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In order to study the effect of water on the competitive adsorption of CH4/CO2 and mixed gases in coal, the self-developed multi-gas competitive adsorption experimental system of coal containing gas was used to conduct the research on the single component adsorption of CH4 and CO2 by coal with different water content. The experimental results show that: Water does not change the basic law of the isothermal adsorption curve of CH4 and CO2, and under the same conditions, water does not affect the ordering of coal's adsorption capacity for a single component of gas, and the adsorption capacity of coal for CO2 is always greater than that of CH4. Under the same conditions, the inhibition rate of water on CH4 is greater than that of CO2 adsorption capacity, indicating that the inhibition degree of water on coal's adsorption of weakly adsorbent gases is greater. The research on the effect of water on the competitive adsorption of mixed gas shows that: when the proportion of gas injected into the coal remains unchanged, under the same adsorption equilibrium pressure, the total adsorption of mixed gas decreases with the increase of water content, and the adsorption amount of CH4 and CO2 after adsorption equilibrium decreases with the increase of water content in the coal. When the water content is unchanged, the greater the gas adsorption equilibrium pressure under the same gas injection ratio, the greater the adsorption amount of CH4 and CO2 after adsorption equilibrium. The volume fraction of CO2 in the free phase is always lower than that of the gas source, while the volume fraction of CH4 is always higher than that of the gas source. Under different conditions, the values of CO2/CH4 selection coefficients are greater than 1, ranging from 4.8 to 5.4, and the adsorption affinity of coal for CO2 is greater than that of CH4. The selection coefficients of CO2/CH4 decrease with the increase of water content of coal samples under the same gas adsorption conditions. This study further improves the theoretical analysis of factors affecting coal gas adsorption, and provides a theoretical basis for engineering practice for underground gas injection and gas extraction technology.

Protein demand from aquaculture exacerbates environmental pressures. Zig-zag eel (Mastacembelus armatus, MA) is a new aquaculture species in southern China and has great potential for future promotion. In this study, we used Spirulina platensis powder (SPP) to replace 0–20 % of fishmeal in the feed, respectively. A 10-week aquaculture experiment was conducted on 600 MAs with five groups of F0 (0 %), F1 (5 %), F2 (10 %), F3 (15 %), and F4 (20 %) set up with equal nitrogen (approximately 50.00 % crude protein) and equal fat (about 5.50 % crude fat) feeds. The experimental results showed that replacing fishmeal with different proportions of SPP significantly reduced FCR (p < 0.05), increased WGR and SGR (p < 0.05), and reduced the feeding cost, with the best performance in F2. Polynomial analysis combining WGR and SGR showed that the optimum percentage of substitution was 10.93 % and 11.09 % in MA diets, respectively. The addition of SPP significantly reduced the levels of EPA and DHA content (p < 0.05), significantly increased the proportion of C14:0, C16:1, C20:5n3, and C22:6n3 (p < 0.05), and a high proportion of SPP addition significantly decreased saturated fatty acid content (p < 0.05). The length of intestinal villi and the secretion levels of Chymotrypsin and Pepsin were significantly increased (p < 0.05), and the secretion level of Lipase was significantly decreased (p < 0.05) in the experimental group. A low percentage of SPP increased microbial diversity in MA’s gut. Functional pathways related to metabolic functions were the most obvious broad groups with the most significant changes in relative abundance in the experimental group, and Plesiomonas and Aeromonas may be the key microorganisms involved in regulating the digestion and metabolism of SPP in the gut of MA.

Abstract Previous studies have indicated that Cranoglanis bouderius and Pangasianodon hypophthalmus clustered into a sister group. However, there was a significant difference in their minimum tolerated temperatures. To reveal the temperature adaptation‐related genes, a genome‐wide comparative analysis was performed. First, a chromosome‐level draft genome of C. bouderius was constructed in this study. The genome assembly was 999.18 Mb in size with a contig N50 of 20.47 Mb. Then, an additional 118.98 Gb of Hi‐C data was applied to assemble contigs into scaffolds and 910.59 Mb was anchored and orientated onto 38 chromosomes of C. bouderius. A total of 24,165 protein‐coding genes were predicted from the genome with 22,920 (94.84%) genes functionally annotated. Genome‐wide comparative analysis revealed that the genes related to resistance to low‐temperature stress were mainly enriched into the gene ontology (GO) terms associated with mitochondrial fusion and calcium ion transport. Further, the low‐temperature stress test on the C. bouderius and P. hypophthalmus also revealed that the C. bouderius can better control the homeostasis of calcium ions in cells than P. hypophthalmus, and then better maintain the dynamic changes of mitochondrial fusion and fission in cells, thereby resisting cell damage caused by low‐temperature stress.

The design of the high-speed on/off valve is challenging due to the interrelated structural parameters of its driving actuator. Hence, this study proposes a multi-objective optimization approach that integrates a backpropagation neural network and artificial fish swarm algorithm optimization techniques to accurately model the electromagnetic solenoid structure. The backpropagation neural network is fitted and trained using simulation data to obtain a reduced-order model of the system, enabling the precise prediction of the system’s output based on the input structural parameters. By employing the artificial fish swarm algorithms, with optimization objectives focusing on the valve’s opening and closing times, a Pareto optimal solution set comprising 30 solutions is generated. Utilizing the optimized structural parameters, a prototype is manufactured and an experimental setup is constructed to verify the dynamic characteristics and flow pressure drop. The high-speed on/off valve achieves an approximate opening and closing time of 3 ms. Notably, the system output predicted using the backpropagation neural network (BPNN) exhibits consistency with the experimental findings, providing a reliable alternative to mathematical modeling.

The coal mine’s underground heading roadway suffers from a lack of effective temporary support, which contributes to low efficiency and inadequate safety in excavation operations. This paper presents a novel approach for roadway excavation, support, and anchoring, utilizing the twin-link stepping temporary support method. To address the stability requirements of the roadway roof in this support method, a numerical model of the excavation face was developed using the BBM (Bonded Block Model) method in 3DEC 7.0 software. Through numerical simulation, the repeatability of the twin-link stepping temporary support process was assessed for various roadway roof rock types, thicknesses, and burial depths. By considering aspects such as roof fragmentation, roof convergence, and relative displacement between the direct roof and the bedrock, the range of roadway roof repeatability was determined. The proposed twin-link stepping temporary support process, along with its applicable roof conditions, establishes a theoretical foundation for implementing the parallel operation mode in coal mine underground heading roadways, thereby significantly enhancing safety and efficiency.

IL-37 is a newly discovered member of the IL-1 cytokine family which plays an important role in regulating inflammation and maintaining physiological homeostasis. IL-37 showed a close relationship with IL-18, another key cytokine in inflammation regulation and cancer development. IL-37 affects the function of IL-18 either by binding to IL-18Rα, a key subunit of both IL-37 and IL-18 receptor, or by drastically neutralizing the IL-18 protein expression of IL-18 binding protein, an important natural inhibitory molecule of IL-18. Moreover, as another subunit receptor of IL-37, IL-1R8 can suppress IL-18Rα expression, functioning as a surveillance mechanism to prevent overactivation of both IL-18 and IL-37 signaling pathways. While IL-18 and IL-37 share the same receptor subunit, IL-18 would in turn interfere with IL-37 signal transduction by binding to IL-18Rα. It is also reported that IL-18 and IL-37 demonstrated opposing effects in a variety of cancers, such as glioblastoma, lung cancer, leukemia, and hepatocellular cancer. Although the mutual regulation of IL-18 and IL-37 and their diametrically opposed effects in cancers has been reported, IL-18 has not been taken into consideration when interpreting clinical findings and conducting mechanism investigations related to IL-37 in cancer. We aim to review the recent progress in IL-18 and IL-37 research in cancer and summarize the correlation between IL-18 and IL-37 in cancer based on their expression level and underlying mechanisms, which would provide new insights into elucidating the conflicting roles of IL-18 and IL-37 in cancer and bring new ideas for translational research related to IL-18 and IL-37.

This study evaluated the effects of koumine on growth performance, brain transcriptional response, expression of genes associated with circadian rhythms, and physiological stress indicators in carp (5.21 ± 0.05 g). Fish were fed four different koumine levels (0, 0.2, 2, and 20 mg/kg) of diet (crude protein 29.71%, crude lipid 3.68%) for 10 weeks in a RAS (26.0–28.0 ℃, pH 7.3–7.5, and DO 5.5–6.1 mg/L). Each type of feed was administered to three replicate tanks (50 L, 12 cycles per day), each containing 30 fish, with feeding occurring twice daily. The results showed that koumine supplementation improved the growth performance of carp. Significant enrichment of circadian rhythm, memory, and behavior-related pathways in the brain of the koumine-supplemented group of fish. The circadian rhythm positive feedback-related genes MKP5, ATP1A, ATP2A, and CRY2 were significantly upregulated (P

[Introduction] With the development of domestic renewable energy industry, the recession of governmental subsidies and the implementation of policies such as competitive allocation of resources, Levelized Cost of Energy (LCOE) is gaining more and more attention and application, but its calculation method is inconsistent in domestic energy industry. In this paper, the relationship between Internal Rate of Return (IRR) and LCOE is analyzed to improve understanding of LCOE and standardize its application. [Method] The characteristics and application scenarios of LCOE and IRR were analyzed, and then their calculation formulas were simplified and transformed to analyze the difference and relation between them in models. Finally through the case analysis of an offshore wind power plant, the actual difference between the results was calculated, and the factors causing the difference and their sensitivities were analyzed. [Result] From the perspective of results, the simplified calculation models are very similar except for the income tax. According to the case analysis, the factors causing the difference between IRR and LCOE include the VAT deduction, after-tax incentives of VAT and income tax, additional taxes, and financing during the construction period, and influenced different directions to different extent. It can be considered that IRR and LCOE are similar in principle, but they become different under the influence of domestic fiscal policy, tax system and increased boundary conditions. [Conclusion] It is suggested that LCOE is properly localized and revised by competent departments, industry associations, etc. In combination with environmental impact costs and power system impact costs, the economy of different power generation approaches can be compared, and the rapid comparison of the economy of different schemes can also be achieved in specific projects.

Abstract Background Individuals with certain chronic inflammatory lung diseases have a higher risk of developing lung cancer (LC). However, the underlying mechanisms remain largely unknown. Here, we hypothesized that chronic exposure to house dust mites (HDM), a common indoor aeroallergen associated with the development of asthma, accelerates LC development through the induction of chronic lung inflammation (CLI). Methods The effects of HDM and heat-inactivated HDM (HI-HDM) extracts were evaluated in two preclinical mouse models of LC (a chemically-induced model using the carcinogen urethane and a genetically-driven model with oncogenic Kras G12D activation in lung epithelial cells) and on murine macrophages in vitro. Pharmacological blockade or genetic deletion of the Nod-like receptor family pyrin domain-containing protein 3 (NLRP3) inflammasome, caspase-1, interleukin-1β (IL-1β), and C–C motif chemokine ligand 2 (CCL2) or treatment with an inhaled corticosteroid (ICS) was used to uncover the pro-tumorigenic effect of HDM. Results Chronic intranasal (i.n) instillation of HDM accelerated LC development in the two mouse models. Mechanistically, HDM caused a particular subtype of CLI, in which the NLRP3/IL-1β signaling pathway is chronically activated in macrophages, and made the lung microenvironment conducive to tumor development. The tumor-promoting effect of HDM was significantly decreased by heat treatment of the HDM extract and was inhibited by NLRP3, IL-1β, and CCL2 neutralization, or ICS treatment. Conclusions Collectively, these data indicate that long-term exposure to HDM can accelerate lung tumorigenesis in susceptible hosts (e.g., mice and potentially humans exposed to lung carcinogens or genetically predisposed to develop LC).

Environmental pollutants are closely linked to lung cancer. The different types of environmental pollutants can be classified as chemical, physical, and biological. The roles of common chemical and physical pollutants such as PM2.5, smoking, radon, asbestos, and formaldehyde in lung cancer have been extensively studied. Notably, the worldwide COVID-19 pandemic raised awareness of the strong link between biological pollution and human health. Allergens such as house dust mites and pollen, as well as bacteria and viruses, are common biological pollutants. A few biological pollutants have been reported to promote lung cancer via inducing inflammatory cytokines secretion, such as IL-1β, IL-6, and TGF-β, as well as suppressing immunosurveillance by upregulating regulatory T (Treg) cells while dampening the function of CD8+ T cells and dendritic cells. However, the correlation between common biological hazards, such as SARS-CoV-2, human immunodeficiency viruses, Helicobacter pylori, and house dust mites, and lung cancer is not fully elucidated, and the underlying mechanisms are still unclear. Moreover, the majority of studies that have been performed in lung cancer and biological carcinogens were not based on the perspective of biological pollutants, which has challenged the systematicity and coherence in the field of biological pollutants in lung cancer. Here, in addition to reviewing the recent progress made in investigating the roles of allergens, viruses, and bacteria in lung cancer, we summarized the potential mechanisms underlying biological pollutants in lung cancer. Our narrative review can shed light on understanding the significance of biological pollutants in lung cancer, as well as inspire and broaden research ideas on lung cancer etiology.

This study determined the effect of dietary kelp meal (KM) on metabolism of the hybrid snakeheads (Channa maculatus ♀ × Channa argus ♂), and the spatiotemporal changes in their resistance to ammonia stress, including survival rate, histopathology, biochemical parameters, and the expression of immune-related genes. The experimental diets contained: 0% KM, 5% KM, 10% KM, 15% KM, 15% KM + 5% binder. After eight weeks of feeding, six fish per diet were sampled for metabolic studies, and the remaining fish were placed under ammonia stress at two concentrations (1200 mg/L and 120 mg/L) for 48 h. Our results showed that replacing flour with kelp meal to the diet could alter the activities of some metabolic enzymes and reduced the lethality of hybrid snakeheads under high ammonia exposure. Histopathological results revealed a variety of pathological features in the liver after exposure to ammonia nitrogen. The levels of glutamate dehydrogenase (GDH), glutamine synthetase (GS), superoxide dismutase (SOD), catalase (CAT), and malondialdehyde (MDA) showed the trend of first increasing and then decreasing with the decrease of the flour concentration in the diet under high concentration of ammonia stress. Besides, kidneys receive more severe oxidative damage than the liver. Similar results were found in the mRNA abundance of immune-related genes, and the kidney were mostly significantly down-regulated, but feeding moderate amounts of kelp meal can alleviate this damage. The transcriptome analysis showed that kelp meal can affect antigen processing and presentation process by the MHCⅠ signaling pathway mechanism, and thus regulate the immune response of hybrid snakeheads. Our study suggests that adding kelp meal in the diets could improve the ability of hybrid snakeheads to resist ammonia stress and the optimal replacement group is 10% KM group.

Koumine is one of the most abundant alkaloids found in Gelsemium elegans, and it has a wide range of pharmacological effects including antitumor, anti-inflammatory, analgesic treatment effects, and antianxiety. However, its high toxicity and unclear mechanism of action have greatly limited the medicinal development and use of koumine. We investigated the toxic effects of koumine on the developmental toxicity and behavioral neurotoxicity of zebrafish embryos and larvae. Embryos at 6 h postfertilization (hpf) were exposed to 12.5, 25, 50, 75, and 100 mg/L of koumine until 120 hpf. Koumine affected the hatching and heartbeats of the embryos. The morphological analysis also revealed many abnormalities, such as shortened bodies, yolk sac edemas, tail malformations, and pericardial edemas. To identify the neurotoxicity of koumine, the behavior of the larvae was measured. Koumine at 50 and 100 mg/L affect the escape response. The embryos exhibited uncoordinated muscle contractions along the body axis in response to touch at 36 hpf. More importantly, we found that the neurotoxicity of koumine is mainly caused by influencing the ACh content and the activity of AChE without impairing motor neuron development. A comprehensive analysis shows that a high concentration of koumine has obvious toxic effects on zebrafish, and the safe concentration of koumine for zebrafish should be less than 25 mg/L. These results will be valuable for better understanding the toxicity of koumine and provide new insights into the application of koumine.

This paper proposes a temporary support system for improving the efficiency and safety of underground roadway excavation in coal mines. Firstly, this study establishes a calculation model for the initial supporting force of the excavation of roadway temporary support and a gray system-based automatic prediction model for the initial supporting force level, based on the mechanism of temporary support controlling the roof. These models enable the prediction of the required initial supporting force at different locations along the roadway’s temporary support area, thereby providing a basis for controlling the initial supporting force of the temporary support system. To achieve efficient and adaptive control of the initial supporting force of temporary supports at different locations, this study designs a support force controller based on Simulated Annealing Particle Swarm Optimization Proportional-Integral-Derivative (SAPSO-PID). This study establishes a mathematical model for the hydraulic cylinder pressure system controlled by the temporary support overflow valve and conducts a stability analysis and model verification. The study constructs a simulation control system for the initial supporting force based on SAPSO-PID using the combined simulation platform of AMESim and Matlab. The simulation results demonstrate that the proposed support force control system efficiently achieves adaptive control of the initial supporting force of temporary supports. An experimental system in the underground roadway of a coal mine is constructed to validate the results of the simulation analysis.

Glioblastoma is carcinogenesis of glial cells in central nervous system and has the highest incidence among primary brain tumors. Brain metastasis, such as breast cancer and lung cancer, also leads to high mortality. The available medicines are limited due to blood–brain barrier. Abnormal activation of phosphatidylinositol 3-kinases (PI3K) signaling pathway is prevalent in glioblastoma and metastatic tumors. Here, we characterized a 2-amino-4-methylquinazoline derivative XH30 as a potent PI3K inhibitor with excellent anti-tumor activity against human glioblastoma. XH30 significantly repressed the proliferation of various brain cancer cells and decreased the phosphorylation of key proteins of PI3K signaling pathway, induced cell cycle arrest in G1 phase as well. Additionally, XH30 inhibited the migration of glioma cells and blocked the activation of PI3K pathway by interleukin-17A (IL-17A), which increased the migration of U87MG. Oral administration of XH30 significantly suppressed the tumor growth in both subcutaneous and orthotopic tumor models. XH30 also repressed tumor growth in brain metastasis models of lung cancers. Moreover, XH30 reduced IL-17A and its receptor IL-17RA in vivo. These results indicate that XH30 might be a potential therapeutic drug candidate for glioblastoma migration and brain metastasis.

Environmental sensors are essential for tracking weather conditions and changing trends, thus preventing adverse effects on species and environment. Missing values are inevitable in sensor recordings due to equipment malfunctions and measurement errors. Recent representation learning methods attempt to reconstruct missing values by capturing the temporal dependencies of sensor signals as handling time series data. However, existing approaches fall short of simultaneously capturing spatio-temporal dependencies in the network and fail to explicitly model sensor relations in a data-driven manner. In this work, we propose a novel Adaptive Graph Convolutional Imputation Network for missing value imputation in environmental sensor networks. A bidirectional graph convolutional gated recurrent unit module is introduced to extract spatio-temporal features which takes full advantage of the available observations from the target sensor and its neighboring sensors to recover the missing values. In addition, we design an adaptive graph learning layer that learns a sensor network topology in an end-to-end framework, in which no prior network information is needed for capturing spatial dependencies. Extensive experiments on three real-world environmental sensor datasets (solar radiation, air quality, relative humidity) in both in-sample and out-of-sample settings demonstrate the superior performance of the proposed framework for completing missing values in the environmental sensor network, which could potentially support environmental monitoring and assessment.

Asymmetrical working conditions of the utility grid introduce the large-amplitude negative-sequence component to the output current of the voltage source converter (VSC), causing power semiconductor devices to suffer from thermal fatigue and thermal damage. Though the conventional phase-locked loop (PLL) based voltage oriented control (VOC) solution can suppress the steady-state negative-sequence current effectively, it has a weak suppression ability of transient overload current, and even aggravates the transient current asymmetry and causes more severe transient impact to the VSC. This paper first analyzes the transient performance of the conventional VOC strategy, especially its dynamic response time and the main factors for performance limitation. On this basis, the PLL-free VOC strategy for VSCs tied to unbalanced grids is proposed, and its critical parts, namely, the reference current calculation and the fast detection of the grid voltage sequence components, are implemented. Besides, to improve the frequency adaptability, a high-performance grid frequency detection strategy is developed based on the difference-frequency phase caused by the frequency variation. Finally, experiments are performed to verify the effectiveness and advancement of the proposed method. Specifically, the results proved the rapidity, accuracy, and frequency adaptability of the proposed method in suppressing the VSC negative-sequence current, both in transient and steady-state conditions.

Human tumors harbor a plethora of microbiota. It has been shown that the composition and diversity of intratumor microbiome are significantly associated with the survival of patients with pancreatic ductal adenocarcinoma (PDAC). However, the association in Chinese patients as well as the effect of different microorganisms on inhibiting tumor growth are unclear. In this study, we collected tumor samples resected from long-term and short-term PDAC survivors and performed 16S rRNA amplicon sequencing. We found that the microbiome in samples with different survival time were significantly different, and the differential bacterial composition was associated with the metabolic pathways in the tumor microenvironment. Furthermore, administration of Megasphaera, one of the differential bacteria, induced a better tumor growth inhibition effect when combined with the immune checkpoint inhibitor anti-programmed cell death-1 (anti-PD-1) treatment in mice bearing 4T1 tumor. These results indicate that specific intratumor microbiome can enhance the anti-tumor effect in the host, laying a foundation for further clarifying the underlying detailed mechanism.

Automated characterization of spatial data is a kind of critical geographical intelligence. As an emerging technique for characterization, spatial Representation Learning (SRL) uses deep neural networks (DNNs) to learn non-linear embedded features of spatial data for characterization. However, SRL extracts features by internal layers of DNNs, and thus suffers from lacking semantic labels. Texts of spatial entities, on the other hand, provide semantic understanding of latent feature labels, but is insensible to deep SRL models. How can we teach a SRL model to discover appropriate topic labels in texts and pair learned features with the labels? This paper formulates a new problem: feature-topic pairing, and proposes a novel Particle Swarm Optimization (PSO) based deep learning framework. Specifically, we formulate the feature-topic pairing problem into an automated alignment task between 1) a latent embedding feature space and 2) a textual semantic topic space. We decompose the alignment of the two spaces into: 1) point-wise alignment, denoting the correlation between a topic distribution and an embedding vector; 2) pair-wise alignment, denoting the consistency between a feature-feature similarity matrix and a topic-topic similarity matrix. We design a PSO based solver to simultaneously select an optimal set of topics and learn corresponding features based on the selected topics. We develop a closed loop algorithm to iterate between 1) minimizing losses of representation reconstruction and feature-topic alignment and 2) searching the best topics. Finally, we present extensive experiments to demonstrate the enhanced performance of our method.

In China, the Cranoglanis bouderius is classified as a national class II-protected animal. The development of C. bouderius populations has been affected by a variety of factors over the past few decades, with severe declines occurring. Considering the likelihood of continued population declines of the C. bouderius in the future, it is critical to investigate the currently unknown characteristics of gonadal differentiation and sex-related genes for C. bouderius conservation. In this study, the Illumina sequencing platform was used to sequence the gonadal transcriptome of the C. bouderius to identify the pathways and genes related to gonadal development and analyze the expression differences in the gonads. A total of 12,002 DEGs were identified, with 7220 being significantly expressed in the ovary and 4782 being significantly expressed in the testis. According to the functional enrichment results, the cell cycle, RNA transport, apoptosis, Wnt signaling pathway, p53 signaling pathway, and prolactin signaling pathway play important roles in sex development in the C. bouderius. Furthermore, the sequence characterization and evolutionary analysis revealed that AMH, DAX1, NANOS1, and AR of the C. bouderius are highly conserved. Specifically, the qRT-PCR results from various tissues showed significant differences in AMH, DAX1, NANOS1, and AR expression levels in the gonads of both sexes of C. bouderius. These analyses indicated that AMH, DAX1, NANOS1, and AR may play important roles in the differentiation and development of C. bouderius gonads. To our best knowledge, this study is the first to analyze the C. bouderius gonadal transcriptome and identify the structures of sex-related genes, laying the foundation for future research.

Cultivated land fragmentation (CLF) is a key obstacle to agricultural development and has a strong relationship with regional food security and global sustainable development. However, few studies have analyzed the spatio-temporal distribution pattern and evolution characteristics of CLF and the complex interactions among their influencing factors in rapidly developing regions. In this study, first, the GlobeLand30 datasets were used to obtain characteristic parameters of cultivated land in counties in Guangdong Province in 2000, 2010, and 2020. Then, the linear weighted comprehensive evaluation model based on the principal component analysis (PCA) was used to measure the extent of CLF. Finally, the exploratory spatial data analysis (ESDA) was used to analyze the spatio-temporal distribution pattern and evolution characteristics of CLF, and geodetector (GD) and random forest (RF) models were used to explore the factors influencing the spatial difference in CLF. The results showed that the spatial differences in the distribution of cultivated land resources in Guangdong Province are relatively large and the extent of agglomeration is generally low. The extent of CLF on the county scale is mainly medium and higher. The overall spatial distribution shows an increasing trend from the south to the north and from the west to the east, and the spatial distribution pattern with agglomeration and randomness remains relatively stable. From 2000 to 2020, the overall CLF continued to intensify and the evolution of CLF on the county scale mainly increased. The spatial difference in CLF is the result of that based on the natural environment and influenced by factors such as social, economic, and agricultural development. The interaction between influencing factors is very strong, dominated by nonlinear enhancement. The results are of great significance for promoting the intensive and efficient utilization of cultivated land resources and sustainable regional development.

Gelsemium elegans Benth. (GEB) is a traditional medicinal plant in China, and acts as a growth promoter in pigs and goats. Koumine (KM) is the most abundant alkaloid in GEB and produces analgesic, anti-cancer, and immunomodulatory effects. KM can be used as an aquatic immune stimulant, but its growth-promoting effects and transcriptional mechanisms have not been investigated. Diets containing KM at 0, 0.2, 2, and 20 mg/kg were fed to Cyprinus carpio for 71 days to investigate its effects on growth performance, intestinal morphology, microflora, biochemical indicators, and transcriptional mechanisms. Cyprinus carpio fed with KM as the growth promoter, and the number of intestinal crypts and intestinal microbial populations were influenced by KM concentration. KM increased the abundance of colonies of Afipia, Phyllobacterium, Mesorhizobium, and Labrys, which were associated with compound decomposition and proliferation, and decreased the abundance of colonies of pathogenic bacteria Methylobacterium-Methylorubrum. A total of 376 differentially-expressed genes (DEGs) among the four experimental groups were enriched for transforming growth factor-β1 and small mother against decapentaplegic (TGF-β1/Smad), mitogen-activated protein kinase (MAPK), and janus kinases and signal transducers and activators of transcription (Jak/Stat) signaling pathways. In particular, tgfbr1, acvr1l, rreb-1, stat5b, smad4, cbp, and c-fos were up-regulated and positively correlated with KM dose. KM had a growth-promoting effect that was related to cell proliferation driven by the TGF-β1/Smad, MAPK, and Jak/Stat signaling pathways. KM at 0.2 mg/kg optimized the growth performance of C. carpio, while higher concentrations of KM (2 and 20 mg/kg) may induce apoptosis without significantly damaging the fish intestinal structure. Therefore, KM at low concentration has great potential for development as an aquatic growth promotion additive.

Building extraction of remote sensing images is very important for urban planning. In the field of deep learning, in order to extract more detailed building features, more complex convolution operations and larger network models are usually used to segment buildings, resulting in low efficiency of automatic extraction. The existing network is difficult to balance the extraction accuracy and extraction speed. Considering the segmentation accuracy and speed, a Feature Residual Analysis Network (FRA-Net) is proposed to realize fast and accurate building extraction. The whole network includes two stages: encoding and decoding. In the encoding stage, a Separable Residual Module (SRM) is designed to extract feature information and extract building features from remote sensing images, avoiding the use of large convolution kernels to reduce the complexity of the model. In the decoding stage, the SRM is used for information decoding, and a multi-feature attention module is constructed to enhance the effective information. The experimental results on the LandCover dataset and Massachusetts Buildings dataset show that the reasoning speed has been greatly improved without reducing the segmentation accuracy.