learning algorithms. The model discusses the important parameters in the data decomposition technique, determines the best parameter values by comparing the model’s performance, and then decomposes and reconstructs the wind speed time series. In addition, a novel optimization algorithm is used to optimize the parameters of the machine learning algorithm using a waiting strategy and an aggressive strategy to improve the effectiveness of the model. Several control experiments were designed and implemented using 10-min wind speed data from three sites in Penglai, Shandong Province. Based on the numerical comparison results and the discussion of the proposed model, it is concluded that the developed model can obtain high accuracy and reliability of wind speed prediction in the short term relative to other comparative models and can have further applications in wind power plants.

The converter transformer is the core equipment of HVDC transmission system, the valve-side winding of which needs to withstand DC voltage. Partial discharge is one of the main threats to the safe operation of converter transformer, yet the characteristics of partial discharge development of the oil-pressboard insulations under constant DC voltage are insufficiently understood. In order to better understand the partial discharge characteristics of the oil-pressboard insulation under DC voltage and provide deeper theoretical support for insulation diagnosis of converter transformers, development characteristics including the time-varying tendency of discharge magnitude and repetition rate of partial discharge in oil-pressboard insulation under constant positive and negative DC voltage were studied. The results indicate that the development of partial discharge in a needle-plane oil-pressboard insulation model under constant DC voltage has three stages: the intensive discharging stage, the silent-burst stage, and the breakdown stage. Throughout all stages, the partial discharge magnitude and repetition rate first decrease and increase afterwards. At the silent-burst stage, the partial discharge appears in the form of a “cluster” with very large magnitude and repetition rate. Each cluster exists for tens of seconds but with at a very long interval with each other. Further analysis shows that the repeated accumulation and dissipation of free charges on the surface of the pressboard cause the above phenomena. Negative charges are easy to accumulate and difficult to dissipate under the same voltage amplitude compared to positive charges, leading to a weaker actual electric field at the needle tip and thus partial discharges under negative DC voltage with a lower magnitude and longer interval.

The study investigated the extrusion modification of wheat bran and its effects on structural and rheological properties of wheat flour dough. Extruded bran showed better solubility of dietary fiber and structural porosity, leading to higher hydration and swelling power. Addition of extruded bran to dough caused water redistribution as an intensive aggregation of bound water to gluten matrix with reduced mobility. The bran–gluten interaction influenced by water sequestering caused partial gluten dehydration and conversion of β-turn into β-sheet, which demonstrated the formation of a more polymerized and stable gluten network. Farinographic data confirmed the promotion of dough stability with extruded bran addition at lower gluten content, while viscoelastic data suggested improved dough elasticity at all gluten contents by increasing elastic moduli and decreasing loss tangent. This study would be useful for interpreting the modification effect and mechanism of extrusion on cereal brans and provide valuable guidance for applying it as an effective modification technology on the commercial production of cereal bran and its flour products.

A purified polysaccharide, designated as SE-WGPI, was isolated from wheat germ modified by steam explosion. The primary structure characteristics were determined by HPGPC, GC, periodate oxidation-Smith degradation, methylation analysis, FT-IR, NMR and Congo red test. The results showed that SE-WGPI was a homogeneous hetero-polysaccharide with the average molecular weight of 5.6 × 103 Da. The monosaccharide composition mainly consisted of glucose, arabinose and xylose with a molar ratio of 59.51: 20.71: 19.77. The main backbone of SE-WGPI consisted of →4,6)-α-D-Glcp(1→6)-α-D-Glcp(1→3)-β-D-Xylp(1→5)-α-L-Araf(1→ and the side chain was α-D-Glcp(1→ linked at the C4-position of →4,6)-α-D-Glcp(1→. SE-WGPI likely has a complex netted structure with triple helix conformation and good thermal stability. In addition, SE-WGPI had valid in vitro radical scavenging activities on DPPH and hydroxyl radicals. This study may provide structural information of SE-WGPI for its promising application in the fields of functional foods or medicines.

Although some traditional autoencoders and their extensions have been widely used in the research of intelligent fault diagnosis of rotating parts, their feature extraction capabilities are limited without label information. In response to this problem, this research proposes a hierarchical sparse discriminant autoencoder (HSDAE) method for fault diagnosis of rotating components, which is a new semi-supervised autoencoder structure. By considering the sparsity of autoencoders, a hierarchical sparsity strategy was proposed to improve the stacked sparsity autoencoders, and the particle swarm optimization algorithm was used to obtain the optimal sparsity parameters to improve network performance. In order to enhance the classification of the autoencoder, a class aggregation and class separability strategy was used, which is an additional discriminative distance that was added as a penalty term in the loss function to enhance the feature extraction ability of the network. Finally, the reliability of the proposed method was verified on the bearing data set of Case Western Reserve University and the bearing data set of the laboratory test platform. The results of comparison with other methods show that the HSDAE method can enhance the feature extraction ability of the network and has reliability and stability for different data sets.

Due to the mechanical equipment working under variable speed and load for a long time, the distribution of samples is different (domain shift). The general intelligent fault diagnosis method has a good diagnostic effect only on samples with the same sample distribution, but cannot correctly predict the faults of samples with domain shift in a real situation. To settle this problem, a new intelligent fault diagnosis method, domain adaptation network with double adversarial mechanism (DAN-DAM), is proposed. The DAN-DAM model is mainly composed of a feature extractor, two label classifiers and a domain discriminator. The feature extractor and the two label classifiers form the first adversarial mechanism to achieve class-level alignment. Moreover, the discrepancy between the two classifiers is measured by Wasserstein distance. Meanwhile, the feature extractor and the domain discriminator form the second adversarial mechanism to realize domain-level alignment. In addition, maximum mean discrepancy (MMD) is used to reduce the distance between the extracted features of two domains. The DAN-DAM model is verified by multiple transfer experiments on some datasets. According to the transfer experiment results, the DAN-DAM model has a good diagnosis effect for the domain shift samples. Moreover, the diagnostic accuracy is generally higher than other mainstream diagnostic methods.

The angular non-critical phase-matching (A-NCPM) second-harmonic-generation (SHG) properties of RE1xRE21−xCOB (RE1, RE2 = Y, Gd, La, Tm, Sm, and Nd) type mixed crystals including NCPM wavelength and conversion efficiency were detailedly investigated. Theoretical calculations manifest that the A-NCPM SHG scope of these crystals is 0.72~1.42 µm, and in experiments, the A-NCPM SHG waveband of 0.72~1.25 µm has been realized, by changing the ratio of the rare-earth elements RE1 and RE2 in RE1xRE21−xCOB crystals. Comparing to the temperature-dependent A-NCPM SHG of 0.95~1.34 µm in LiB3O5 (LBO) crystal, the composition-dependent A-NCPM SHG of 0.72~0.95 µm in RE1xRE21−xCOB type crystals is unique and has special significance for the frequency conversion of Ti:Sapphire lasers. Relationships between the birefringence and radius of rare-earth ion RE3+ in RE1xRE21−xCOB mixed crystals were discussed. Aiming for the A-NCPM SHG of 0.72~1.42 µm, we supply a clear, completed, and optimized solution on how to select the compositions of RE1xRE21−xCOB mixed crystals. Under focusing light beam conditions, high efficient A-NCPM SHG for both OPO and Ti:sapphire lasers were realized experimentally by using long Y- and Z-cut RE1xRE21−xCOB crystal samples.

In this paper, the partial eigenvalue assignment problem of gyroscopic second-order systems with time delay is considered. We propose a multi-step method for solving this problem in which the undesired eigenvalues are moved to desired values and the remaining eigenvalues are required to remain unchanged. Using the matrix vectorization and Hadamard product, we transform this problem into a linear systems of lower order, and analysis the computational costs of our method. Numerical results exhibit the efficiency of our method.

Frequently occurring fatty liver disease in dairy cows during the perinatal period, a typical type of non-alcoholic fatty liver disease (NAFLD), results in worldwide high culling rates of dairy cows (averagely about 25%) after calving. This has been developing into a critical industrial problem throughout the world, because the metabolic disease severely affects the welfare and economic value of dairy cows. Findings about the molecular mechanisms how the fatty liver disease develops would help scientists to discover novel therapeutic targets for NAFLD. Studies have shown that PPARγ participates or regulates the fat deposition in liver by affecting the biological processes of hepatic lipid metabolism, insulin resistance, gluconeogenesis, oxidative stress, endoplasmic reticulum stress and inflammation, which all contribute to fatty liver. This review mainly focuses on crucial regulatory mechanisms of PPARγ regulating lipid deposition in the liver via direct and/or indirect pathways, suggesting that PPARγ might be a potential critical therapeutic target for fatty liver disease, however, it would be of our significant interest to reveal the pathology and pathogenesis of NAFLD by using dairy cows with fatty liver as an animal model. This review will provide a molecular mechanism basis for understanding the pathogenesis of NAFLD.

Accurate wind power and wind speed forecasting remains a critical challenge in wind power systems management. This paper proposes an ultra short-time forecasting method based on the Takagi−Sugeno (T−S) fuzzy model for wind power and wind speed. The model does not rely on a large amount of historical data and can obtain accurate forecasting results though efficient linearization. The proposed method employs meteorological measurements as input. Next, the antecedent and the consequent parameters of the forecasting model are identified by the fuzzy c-means clustering algorithm and the recursive least squares method. From these components, the T−S fuzzy model is obtained. Wind farms located in China (Shanxi Province) and in Ireland (County Kerry) are considered as cases with which to validate the proposed forecasting method. The forecasting results are compared with results from the contemporary machine learning-based models including support vector machine (SVM), the combined model of SVM and empirical mode decomposition, and back propagation neural network methods. The results show that the proposed T−S fuzzy model can effectively improve the precision of the short-term wind power forecasting.

To explore the potential for further enhancing the gas mixing uniformity of natural gas (NG) engines, this paper identifies turbulent kinetic energy (TKE), which has an essential impact on gas mixing, as the entry point of the research. After establishing a computational fluid dynamics (CFD) model for NG engines’ direct injection and mixing processes, the inlet pressure is selected as the experimental variable to investigate the influence of TKE on gas mixing uniformity. In particular, by proposing the theoretical concept of the core mixing stage, the numerical variation rule between the best mixture concentration region (BMCR) percentage and the mean turbulent kinetic energy (MTKE) of the core mixing stage is analyzed under certain injection timing conditions. The results indicate that, with identical intake pressures, an advanced gas injection timing elevates the total turbulence kinetic energy (TTKE) during the core mixing stage, thereby amplifying the uniformity of the gas mixture at the ignition. In specific scenarios, as the intake pressure increases, the decreasing trend in the BMCR proportion closely resembles the diminishing trend in the MTKE during the core mixing stage. Scrutinizing the variation trend in either parameter allows for an approximate prediction of the variation trend in the other parameter. When the intake pressure is gradually raised from the naturally aspirated state, the adequacy of the gas jet development is progressively reduced by the increasing back pressure in the cylinder.

Three new Aceria species from South China are described and illustrated. Aceria bischofiaesp. nov. was collected on Bischofia javanica Blume (Phyllanthaceae), inducing galls on surfaces of the leaves; Aceria cryptocaryaesp. nov. was collected on Cryptocarya metcalfiana Allen (Lauraceae), causing the formation of erinea on the undersurface of the leaves; and Aceria buddlejaesp. nov. was collected as a vagrant on Buddleja lindleyana Fort. (Scrophulariaceae) leaves, and no symptoms were observed on the host plant.

The nitrogen isotopic compositions of lunar soil have important implications for the sources of lunar volatiles and even the evolution of the moon. At present, the research on the lunar nitrogen isotopic compositions is mainly based on the lunar meteorites and the samples brought back by the Apollo and Luna missions. However, volatiles adsorbed on the surface of the lunar soil may be lost due to changes in temperature and pressure, as well as vibration and shock effects when the sample is returned. At the same time, in the case of low N content in the sample, since N is the main component of the earth’s atmosphere, it is easily affected by the atmosphere during the analysis process. Therefore, in situ nitrogen isotopic analysis of lunar soil on orbit is necessary to avoid the problems mentioned above and is one of the primary science goals for the Lunar Soil Volatile Measuring instrument on Chang’e-7 spacecraft. After the nitrogen purification procedure, the volatiles in lunar soil that are released through single-step or stepped heating techniques diffuse to the quadrupole mass spectrometer to obtain the N contents and isotopic compositions of the lunar soil. This paper introduces the ground test for N isotopic analysis of lunar soil in orbit according to the Lunar Soil Volatile Measuring Instrument. After long-term repeated measurements, the background and CO-corrected Air-STD 14N/15N ratio is 268.986 ± 4.310 (1SD, n = 35), and the overall reproducibility of measurements is 1.6%. The accuracy of N isotopic compositions is calculated to be better than 5%, which can distinguish different sources of N components in lunar soil.

According to the big impact hypothesis, the moon should be very dry. However, more and more evidence from the remote sensing of the moon in recent years indicates that there is a lot of water in the moon’s polar regions. Researching the source and distribution of volatiles such as water can provide a key constraint on the formation and evolution of the moon. If there is a large amount of a volatile such as water ice in the polar area of the moon, it can be used as a further resource. Regrettably, there are no detectors in place to detect the amount and presence of water to date. In the new wave of lunar exploration, polar water has become one of the main tasks of NASA, ESA and RKA. The Chang’e-7 spacecraft of China’s fourth lunar exploration phase has also used the Water Molecular Analyzer and the Lunar Soil Volatile Measuring Instrument to detect water content in the lunar polar region. This paper introduces a set of methods and principles for analyzing water content via the heat flux method according to the characteristics of the Lunar Soil Volatile Measuring Instrument that was deployed on the lunar surface. According to the current design, the water content of 0.008~0.17% can be analyzed.

Formaldehyde (FA) is a toxic compound that is considered to have a carcinogenic effect due to its damage to biological macromolecules. However, the influence of FA at the protein level remains to be explored. Here, we used LC-MS/MS to identify the differentially expressed proteins and modifications to proteins between FA-treated and untreated HeLa cells. Among 2021 proteins identified, 196 proteins were significantly down-regulated and 152 up-regulated. The differentially expressed proteins were further analyzed using bioinformatics tools for annotating the characterization of their localizations and functions. To evaluate the interaction of FA with proteins, we performed proteomic analysis for a mass shift of 12 Da on the side chains of lysine, cysteine and tryptophan, which are induced by FA as noticeable signals. We identified the modified proteins and sites, suggesting direct interaction between FA and proteins. Motif analysis further showed the characterization of amino acid sequences that react with FA. Cluster analysis of the modified proteins indicated that the FA-interacting networks are mostly enriched in the nuclei, ribosomes and metabolism. Our study presents the influence of FA on proteomes and modifications, offering a new insight into the mechanisms underlying FA-induced biological effects.

The effects that maternal dietary methionine have on progeny have been reported on broilers. However, the paternal effects are not known, so the current study was conducted to explore the influences of paternal dietary methionine (Met) have on progeny carcass traits, meat quality, and related gene expressions. A total of 192 hens and 24 roosters from Ross parent stock at 36 weeks of age were selected. From week 37 to 46, the roosters were allocated to two groups with three replicates of 4 cocks each, (control, 0.28% Met), and methionine group (MET group, 0.28% Met + 0.1% coated Met). The results revealed that, although the heavier live body weight in progeny at day 49 of control group compared to MET group (p < 0.05), the relative eviscerated yield and relative thigh muscle yield were higher in MET group (p < 0.05); but the relative abdominal fat was lower (p < 0.05). In thigh and breast muscles, a positive response of pH24 h value, shear force (g) and drip loss (%) were observed in MET group (p < 0.05). The lightness (L) and redness (a) were increased (p < 0.05) in breast muscles of MET group, while only the redness (a*24 h) and yellowness (b*24 h) were increased (p < 0.05) in thigh muscles of MET group. The gender has a significant (p < 0.05) effect on carcass traits and muscle redness (a*), where these traits improved in males, and no interaction between treatments and gender were observed for these results. The expression levels of PRKAG2 and PRDX4 supported the changes in muscle pH, with these up-regulated in thigh and breast muscles of MET group, the PPP1R3A gene supported the changes in pH value being down-regulated (p < 0.01) in these same muscles. The BCO1 gene expression was consistent with the changes in meat color and was up-regulated (p < 0.01) in thigh muscles of MET group, consistent with the changes in b* color values. Finally, it was concluded that the supplementation of 0.1% Met to rooster diets could improve carcass characteristics and meat quality of progeny.

Presently, the heterophil-to-lymphocyte (H/L) ratio is being studied extensively as a disease resistance trait. Through intricate mechanisms to identify and destroy pathogenic microorganisms, heterophils play a pivotal role in the immune defense systems of avian species. To reveal the genetic basis and molecular mechanisms affecting the H/L ratio, phenotypic and H/L data from 1650 white feather chicken broilers were used in performing a genome-wide association study. A self-developed, chicken-specific 55K chip was used for heterophils, lymphocytes, and H/L classification, according to individual genomic DNA profiles. We identified five significant single nucleotide polymorphisms (SNPs) when the genome-wide significance threshold was set to 5% (p < 2.42 × 10−6). A total of 15 SNPs obtained seemingly significant levels (p < 4.84 × 10−5). Gene annotation indicated that CARD11 (Caspase recruitment domain family member 11), BRIX1 (Biogenesis of ribosomes BRX1), and BANP (BTG3 associated nuclear protein) play a role in H/L-associated cell regulation and potentially constitute candidate gene regions for cellular functions dependent on H/L ratios. These results lay the foundation for revealing the genetic basis of disease resistance and future marker-assisted selection for disease resistance.

Based on the results of our previous genome-wide association study (GWAS), a comprehensive analysis on single nucleotide polymorphisms (SNPs) was performed on White Leghorn and Beijing-You chickens with high and low IgY levels in defined genomic regions using the capture-sequencing approach. High and low IgY chickens showed substantial genetic variations. In total, more than 30,000 SNPs were found in all four chicken groups, among which 1045 were non-synonymous mutations resulting in amino acids alterations. In total, 23,309 Indels were identified. Among the 1169 Indels that were found only in Beijing-You chickens, 702 were shared between high and low IgY chickens compared with the reference genome. There were 1016 Indels specific to the White Leghorn chickens, among which 188 were high IgY-specific, 134 were low IgY-specific and 694 were shared between the high and low IgY chicken lines. Many genetic mutations were located in the regulatory regions of important immunomodulatory genes, including TAP1, TAP2 and BF1. Our findings provide an in-depth understanding of genetic mutations in chicken microchromosomes.