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This paper focuses on airlines’ dynamic pricing strategy for air tickets, aiming to explore its diversified features in depth. Dynamic pricing strategy provides a strong impetus for airline operation and revenue optimisation, which is conducive to improving airline efficiency and promoting the development of the aviation industry. Taking China Southern Airlines as an example, the study finds that the airline’s dynamic pricing strategy is flexible, market-differentiated and time-sensitive by collecting fare data of different routes from April 2023 to May 2023, and analysing the characteristics of the dynamic pricing strategy based on the characteristics of fare fluctuations. The study finds that the airline’s dynamic pricing strategy has flexibility, market variability and time sensitivity. The results of the study have certain reference value for exploring the nature of the airline’s dynamic pricing strategy, optimising the airline’s operation and revenue management, and promoting the prosperous development of the whole aviation industry.

MicroRNAs (miRNAs) and natural antisense transcripts (NATs) control many biological processes and have been broadly applied for genetic manipulation of eukaryotic gene expression. Still unclear, however, are whether and how NATs regulate miRNA production. Here, we report that the cis -NATs of MIR398 genes repress the processing of their pri-miRNAs. Through genome-wide analysis of RNA sequencing data, we identify cis -NATs of MIRNA genes in Arabidopsis and Brassica. In Arabidopsis, MIR398b and MIR398c are coexpressed in vascular tissues with their antisense genes NAT398b and NAT398c , respectively. Knock down of NAT398b and NAT398c promotes miR398 processing, resulting in stronger plant thermotolerance owing to silencing of miR398-targeted genes; in contrast, their overexpression activates NAT398b and NAT398c , causing poorer thermotolerance due to the upregulation of miR398-targeted genes. Unexpectedly, overexpression of MIR398b and MIR398c activates NAT398b and NAT398c . Taken together, these results suggest that NAT398b/c repress miR398 biogenesis and attenuate plant thermotolerance via a regulatory loop. MiRNAs and natural antisense transcripts can both regulate gene expression and plant development. Here, the authors show that cis -NATs to MIR398 repress processing of pri-miR398 and that cis -NAT expression is downregulated at high temperatures, contributing to miR398 mediated thermotolerance responses.

This study aimed to evaluate the positive effects on anti-oxidation, anti-inflammation, and microbial composition optimization of diabetic mice using tussah (Antheraea pernyi) silk fibroin peptides (TSFP), providing the theoretical foundation for making the use of silk resources of A. pernyi and incorporating as a supplement into the hypoglycemic foods. The animal model of diabetes was established successfully. Alloxan-induced diabetic mice were orally administered using TSFP, and the hypoglycaemic effects in vivo were systematically investigated. The results indicated that TSFP could significantly reduce the fasting blood glucose (FBG) levels and suppress the mRNA expression of glycometabolism genes of diabetic mice. In addition, the TSFP could ameliorate the lipid dysbolism and contribute to a higher anti-oxidation capacity. Moreover, TSFP could alleviate pathological damages and hinder inflammatory processes of diabetic mice. Besides, the supplementation of TSFP presented a greater ability to shape and optimize the gut microbial composition by enriching the profitable bacteria and inhibiting the pathogenic microorganisms. Correlation analysis also revealed that the abundances of functional bacteria in the TSFP-treated groups exhibited better correlations with serum parameters, which would be of positive significance for blood glucose regulation and inflammation remission. These results collectively corroborated the feasibility and superiority of using TSFP for hyperglycaemia remission via anti-oxidation enhancement, inflammation alleviation, and microbial composition optimization, contributing to a safely feasible and biologically efficient strategy for improving anti-diabetic effects.

Dibutyl phthalate (DBP) with teratogenicity, carcinogenesis, and mutagenesis, is a ubiquitous endocrine disruptor in the environment. The widespread usage of plastic mulch has resulted in a severe DBP pollution problem in agricultural soil. One of the most vital ways to mitigate the DBP pollution problem is to use DBP degrading bacteria to reduce the concentration of DBP in agricultural soil. DBP degrading bacteria studied in previous studies mainly come from sewage treatment plants, rivers, landfills, bioreactors, and other environmental media. At the same time, there was relatively little research on DBP degrading bacteria in agricultural soil. Therefore, using the pure culture approach, the candidate DBP degrading strains were isolated and screened from vegetable plots contaminated with plastic mulch in Dayi County, Chengdu City, Sichuan Province, China. The taxonomy of the strains was determined using the 16 sedimentation ribosomal deoxyribonucleic acid (16S rDNA) molecular technique. Furthermore, ultraviolet and visible spectrophotometry and high performance liquid chromatography (HPLC) were used to assess the degrading capability of strains. The findings showed that a total of twenty-six DBP degrading strains were screened from vegetable plots contaminated with plastic mulch in Dayi County, Chengdu City, Sichuan Province, China, and these strains belonged to two phyla: Proteobacteria and Bacillota , eight families, including Pseudomonas , Enterobacteriaceae , and Bacillaceae , as well as ten genera, such as Enterobacter , Pseudomonas , and Bacillus . One of them, the strain SWDB-7 was a potentially new species in the Enterobacter genus. The most prominent genus of the isolated strains was Enterobacter . There were significant variations in the degradation capability of different obtained DBP degrading strains. and their degradation efficiency was 14.12%-91.86%. With a total DBP removal rate of 91.86%, strain SWDB-15 had the most effective degrading capability among them. To sum up, the DBP degrading strains in vegetable plots contaminated with plastic mulch in Dayi County, Chengdu City, Sichuan Province, China are rich in diversity and capable of breaking down DBP.

HighlightsThe advancement and current status of dual-atom catalysts are reported.The synergistic effects exhibited by recent dual-atom catalysts in mechanistic studies are classified and summarized.Challenges and prospects of dual-atom catalysts in synthesis, characterization, applications, and theory are discussed.The exploration of sustainable energy utilization requires the implementation of advanced electrochemical devices for efficient energy conversion and storage, which are enabled by the usage of cost-effective, high-performance electrocatalysts. Currently, heterogeneous atomically dispersed catalysts are considered as potential candidates for a wide range of applications. Compared to conventional catalysts, atomically dispersed metal atoms in carbon-based catalysts have more unsaturated coordination sites, quantum size effect, and strong metal–support interactions, resulting in exceptional catalytic activity. Of these, dual-atomic catalysts (DACs) have attracted extensive attention due to the additional synergistic effect between two adjacent metal atoms. DACs have the advantages of full active site exposure, high selectivity, theoretical 100% atom utilization, and the ability to break the scaling relationship of adsorption free energy on active sites. In this review, we summarize recent research advancement of DACs, which includes (1) the comprehensive understanding of the synergy between atomic pairs; (2) the synthesis of DACs; (3) characterization methods, especially aberration-corrected scanning transmission electron microscopy and synchrotron spectroscopy; and (4) electrochemical energy-related applications. The last part focuses on great potential for the electrochemical catalysis of energy-related small molecules, such as oxygen reduction reaction, CO2 reduction reaction, hydrogen evolution reaction, and N2 reduction reaction. The future research challenges and opportunities are also raised in prospective section.

Driven by solid economic developments, emerging economies are experiencing significant institutional change, particularly in regulatory structures and market systems. Coupled with fierce market competition and reforms, serious challenges for the sustainable development of new ventures are created due to smallness and newness liabilities. This study examines how new ventures grow and adapt to the rapid environmental shifts in emerging economies by exploring the effects of entrepreneurial bricolage. This study found that entrepreneurial bricolage has a positive impact on both new venture growth and adaptiveness. Further, institutional voids have contrasting effects on these two relationships. The effectiveness of entrepreneurial bricolage on new venture growth is stronger in a context with serious institutional voids, while the effectiveness of entrepreneurial bricolage on new venture adaptiveness is weaker in a context with serious institutional voids. These findings not only enrich our knowledge on the implications of entrepreneurial bricolage, but also advance our understanding of the emerging economy context.

Background Previous studies have identified that socioeconomic status (SES) and obesity are associated with hypertension. However, their interaction on hypertension risk has not yet been assessed. Methods The study used data from 6,069 Tibetan residents in Chengguan District in Lhasa, the Chinese Tibetan autonomous region’s capital, based on a cohort study conducted from May 2018 to September 2019 in five provinces in southwest China. We used logistic regression models to assess the complex relations of SES and obesity with hypertension. Results Compared with individuals of high SES, low and moderate SES were positively associated with high risk of hypertension. SES and obesity have significant additive interaction on hypertension (general obesity by BMI: RERI = 1.33, P < 0.001; abdominal obesity by WC: RERI = 0.76, P < 0.001; abdominal obesity by WHtR: RERI = 0.96, P < 0.001). In people from the low and moderate SES segments, obesity was linked to an increased risk of hypertension, but the correlations were stronger in people from the moderate SES category. Compared with people of high SES and non obese, those with moderate SES and obesity had a higher risk of hypertension, and ORs were 4.38 (2.80, 6.84) for general obesity by BMI, 3.38 (2.05, 5.57) for abdominal obesity by WC, and 3.18 (1.57, 6.42) for abdominal obesity by WHtR. Conclusion There is an independent and additive interaction effect of obesity and SES on the risk of hypertension. People with obesity, especially those of moderate and low SES, should reduce weight and waist circumference, and pay more attention to blood pressure. Moreover, the government, health administration departments, and society should prioritize improving the socioeconomic status of the Tibetan population and addressing risk factors like obesity.

Predicting compound-protein interactions (CPIs) plays a crucial role in drug discovery. Traditional methods, based on the key-lock theory and rigid docking, often fail with novel compounds and proteins due to their inability to account for molecular flexibility and the high sparsity of CPI data. Here, we introduce ColdstartCPI, a framework inspired by induced-fit theory, which leverages unsupervised pre-training features and a Transformer module to learn both compound and protein characteristics. ColdstartCPI treats proteins and compounds as flexible molecules during inference, aligning with biological insights. It outperforms state-of-the-art sequence-based models, particularly for unseen compounds and proteins, and shows strong generalization capability compared to structure-based methods in virtual screening. ColdstartCPI also excels in sparse and low-similarity data conditions, demonstrating its potential in data-limited settings. Our results are validated through literature search, molecular docking, and binding free energy calculations. Overall, ColdstartCPI offers a perspective on sequence-based drug design, presenting a promising tool for drug discovery. Existing models for predicting compound-protein interactions (CPIs) struggle with novel molecules and sparse data. Here, authors introduce a framework that combines pre-trained feature extraction with transformer dynamic tuning to improve CPI prediction.

With the continuous advancement of industrial intelligence, the application of hydraulic robots is becoming increasingly widespread, and the demand for their health diagnosis and maintenance is becoming more urgent. By integrating digital twin (DT) and deep learning technologies, this paper presents an intelligent fault diagnosis method for hydraulic robots based on multi-source information fusion. Firstly, a fault diagnosis architecture and solution for hydraulic robots based on DT technology are proposed. Secondly, a DT model of the hydraulic robot, which incorporates a 3D model and an attribute model with virtual–physical synchronization capabilities, is established, and a calibration method for the twin model is explored. Next, for four typical faults—leakage in the hydraulic system, valve sticking, damping hole blockage, and filter blockage—fault mechanism analysis and evolution process simulation are conducted on the established DT model. A multi-source high-quality dataset, covering normal operating conditions and multiple fault scenarios, is constructed to drive the data twin model. Finally, a feature extraction method combining Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and Attention mechanisms is proposed. This is followed by using a Random Forest (RF) classifier to achieve accurate fault diagnosis for various hydraulic system failures. The experimental results validate the effectiveness and practicality of this method.

Soil aggregate formation and stabilization are pivotal for remediating saline-alkali soils, but the potential of cooling-phase organic fertilizer (CPOF)—a transitional stage in composting—has been overlooked. This study systematically investigated the regulatory effects of CPOF on saline soil aggregate systems, focusing on two key objectives: (1) comparing the efficacy of CPOF with organic fertilizers from other composting phases (initial, thermophilic, matured) in enhancing macroaggregate proportion and stability; and (2) clarifying how CPOF’s unique organic components influence carbon speciation across aggregate size fractions. Our results demonstrated that CPOF outperformed other composting phases in improving soil physical properties and aggregate dynamics. It reduced soil bulk density by 18.5% and increased porosity by 22.3%, driven by three mechanisms: (1) dominant humification microorganisms (e.g., Actinobacteria) secreting extracellular polymeric substances (EPS) that bind soil particles; (2) a balanced ratio of labile and stable organic components, providing both immediate binding agents and long-term humic substances; and (3) enhanced microbial-mineral interactions via ligand exchange and cation bridging. In aggregate dynamics, CPOF significantly promoted macroaggregate (>0.25 mm) formation and stability, with peak effects at 180 days. This was attributed to fungal communities (e.g., Peniophora, Mucorales) producing glomalin-related soil proteins (GRSP) and calcium-mediated particle bridging. CPOF also increased organic carbon content in macroaggregates by 18–22% through labile carbon (supporting microbial activity) and transitional humic substances (facilitating long-term sequestration), with sustained stability over 540 days. These findings highlight CPOF as a time-sensitive amendment that synchronizes microbial activity with physical carbon protection, offering a scalable solution for saline soil rehabilitation. A proposed two-phase strategy—initial CPOF application for rapid improvement, followed by mature compost for long-term maintenance—could enhance carbon sequestration efficiency by 15–20% in regions like the Yellow River Basin, supporting climate-smart agriculture and global saline soil management.