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The gut microbiota has become an essential component of the host organism and plays a crucial role in the host immune system, metabolism, and physiology. Nevertheless, our comprehension of how the fish gut microbiota contributes to enhancing nutrient utilization in the diet and improving host growth performance remains unclear. In this study, we employed a comprehensive analysis of the microbiome, metabolome, and transcriptome to analyze intestines of the normal control group and the antibiotic-treated model group of T. ovatus to investigate how the gut microbiota enhances fish growth performance and uncover the underlying mechanisms. First, we found that the growth performance of the control group was significantly higher than that of the antibiotic-treated model under the same feeding conditions. Subsequent multiomics analyses showed that the gut microbiota can improve its own composition by mediating the colonization of some probiotics represented by Lactobacillus in the intestine, improving host metabolic efficiency with proteins and lipids, and also influencing the expression of genes in signaling pathways related to cell proliferation, which together contribute to the improved growth performance of T. ovatus. Our results demonstrated the important contribution of gut microbiota and its underlying molecular mechanisms on the growth performance of T. ovatus.

Convolutional neural networks (CNNs) have recently been demonstrated to be able to substantially improve the land cover classification accuracy of hyperspectral images. Meanwhile, the rapidly developing capacity for satellite and airborne image spectroscopy as well as the enormous archives of spectral data have imposed increasing demands on the computational efficiency of CNNs. Here, we propose a novel CNN framework that integrates one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) CNNs to obtain highly accurate and fast land cover classification from airborne hyperspectral images. To achieve this, we first used 3D CNNs to derive both spatial and spectral features from hyperspectral images. Then, we successively utilized a 2D CNN and a 1D CNN to efficiently acquire higher-level representations of spatial or spectral features. Finally, we leveraged the information obtained from the aforementioned steps for land cover classification. We assessed the performance of the proposed method using two openly available datasets (the Indian Pines dataset and the Wuhan University dataset). Our results showed that the overall classification accuracy of the proposed method in the Indian Pines and Wuhan University datasets was 99.65% and 99.85%, respectively. Compared to the state-of-the-art 3D CNN model and HybridSN model, the training times for our model in the two datasets were reduced by an average of 60% and 40%, respectively, while maintaining comparable classification accuracy. Our study demonstrates that the integration of 1D, 2D, and 3D CNNs effectively improves the computational efficiency of land cover classification with hyperspectral images while maintaining high accuracy. Our innovation offers significant advantages in terms of efficiency and robustness for the processing of large-scale hyperspectral images.

As a member of the forkhead box L gene family, foxl2 plays a significant role in gonadal development and the regulation of reproduction. During the evolution of deuterostome, whole genome duplication (WGD)-enriched lineage diversifications and regulation mechanisms occurs. However, only limited research exists on foxl2 duplication in teleost or other vertebrate species. In this study, two foxl2 paralogs, foxl2 and foxl2l, were identified in the transcriptome of spotted knifejaw (Oplegnathus punctatus), which had varying expressions in the gonads. The foxl2 was expressed higher in the ovary, while foxl2l was expressed higher in the testis. Phylogenetic reconstruction, synteny analysis, and the molecular evolution test confirmed that foxl2 and foxl2l likely originated from the first two WGD. The expression patterns test using qRT-PCR and ISH as well as motif scan analysis revealed evidence of potentially functional divergence between the foxl2 and foxl2l paralogs in spotted knifejaw. Our results indicate that foxl2 and foxl2l may originate from the first two WGD, be active in transcription, and have undergone functional divergence. These results shed new light on the evolutionary trajectories of foxl2 and foxl2l and highlights the need for further detailed functional analysis of these two duplicated paralogs.

The proven reserves of heavy oil in the Bohai oilfield exceed 600 million tons. Heavy oil is highly viscous, temperature sensitive, and suitable for thermal extraction, but due to the strong inhomogeneity of the reservoir, the recovery rate of pure thermal extraction development is low, and there is an urgent need to conduct research on profile control + thermal extraction to guide the actual production. In this paper, we propose an integrated technology of profile control and thermal recovery to enhance heavy oil recovery. The heavy oil exhibited strong temperature dependence and nonlinear flow characteristics. An inorganic gel was selected for profile control to assist thermal recovery. Thermal recovery experiments were conducted in the laboratory using cores saturated by crude oil with different viscosities to simulate the oil in areas swept by thermal fluid. The 4% to 6% inorganic gel can seal up to 99% on 2000 × 10−3 μm2 cores. As the thermal recovery temperature increased from 55 to 200 °C, the efficiency of oil recovery increased from 10.8% to 42.9% in experiments with three-layer heterogeneous cores; it increased by 8.9–13.2% when profile control was implemented using the inorganic gel with a concentration of 4%. The injection parameters for thermal recovery were optimized with a thermal fluid swept area of 3/10 times the injector–producer distance, including three slugs of crude oil with different viscosities. According to the experiments involving an inverted nine-point well pattern, the integrated technology of profile control and thermal recovery enhances oil recovery by 1.4% compared to of profile control or thermal recovery alone.

The existing plugging removal operation in JZ9-3 oilfield has the disadvantages of small amount of plugging remover, fast injection speed, and short construction time. Under the condition of injection well suction profile reversal, plugging remover is difficult to enter the low permeability part and play the role of deep plugging removal. In order to improve the plugging removal effect, this paper used the physical simulation method to carry out the experimental study and mechanism analysis on the effect of water flooding, chemical flooding, and plugging removal measures of the multi-layer system combination model. The results showed that the recovery of general plugging removal after chemical flooding increases by only 0.70%, while the recovery of ‘profile control + plugging removal’ increases by ‘9.34% + 2.59%’, and the amount of produced liquid decreases by more than 40%. It can be seen that the combined operation of profile control and plugging removal has dual effects of plugging and dredging and synergistic effect, which not only expands the swept volume, but also reduces the inefficient and ineffective cycles. On this basis, the optimization design and effect prediction of the target well W4-2 plugging removal scheme were carried out by using the numerical simulation method. Recommended scheme: inorganic gel profile control agent volume 13,243.6 m3, produced by the main agent (Na2O·nSiO2), isolation fluid (Water), and auxiliary agent (CaCl2) through multiple rounds of alternating injection into the reservoir. The plug removal agent (K2S2O8) injection volume is 100 m3, the concentration is 0.8%. The post-implementation ‘Output/Input’ ratio is expected to be 3.7.

The convolutional neural network (CNN) method has been widely used in the classification of hyperspectral images (HSIs). However, the efficiency and accuracy of the HSI classification are inevitably degraded when small samples are available. This study proposes a multidimensional CNN model named MDAN, which is constructed with an attention mechanism, to achieve an ideal classification performance of CNN within the framework of few-shot learning. In this model, a three-dimensional (3D) convolutional layer is carried out for obtaining spatial–spectral features from the 3D volumetric data of HSI. Subsequently, the two-dimensional (2D) and one-dimensional (1D) convolutional layers further learn spatial and spectral features efficiently at an abstract level. Based on the most widely used convolutional block attention module (CBAM), this study investigates a convolutional block self-attention module (CBSM) to improve accuracy by changing the connection ways of attention blocks. The CBSM model is used with the 2D convolutional layer for better performance of HSI classification purposes. The MDAN model is applied for classification applications using HSI, and its performance is evaluated by comparing the results with the support vector machine (SVM), 2D CNN, 3D CNN, 3D–2D–1D CNN, and CBAM. The findings of this study indicate that classification results from the MADN model show overall classification accuracies of 97.34%, 96.43%, and 92.23% for Salinas, WHU-Hi-HanChuan, and Pavia University datasets, respectively, when only 1% HSI data were used for training. The training and testing times of the MDAN model are close to those of the 3D–2D–1D CNN, which has the highest efficiency among all comparative CNN models. The attention model CBSM is introduced into MDAN, which achieves an overall accuracy of about 1% higher than that of the CBAM model. The performance of the two proposed methods is superior to the other models in terms of both efficiency and accuracy. The results show that the combination of multidimensional CNNs and attention mechanisms has the best ability for small-sample problems in HSI classification.

The leaf area index (LAI) is of great significance for crop growth monitoring. Recently, unmanned aerial systems (UASs) have experienced rapid development and can provide critical data support for crop LAI monitoring. This study investigates the effects of combining spectral and texture features extracted from UAS multispectral imagery on maize LAI estimation. Multispectral images and in situ maize LAI were collected from test sites in Tongshan, Xuzhou, Jiangsu Province, China. The spectral and texture features of UAS multispectral remote sensing images are extracted using the vegetation indices (VIs) and the gray-level co-occurrence matrix (GLCM), respectively. Normalized texture indices (NDTIs), ratio texture indices (RTIs), and difference texture indices (DTIs) are calculated using two GLCM-based textures to express the influence of two different texture features on LAI monitoring at the same time. The remote sensing features are prescreened through correlation analysis. Different data dimensionality reduction or feature selection methods, including stepwise selection (ST), principal component analysis (PCA), and ST combined with PCA (ST_PCA), are coupled with support vector regression (SVR), random forest (RF), and multiple linear regression (MLR) to build the maize LAI estimation models. The results reveal that ST_PCA coupled with SVR has better performance, in terms of the VIs + DTIs (R2 = 0.876, RMSE = 0.239) and VIs + NDTIs (R2 = 0.877, RMSE = 0.236). This study introduces the potential of different texture indices for maize LAI monitoring and demonstrates the promising solution of using ST_PCA to realize the combining of spectral and texture features for improving the estimation accuracy of maize LAI.

Rice bacterial leaf streak (BLS) is a serious disease in rice leaves and can seriously affect the quality and quantity of rice growth. Automatic estimation of disease severity is a crucial requirement in agricultural production. To address this, a new method (termed BLSNet) was proposed for rice and BLS leaf lesion recognition and segmentation based on a UNet network in semantic segmentation. An attention mechanism and multi-scale extraction integration were used in BLSNet to improve the accuracy of lesion segmentation. We compared the performance of the proposed network with that of DeepLabv3+ and UNet as benchmark models used in semantic segmentation. It was found that the proposed BLSNet model demonstrated higher segmentation and class accuracy. A preliminary investigation of BLS disease severity estimation was carried out based on our BLS segmentation results, and it was found that the proposed BLSNet method has strong potential to be a reliable automatic estimator of BLS disease severity.

Residual compressive stress can improve fretting fatigue strength. In this paper, the effects of residual stress on fretting fatigue of Al 2024-T351 alloy specimens are studied using a numerical approach. The extended finite element method combined with the cyclic cohesive zone model is adopted to model fretting fatigue crack growth behavior. It is shown that residual stress changes the fretting fatigue crack growth path and enhances fretting fatigue life. Crack initiation angle, depth of knee point, crack initiation life, crack propagation life and total life are greater for specimens with residual stress compared to specimens without residual stress. The effects of residual stress are more remarkable for specimens with a high intensity of residual stress. However, the effects of residual stress reduce at a high bulk load level.

Tungsten trioxide (WO3) is a wide band gap semiconductor material, which is commonly not only used, but also investigated as a significant electrochromic layer in electrochromic devices. WO3 films have been prepared by inorganic and sol-gel free ammonium tungstate ((NH4)2WO4), with the modification of glycerol using the spin coating technique. The surface tension, the contact angle and the dynamic viscosity of the precursor solutions demonstrated that the sample solution with a 25% volume fraction of glycerol was optimal, which was equipped to facilitate the growth of WO3 films. The thermal gravimetric and differential scanning calorimetry (TG-DSC) analysis represented that the optimal sample solution transformed into the WO3 range from 220 °C to 300 °C, and the transformation of the phase structure of WO3 was taken above 300 °C. Fourier transform infrared spectroscopy (FT-IR) spectra analysis indicated that the composition within the film was WO3 above the 300 °C annealing temperature, and the component content of WO3 was increased with the increase in the annealing temperature. The X-ray diffraction (XRD) pattern revealed that WO3 films were available for the formation of the cubic and monoclinic crystal structure at 400 °C, and were preferential for growing monoclinic WO3 when annealed at 500 °C. Atomic force microscope (AFM) images showed that WO3 films prepared using ammonium tungstate with modification of the glycerol possessed less rough surface roughness in comparison with the sol-gel-prepared films. An ultraviolet spectrophotometer (UV) demonstrated that the sample solution which had been annealed at 400 °C obtained a high electrochromic modulation ability roughly 40% at 700 nm wavelength, as well as the optical band gap (Eg) of the WO3 films ranged from 3.48 eV to 3.37 eV with the annealing temperature increasing.

The purpose of this paper is to investigate combustion characteristics for rotary engine via numerical studies. A 3D numerical model was developed to study the influence of several operative parameters on combustion characteristics. A novel rotary engine called, “Leaf Spring Rotary Engine”, was used to illustrate the structure and principle of the engine. The aims are to (1) improve the understanding of combustion process, and (2) quantify the influence of rotational speed, excess air ratio, initial pressure and temperature on combustion characteristics. The chamber space changed with crankshaft rotation. Due to the complexity of chamber volume, an equivalent modeling method was presented to simulate the chamber space variation. The numerical simulations were performed by solving the incompressible, multiphase Unsteady Reynolds-Averaged Navier–Stokes Equations via the commercial code FLUENT using a transport equation-based combustion model; a realizable turbulence model and finite-rate/eddy-dissipation model were used to account for the effect of local factors on the combustion characteristics.

PRDM14 is a PR (PRDI-BF1-RIZ1 homologous) domain protein with six zinc fingers and essential roles in genome-wide epigenetic reprogramming. This protein is required for the establishment of germ cells and the maintenance of the embryonic stem cell ground state. In this study, we cloned the full-length cDNA and genomic DNA of the Paralichthys olivaceus prdm14 (Po-prdm14) gene and isolated the 5' regulatory region of Po-prdm14 by whole-genome sequencing. Peptide sequence alignment, gene structure analysis, and phylogenetic analysis revealed that Po-PRDM14 was homologous to mammalian PRDM14. Results of real-time quantitative polymerase chain reaction amplification (RT-qPCR) and in situ hybridization (ISH) in embryos demonstrated that Po-prdm14 was highly expressed between the morula and late gastrula stages, with its expression peaking in the early gastrula stage. Relatively low expression of Po-prdm14 was observed in the other developmental stages. ISH of gonadal tissues revealed that the transcripts were located in the nucleus of the oocytes in the ovaries but only in the spermatogonia and not the spermatocytes in the testes. We also presume that the Po-prdm14 transcription factor binding sites and their conserved binding region among vertebrates. The combined results suggest that Po-PRDM14 has a conserved function in teleosts and mammals.

Nowadays, micro engine miniaturization is one of the most challenging issues, especially for the design and fabrication of the high-power-density micro Wankel engine. With the decrease of the size of the micro engine, the problem of the heat deformation of the cylinder becomes more serious. In this paper, a micro Wankel engine with microtextures on the outer surface of the cylinder is designed and manufactured to diffuse the heat dissipation and regulate the temperature gradient, so as to increase the power output density. First, a series of finite element simulations are conducted to design a type of ideal surface microtexture. Then, the machining condition is optimized to fabricate microtextures by micro cutting on the cylinder surface by studying the processing parameters. Finally, the performance of the new micro Wankel engine in terms of the temperature gradient regulation and the mechanical power output is tested and compared with that of the un-textured micro engine. The comparison results show that temperature of the textured micro engine was dropped from 185 °C to 125 °C and the mechanical power output increased by 10.74% from that of its un-textured counterpart, verifying the proposed methods for temperature gradient regulation.

This study analyzes the effects of shot peening on the crack initiation behavior under fretting loading by using a numerical method. The residual stress relaxation and the contact stress evolution are both considered. The crack initiation life is predicted by the critical plane Smith–Watson–Topper (SWT) model. Considering that the fretting contact region has a high stress gradient along the depth direction, the process volume approach is adopted to calculate the SWT parameters. The results show that the remaining residual stress after relaxation strongly affects crack initiation life. The remaining residual stress decreases with the increase of fatigue loading, and the effect of shot peening on the improvement of crack initiation life is more obvious under smaller fatigue loading. Furthermore, under smaller fatigue loading, the crack initiation life of specimens with high shot peening intensity is longer than that of specimens with low shot peening intensity. However, the opposite phenomenon appears when the fatigue loading is large enough.

Tetrahydrofuran (THF) is well known as a former and a promoter of clathrate hydrates, but the molecular mechanism for the formation of these compounds is not yet well understood. We performed ab initio calculations and ab initio molecular dynamics simulations to investigate the formation, structure, and stability of THF·(H2O)n=1⁻10 and its significance to the formation of the THF hydrate. Weak hydrogen bonds were found between THF and water molecules, and THF could promote water molecules from the planar pentagonal or hexagonal ring. As a promoter, THF could increase the binding ability of the CH4, CO2, or H2 molecule onto a water face, but could also enhance the adsorption of other THF molecules, causing an enrichment effect.

In this paper, an improved delayed detached eddy simulation method combined with shear-stress transport (SST) model was used to study the three-dimensional turbulent characteristics in a small rotary engine with a peripheral port. The turbulent characteristics including instantaneous velocity, turbulent fluctuation, coherent structure and velocity circulation were analysed based on a dynamic model of the small rotary engine. Three sets of conclusions on the basis of computational results were obtained. First, it was found that large-scale vortex structures with high intensity were distributed in the center of the chamber in the intake process and broke into lots of small vortex structures in the compression process. Second, flow stability in the X direction decreased from the leading to the trailing in the small rotary engine. The fluctuation velocity of the Y direction showed the paraboloid feature and its peak position moved from the mid-back to the middle of the chamber during the operation process. Third, during the intake process, two vortices occurred in the cross section parallel to the covers and were located at the leading and trailing of the cross section, respectively. Compared to the intake process, more vortices occur at cross sections which were far away from the central section during the compression process.

GATA-binding protein 6 (GATA6), a highly-conserved transcription factor of the GATA family plays an important role in gonadal cell proliferation, differentiation and endoderm development. In this study, the full-length cDNA of GATA6 of Paralichthys olivaceus (Japanese flounder) was obtained. Phylogenetic, gene structure and synteny analyses demonstrated that GATA6 of P. olivaceus is homologous to that of teleosts and tetrapods. The P. olivaceus GATA6 transcript showed higher expression in testis than in ovary, demonstrating a sexually dimorphic gene expression. During embryonic development, the expression of P. olivaceus GATA6 increased at the blastula stage, demonstrating that GATA6 is involved in morphogenesis. Results of in situ hybridization showed that GATA6 signals were detected in Sertoli cells, oogonia and oocytes. Moreover, 17α methyl testosterone, a male hormone, could moderately upregulate P. olivaceus GATA6 and downregulate P. olivaceus aromatase CYP19A1 in testis cells. These results suggest that GATA6 may play an important role in gonadal development in P. olivaceus. This study provides valuable information on the function of P. olivaceus GATA6, laying the foundation for further development of breeding techniques in this species.