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Post-weaning diarrhea is common in piglets, causing huge economic losses worldwide. Associations between LPS challenge, intestinal inflammation, and microbiota have been reported in Duroc × Landrace × Yorkshire (DLY) crossbred pigs. However, the effects of LPS challenge in other breeds remain unclear. In the current study, we performed a comprehensive comparative analysis of the effects of LPS challenge on jejunal mucosal morphology, jejunal microbial composition, and serum indexes in two pig breeds: DLY and Heigai, an indigenous Chinese breed. The results showed that LPS caused considerable damage to the mucosal morphology, enhanced serum levels of inflammatory cytokines and the intestinal permeability index, and lowered the antioxidant capacity index. LPS challenge also changed the microbial composition and structure of the jejunum, significantly increased the abundances of Escherichia-Shigella in DLY pigs, and decreased those of Gemella and Saccharimonadales in Heigai pigs. Furthermore, LPS challenge triggered functional changes in energy metabolism and activities related to the stress response in the jejunal bacterial community, alleviating the inflammatory response in Heigai pigs. This study also revealed that Heigai pigs had a weaker immune response to LPS challenge than DLY pigs, and identified several genera related to the breed-specific phenotypes of Heigai pigs, including Gemella, Saccharimonadales, Clostridia_UCG_014, Terrisporobacter, and Dielma. Our collective findings uncovered differences between Heigai and DLY pigs in intestinal inflammation and microbiota dysbiosis induced by LPS challenge, providing a theoretical basis for unraveling the mechanism of intestinal inflammation in swine and proposing microbial candidates involved in the resistance to diarrhea in piglets.

Intestinal microbiota has an important impact on pig phenotypes. Previous studies mainly focused on the microbiota of feces and worldwide farmed commercial pigs, while research on the microbiota of various intestinal sections and indigenous pig breeds is very limited. This study aimed to characterize and compare the biogeography of intestinal microbiota in pigs of one Chinese indigenous breed and one commercial crossbred. In this study, we sequenced the microbiota of six intestinal segments in the grown-up pigs of a Chinese indigenous breed, Laiwu pigs, and the worldwide farmed crossbred Duroc × Landrace × Yorkshire (DLY) pigs by 16S rRNA sequencing, characterized the biogeography of intestinal microbiota, and compared the compositional and functional differences between the two breeds. The results showed that there were obvious differences in microbial structure and abundance between the small and large intestines. Laiwu pigs had higher large intestinal diversity than DLY pigs, while DLY pigs had higher small intestinal diversity than Laiwu pigs. Moreover, some specific bacterial taxa and Kyoto Encyclopedia of Genes and Genomes pathways were found to be related to the high fat deposition and good meat quality of Laiwu pigs and the high growth speed and lean meat rate of DLY pigs. This study provides an insight into the shifts in taxonomic composition, microbial diversity, and functional profile of intestinal microbiota in six intestinal segments of Laiwu and DLY pigs, which would be essential for exploring the potential influence of the host’s genetic background on variation in microbiota composition and diversity.

In aerospace engine delivery systems, “one-in-two-out” bifurcation structures are commonly used for flow distribution to downstream pipelines. There are two common “one-in-two-out” bifurcation structures in aircraft engines: the planar orthogonal bifurcation and the spatial orthogonal bifurcation. By adjusting the flow supply upstream and the cross-sectional diameter downstream, the flow distribution in the two branches can be adjusted, i.e., the “splitting ratio” changes. In this paper, a dismantling and flexible experimental system is constructed to measure the pressure signals in each channel and use non-linear dynamic analysis methods to extract pressure characteristics. The particle image velocimetry (PIV) technique combined with the fine rope tracing technique is creatively used to observe the vortex structure in the cross section of the downstream branch. The study found that for spatial orthogonal bifurcation, the pressure signal characteristics in each channel are basically the same at larger splitting ratios, regardless of the chirality. As the splitting ratio decreases, the difference in pressure signal characteristics between the two branches gradually becomes evident and becomes related to the chirality. Moreover, unlike the planar orthogonal bifurcation structure, a complete large vortex structure has not been found in the downstream branch of the spatial orthogonal bifurcation structure, regardless of changes in the splitting ratio, and it is unrelated to the chirality.

The use of gas energy includes a wide range of applications to directly accelerate the liquid in a pipeline without the aid of mechanical equipment, such as marine gas-liquid jet propulsion. To clarify the characteristics of energy transfer by interphase forces for gas-liquid flows in variable cross-section tubes, two-fluid models of annular flow, bubbly flow and homogeneous flow were adopted, respectively, along with four newly elaborated coefficients, which are the work factor of gas fg, reflecting the relative ability of gas to power liquid, the interface work transfer coefficient kg (representing the relative magnitude of mechanical work received by liquid from gas), the interphase work-to-energy conversion coefficient kl (denoting the capability of energy transfer through work performed by interphase forces) and the interphase mechanical efficiency ηw. The results reveal the interphase work transfer is strongly influenced by the structural parameters of the tubes (or nozzles), and an optimized design is necessary to improve the performance. The higher the degree of gas dispersion in the liquid, the more advantageous the conversion of gas work into the liquid’s mechanical energy. Of these three flow patterns, annular flow has the lowest kl and ηw (kl = 0.0797, ηw = 0.9885 in present example), while homogeneous flow displays the limit of interphase mechanical energy conversion because the gas-liquid momentum coupling reaches the maximum (kl = 0.9979, ηw = 1).

Electromagnetically induced transparency (EIT) metamaterials (MTMs) based on the bright-dark mode theory have gained great interest in slow light, sensing, and energy storage in recent years. Typically, various split ring resonators with magnetic response have been proposed as dark resonators in EIT MTMs. Here, we have employed a cut-wire (CW) and two electric-field-coupled inductor-capacitor (ELC) resonators with a pure electrical response on a liquid crystal polymer (LCP) substrate with a low loss tangent to fulfill the EIT effect in the terahertz (THz) region. The former works as the bright mode, and the latter functions as the dark mode. The EIT phenomenon results from the destructive interference between these two modes, which can be verified by numerical simulation and near field distribution. In addition, a Lorentz oscillator model was studied to quantitatively analyze the relationship between the coupling strength and the coupling distance. As a demonstration, an EIT MTM device with 5000 units was fabricated and characterized, which showed a transmission window with a peak value of 0.75 at 0.414 THz. This work may inspire new multifunctional EIT MTMs, especially the flexible applications at THz frequencies.

Cylindrical ducts with axial mean temperature gradient and mean flows are typical elements in rocket engines, can combustors, and afterburners. Accurate analytical solutions for the acoustic waves of the longitudinal and transverse modes within these ducts can significantly improve the performance of low order acoustic network models for analyses of acoustic behaviours and combustion instabilities in these kinds of ducts. Here, we derive an acoustic wave equation as a function of pressure perturbation based on the linearised Euler equations (LEEs), and the modified WKB approximation method is applied to derive analytical solutions based on very few assumptions. The eigenvalue system is built based on the proposed solutions and applied to predict the resonant frequencies and growth rate for transverse modes. Validations of the proposed solutions are performed by comparing them to the numerical results directly calculated from the LEEs. Good agreements are found between analytical reconstruction and numerical results of three-dimensional transverse modes. The system with both mean temperature profile and mean flow presents a larger absolute value of the growth rate than the condition of either uniform mean temperature or no mean flow.

The bifurcation process of self-sustained combustion instability pressure perturbations in a liquid rocket combustor is investigated based on the Helmholtz equations and a pressure dependent flame describing function. The modal frequency and growth rates are numerically resolved by the commercial software COMSOL multiphysics. Validation of the numerical approach is firstly conducted on a Rijke tube combustor, and a supercritical bifurcation for the first longitudinal mode is observed. The bifurcation diagrams for the first transverse mode for different time delays and gain index of the flame describing function are analyzed. Only the supercritical bifurcation presents for this configuration. The trajectory of Hopf points and the bifurcation diagram feature period motions with increasing the time delay. The effect of flame length distributions on the bifurcation diagrams is analyzed by considering a non-uniform flame length distribution model. Results show that the distribution has a large impact on the bifurcation process, e.g., the first transverse mode is more unstable for the non-uniform distribution. Finally, a subcritical bifurcation is found when a more complicated flame describing function is considered; the bistable region presents and the condition for this is discussed.

Combustion instability is the biggest threat to the reliability of liquid rocket engines, whose prediction and suppression are of great significance for engineering applications. To predict the stability of a combustion chamber with a hypergolic propellant, this work used the method of decoupling unsteady combustion and acoustic system. The turbulence is described by the Reynolds-averaged Navier–Stokes technique, and the interaction of turbulence and chemistry interaction is described by the eddy-dissipation model. By extracting the flame transfer function of the combustion field, the eigenvalues of each acoustic mode were obtained by solving the Helmholtz equation, thereby predicting the combustion stability for the combustion chamber. By predictions of the combustion chamber instability with different flow rate distributions, it was found that the increasing of inlet flow rate amplitude will improve the stability or instability of combustion. The combustion stability of the chamber was optimized when the flow rate distribution for the oxidant was set more uniform in the radial direction. The heterogeneity of the flow rate distribution in the circumferential direction is not recommended, considering that a homogeneous flow rate distribution in the circumferential direction is beneficial to the combustion stability of the chamber.

Atherosclerosis is a chronic inflammatory arterial disease characterized by build-up of atheromatous plaque, which narrows the lumen of arteries. Hypercholesterolemia and excessive oxidative stress in arterial walls are among the main causative factors of atherosclerosis. Transient receptor potential channel M2 (TRPM2) is a Ca2+-permeable cation channel activated by oxidative stress. However, the role of TRPM2 in atherosclerosis in animal models is not well studied. In the present study, with the use of adeno-associated virus (AAV)-PCSK9 and TRPM2 knockout (TRPM2−/−) mice, we determined the role of TRPM2 in hypercholesterolemia-induced atherosclerosis. Our results demonstrated that TRPM2 knockout reduced atherosclerotic plaque area in analysis of En face Oil Red O staining of both whole aortas and aortic-root thin sections. Furthermore, TRPM2 knockout reduced the expression of CD68, α-SMA, and PCNA in the plaque region, suggesting a role of TRPM2 in promoting macrophage infiltration and smooth-muscle cell migration into the lesion area. Moreover, TRPM2 knockout reduced the expression of ICAM-1, MCP-1, and TNFα and decreased the ROS level in the plaque region, suggesting a role of TRPM2 in enhancing monocyte adhesion and promoting vascular inflammation. In bone-marrow-derived macrophages and primary cultured arterial endothelial cells, TRPM2 knockout reduced the production of inflammatory cytokines/factors and decreased ROS production. In addition, a TRPM2 antagonist N-(p-amylcinnamoyl) anthranilic acid (ACA) was able to inhibit atherosclerotic development in an ApoE−/− mouse model of atherosclerosis. Taken together, the findings of our study demonstrated that TRPM2 contributes to the progression of hypercholesterolemia-induced atherosclerosis. Mechanistically, TRPM2 channels may provide an essential link that can connect ROS to Ca2+ and inflammation, consequently promoting atherosclerotic progression.

This paper proposes a reversible data hiding scheme by exploiting the DGHV fully homomorphic encryption, and analyzes the feasibility of the scheme for data hiding from the perspective of information entropy. In the proposed algorithm, additional data can be embedded directly into a DGHV fully homomorphic encrypted image without any preprocessing. On the sending side, by using two encrypted pixels as a group, a data hider can get the difference of two pixels in a group. Additional data can be embedded into the encrypted image by shifting the histogram of the differences with the fully homomorphic property. On the receiver side, a legal user can extract the additional data by getting the difference histogram, and the original image can be restored by using modular arithmetic. Besides, the additional data can be extracted after decryption while the original image can be restored. Compared with the previous two typical algorithms, the proposed scheme can effectively avoid preprocessing operations before encryption and can successfully embed and extract additional data in the encrypted domain. The extensive testing results on the standard images have certified the effectiveness of the proposed scheme.

SiO2-Fe2O3-CaO (SFC) is believed to be the transition phase during the SiO2-Fe2O3-CaO-Al2O3 (SFCA) formation process. The effect of SiO2 on the mechanical property and reduction of the CaO-Fe2O3-SiO2 system was inspected in this study. Experiments were carried out under air at 1200 °C with different amounts of SiO2 mixed with Fe2O3 and CaO. The mechanical properties and reduction of samples were studied. Results indicate that the hardness of samples gradually increases with the increase of SFC content. That may be caused by SiO2 solid solution in calcium ferrite. The larger the amount and smaller size of acicular calcium ferrites in samples, the greater the fracture toughness. The solid solution of SiO2 in calcium ferrite is beneficial to decrease the initial reduction temperature. The apparent activation energy values of the samples with the different content of SiO2 from 0% to 5% are 167.23, 84.36, 87.90, 96.02, 92.44 and 107.83 kJ·mol−1, respectively. The microstructure of lump samples after reduction consists of four phases, i.e., CF (CaFe2O4), SFC, calcio-wüstite (CW) and Fe. It was not difficult to find the Fe in the samples reduced from CW. Scanning electron micrograph images have revealed that the acicular-like calcium ferrites are more easily reduced than the platy-like ones.

To enhance the classification accuracy of lower limb movements, a fusion recognition model integrating a surface electromyography (sEMG)-based convolutional neural network, transformer encoder, and long short-term memory network (CNN-Transformer-LSTM, CNN-TL) was proposed in this study. By combining these advanced techniques, significant improvements in movement classification were achieved. Firstly, sEMG data were collected from 20 subjects as they performed four distinct gait movements: walking upstairs, walking downstairs, walking on a level surface, and squatting. Subsequently, the gathered sEMG data underwent preprocessing, with features extracted from both the time domain and frequency domain. These features were then used as inputs for the machine learning recognition model. Finally, based on the preprocessed sEMG data, the CNN-TL lower limb action recognition model was constructed. The performance of CNN-TL was then compared with that of the CNN, LSTM, and SVM models. The results demonstrated that the accuracy of the CNN-TL model in lower limb action recognition was 3.76%, 5.92%, and 14.92% higher than that of the CNN-LSTM, CNN, and SVM models, respectively, thereby proving its superior classification performance. An effective scheme for improving lower limb motor function in rehabilitation and assistance devices was thus provided.

Land-use and land-cover changes in the Eastern European Plain have important implications for regional and global ecological environments, food security, and socio-economic development. Here, three 30 m resolution global land cover data products (FROM_GLC, GlobeLand30, and GLC_FCS30) from the Eastern European Plain were analyzed and evaluated for component similarity, type confusion degree, spatial consistency, and accuracy verification. The research found that the three products provided consistent descriptions of land-cover types in the East European Plain. There was a strong correlation in the type area between the different products, with a correlation coefficient >0.85. Medium-to-high-consistency areas represented 92.31% of the total plains area. The low-consistency areas were mainly concentrated on Yuzhny Island, Kola Peninsula, and Pechora River Basin. The comparison revealed high consistency among the three products in identifying forest, cropland, water, and permanent ice/snow types. However, the consistency was poor for shrubs, wetlands, and bare land. Using the GLCVSS_V1 validation dataset, the highest overall accuracy among the assessed land cover data products was observed in the FROM_GLC (73.96%), followed by GlobeLand30 (69.80%) and GLC_FCS30 (67.29%). The FROM_GLC dataset is suitable for studying forests, tundra, water, and providing an overall representation of the region’s land cover. The GLC_FCS30 dataset is more suitable for agricultural research. The differences between products arise from the differences in classification systems, algorithms, and data correction. In the future, it will be necessary to utilize the advantages of different products for data fusion, focusing on areas with high heterogeneity and easily confused types, and improving the reliability of land-cover data products.

A scientifically accurate assessment of tunnel health is the prerequisite for the safe maintenance and sustainability of the in-service road tunnel. The changing trend of tunnel health is not considered in existing research. Most evaluation indicators are static and the ambiguities or randomness at the boundary of the health level intervals is neglected in most evaluation methods. In this paper, the evaluation index system combined with dynamic, and static is set to solve these problems. The changing trend of the health state of tunnels is analyzed through the cubic b-spline function. The weights of evaluation indicators are calculated based on the AHP-improved entropy method. The health evaluation method is proposed based on combing the extension theory and the cloud model improved by the cloud entropy optimization algorithm. Finally, the evaluation results of the proposed method are compared with the detection data of the Beilongmen Tunnel of Zhangzhuo Expressway. The results demonstrate that 80% of the evaluation results in the sample tunnel data are consistent with the standard results, and the remaining 20% show a lower level of health than the standard results. This reflects the evaluation results are impacted by the trend of tunnel health status changes. The health state can be more accurately evaluated by dynamic indicators. The improved extension cloud model is feasible and applicable in the health assessment of tunnels. This work provides innovative ideas for the evaluation of the health state of tunnels and theoretical support for the formulation of reasonable maintenance measures.

Rapid and accurate identification of mangroves using remote sensing images is of great significance for assisting ecological conservation efforts in coastal zones. With the rapid development of artificial intelligence, deep learning methods have been successfully applied to a variety of fields. However, few studies have applied deep learning methods to the automatic detection of mangroves and few scholars have used medium-resolution Landsat images for large-scale mangrove identification. In this study, cloud-free Landsat 8 OLI imagery of the Indus Delta was acquired using the GEE platform, and NDVI and land use data were used to produce integrated labels to reduce the complexity and subjectivity of manually labeled samples. We proposed the use of MSNet, a semantic segmentation model fusing multiple-scale features, for mangrove extraction in the Indus Delta, and compared the performance of the MSNet model with three other semantic segmentation models, FCN-8s, SegNet, and U-Net. The overall performance ranking of the deep learning methods was MSNet > U-Net > SegNet > FCN-8s. The parallel-structured MSNet model was easy to train, had the fewest parameters and the highest validation accuracy, and provided the best results for the extraction of mangrove pixels with weak features. The MSNet model not only maintains the high-resolution features of the image and fully learns the pixels with weak features during the training process but also fuses the multiple-scale underlying features at different scales to enhance the semantic information and improve the accuracy of feature recognition and segmentation localization. Finally, the areas covered by mangroves in the Indus Delta in 2014 and 2022 were extracted using the best-performing MSNet. The statistics show an increase in mangrove-covered areas in the Indus Delta between 2014 and 2022, with a reduction of 44.37 km2, an increase of 170.48 km2, and a net increase of 126.11 km2.

Improving the brand value of agricultural cultural heritage can promote the development of the local social economy. Meanwhile, cultural memory and brand value are inseparable. Therefore, this study took the Anxi Tieguanyin Tea Culture System as the research object, collected 679 questionnaires, adopted a structural equation model, and applied SPSS 26.0 and Amos 24.0 software (IBM; Armonk, NY, USA) to study the influence of agricultural heritage cultural memory on brand value. This study innovatively develops a scale of agricultural heritage cultural memory, enriches the outer edge of cultural memory theory research, broadens the vision of agricultural heritage research, and provides a useful reference for the inheritance of agricultural heritage and the promotion of brand value.