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Composition-dependent interdiffusion coefficients are key parameters in many physical processes. However, finding such coefficients for a system with few components is challenging due to the underdetermination of the governing diffusion equations, the lack of data in practice, and the unknown parametric form of the interdiffusion coefficients. In this work, we propose InfPolyn, Infinite Polynomial, a novel statistical framework to characterize the component-dependent interdiffusion coefficients. Our model is a generalization of the commonly used polynomial fitting method with extended model capacity and flexibility and it is combined with the numerical inversion-based Boltzmann–Matano method for the interdiffusion coefficient estimations. We assess InfPolyn on ternary and quaternary systems with predefined polynomial, exponential, and sinusoidal interdiffusion coefficients. The experiments show that InfPolyn outperforms the competitors, the SOTA numerical inversion-based Boltzmann–Matano methods, with a large margin in terms of relative error (10× more accurate). Its performance is also consistent and stable, whereas the number of samples required remains small.

Wool quality and yield are two important economic livestock traits. However, there are relatively few molecular studies on lncRNA for improving sheep wool, so these require further exploration. In this study, we examined skin tissue from the upper scapula of Super Merino (SM) and Small-Tailed Han (STH) sheep during the growing period. The apparent difference was verified via histological examination. High-throughput RNA sequencing identified differentially expressed (DE) long non-coding (lncRNAs) and messenger RNAs (mRNAs). The target gene of DE lncRNA and DE genes were enrichment analyzed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). A Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) was used to verify randomly selected DE lncRNAs and mRNAs. Finally, the DE, RAC2, WNT11, and FZD2 genes, which were enriched in the Wnt signaling pathway, were detected via immunohistochemistry. The results showed that a total of 20,888 lncRNAs and 31,579 mRNAs were identified in the skin tissues of the two sheep species. Among these, 56 lncRNAs and 616 mRNAs were differentially expressed. Through qRT-PCR, the trends in the randomly selected DE genes’ expression were confirmed to be aligned with the RNA-seq results. GO and KEGG enrichment analysis showed that DE lncRNA target genes were enriched in GO terms as represented by epidermal and skin development and keratin filature and in KEGG terms as represented by PI3K-Akt, Ras, MAPK, and Wnt signaling pathways, which were related to hair follicle growth and development. Finally, immunohistochemistry staining results indicated that RAC2, WNT11, and FZD2 were expressed in dermal papilla (DP). The lncRNAs MSTRG.9225.1 and MSTRG.98769.1 may indirectly participate in the regulation of hair follicle growth, development, and fiber traits by regulating their respective target genes, LOC114113396(KRTAP15-1), FGF1, and IGF1. In addition, MSTRG.84658.1 may regulate the Wnt signaling pathway involved in the development of sheep hair follicles by targeting RAC2. This study provides a theoretical reference for improving sheep breeding in the future and lays a foundation for further research on the effects of MSTRG.84658.1 and the target gene RAC2 on dermal papilla cells (DPC).

The conjugate of rhein and artesunate have shown promising effects in inducing immunogenic cell death (ICD) and inhibiting tumor growth. Rhein, a natural anthraquinone derivative found in various medicinal plants such as Rheum palmatum, possesses diverse pharmacological properties including anti-inflammatory and anticancer activities. Artesunate, a sesquiterpene lactone extracted from Artemisia annua, exhibits potent antimalarial efficacy and has garnered attention for its potential anticancer properties. Through rational drug design, the conjugation of rhein with artesunate has yielded compounds capable of selectively targeting mitochondria of cancer cells, inducing oxidative stress-mediated ICD, and enhancing the immunogenicity of tumor cells. The conjugate leverages the inherent cytotoxicity of artesunate while incorporating the capability to selectively target the mitochondria of rhein, thereby fostering a special approach to immunotherapy for cancer. Upon accumulation in the mitochondria, these compounds induce the generation of reactive oxygen species (ROS), leading to mitochondrial membrane potential (ΔΨm) reduction and endoplasmic reticulum (ER) stress. Notably, the conjugate exhibits far more potent ICD-inducing properties than their parent compounds. In vivo studies have demonstrated that the vaccine, when treated with the conjugate, effectively suppresses tumor growth.

The gut microbiome (GMB) has been extensively reported to be associated with the development and prognosis of human diseases. This study aims to investigate the relationship between GMB composition and chemotherapy efficacy in diffuse large B-cell lymphoma (DLBCL). We demonstrated that DLBCL patients at diagnosis have altered GMB compositions. Significant enrichment of the Proteobacteria phylum in DLBCL patients was observed. Gene analysis showed a high abundance of virulence factors genes. We found baseline GMB to be associated with clinical outcomes. The emergence of Lactobacillus fermentum was correlated with better treatment outcome. Our pilot results suggested a correlation between GMB composition and DLBCL development and prognosis. Clues from our study, together with previous research, provided a rational foundation for further investigation on the pathogenesis, prognosis value, and targeted therapy of GMB in DLBCL.

This review elucidates the critical role of ghrelin, a peptide hormone mainly synthesized in the stomach in various gastrointestinal (GI) diseases. Ghrelin participates in diverse biological functions ranging from appetite regulation to impacting autophagy and apoptosis. In sepsis, it reduces intestinal barrier damage by inhibiting inflammatory responses, enhancing GI blood flow, and modulating cellular processes like autophagy and apoptosis. Notably, in inflammatory bowel disease (IBD), serum ghrelin levels serve as markers for distinguishing between active and remission phases, underscoring its potential in IBD treatment. In gastric cancer, ghrelin acts as an early risk marker, and due to its significant role in increasing the proliferation and migration of gastric cancer cells, the ghrelin–GHS-R axis is poised to become a target for gastric cancer treatment. The role of ghrelin in colorectal cancer (CRC) remains controversial; however, ghrelin analogs have demonstrated substantial benefits in treating cachexia associated with CRC, highlighting the therapeutic potential of ghrelin. Nonetheless, the complex interplay between ghrelin’s protective and potential tumorigenic effects necessitates a cautious approach to its therapeutic application. In post-GI surgery scenarios, ghrelin and its analogs could be instrumental in enhancing recovery and reducing complications. This article accentuates ghrelin’s multifunctionality, shedding light on its influence on disease mechanisms, including inflammatory responses and cancer progression, and examines its therapeutic potential in GI surgeries and disorders, advocating for continued research in this evolving field.

Organophosphates are a type of emerging environmental contaminant, which can be removed effectively by adsorption. Here, modified steel slag was examined for its adsorptive performance in the removal of hydroxyethylidene diphosphonic acid (HEDP) from water. Compared to acid (55.3%, maximum removal rate) and base (85.5%) modification, high-temperature modification (90.6%) significantly enhanced steel slag’s adsorption capacity for HEDP, surpassing that of unmodified slag (71.2%). Kinetic analyses elucidated a two-phase adsorption process—initial rapid adsorption followed by a slower equilibrium phase. The results of adsorption energy analysis showed that modified steel slag preferentially occupied the sites with higher energy, which promoted the adsorption. After five regeneration cycles, the adsorption properties of the material were not significantly reduced, which indicates that the material has good application potential. Microscopic and spectroscopic techniques, including SEM-EDS, FTIR, and XPS, were employed to uncover the surface chemistry and structural changes responsible for the enhanced adsorption efficiency. The adsorption mechanism of HEDP on steel slag is a complete process guided by hydrogen bonding interactions, strengthened surface complexation, and optimized ligand exchange. This study advances the sustainable utilization of industrial waste materials and contributes significantly to the development of innovative water treatment technologies.

Due to the physical characteristics of acoustic channels, the performance of underwater acoustic communication networks (UACNs) is more susceptible to the impacts of multipath and Doppler effects. Channel quality can serve as a measure of the reliability of underwater communication links. A cross-layer routing protocol based on channel quality (CLCQ) is proposed to improve the overall network performance and resource utilization. First, the BELLHOP ray model is used to calculate the channel impulse response combined with the winter sound speed profile data of a specific sea area. Then, the channel impulse response is integrated into the communication system to evaluate the channel quality between nodes based on the bit error rate (BER). Finally, during the selection of the next hop node, a reinforcement learning algorithm is employed to facilitate cross-layer interaction within the protocol stack. The optimal relay node is determined by the channel quality index (BER) from the physical layer, the buffer state from the data link layer, and the node residual energy. To enhance the algorithm’s convergence speed, a forwarding candidate set selection method is proposed which takes into account node depth, residual energy, and buffer state. Simulation results show that the packet delivery rate (PDR) of the CLCQ is significantly higher than that of Q-Learning-Based Energy-Efficient and Lifetime-Extended Adaptive Routing (QELAR) and Geographic and Opportunistic Routing (GEDAR).

Energy storage (ES) units are vital for the reliable and economical operation of the power system with a high penetration of renewable distributed generators (DGs). Due to ES’s high investment costs and long payback period, energy management with shared ESs becomes a suitable choice for the demand side. This work investigates the sharing mechanism of ES units for low-voltage (LV) energy prosumer (EP) communities, in which energy interactions of multiple styles among the EPs are enabled, and the aggregated ES dispatch center (AESDC) is established as a special energy service provider to facilitate the scheduling and marketing mechanism. A shared ES operation framework considering multiple EP communities is established, in which both the energy scheduling and cost allocation methods are studied. Then a shared ES model and energy marketing scheme for multiple communities based on the leader–follower game is proposed. The Karush–Kuhn–Tucker (KKT) condition is used to transform the double-layer model into a single-layer model, and then the large M method and PSO-HS algorithm are used to solve it, which improves convergence features in both speed and performance. On this basis, a cost allocation strategy based on the Owen value method is proposed to resolve the issues of benefit distribution fairness and user privacy under current situations. A case study simulation is carried out, and the results show that, with the ES scheduling strategy shared by multiple renewable communities in the leader–follower game, the energy cost is reduced significantly, and all communities acquire benefits from shared ES operators and aggregated ES dispatch centers, which verifies the advantageous and economical features of the proposed framework and strategy. With the cost allocation strategy based on the Owen value method, the distribution results are rational and equitable both for the groups and individuals among the multiple EP communities. Comparing it with other algorithms, the presented PSO-HS algorithm demonstrates better features in computing speed and convergence. Therefore, the proposed mechanism can be implemented in multiple scenarios on the demand side.

Postharvest grapes exhibit a limited shelf life due to susceptibility to rot and deterioration, significantly reducing their nutritional and economic value. Sulfur dioxide (SO2) is a widely recognized preservative for extending grape storage life. This study performed a detailed analysis of ‘Munage’ table grapes treated with SO2 fumigation, employing transcriptomic and metabolomic approaches. Results indicate that SO2 fumigation significantly extends the shelf life of grapes, as demonstrated by improved visual quality, reduced decay rates, and increased fruit firmness. We identified 309 differentially accumulated metabolites (DAMs) and 1906 differentially expressed genes (DEGs), including 135 transcription factors (TFs). Both DEGs and DAMs showed significant enrichment of flavonoid-related metabolism compared with the control, and the relative content of four flavonoid metabolites (Wogonin-7-O-glucuronide, Acacetin-7-O-glucuronide, Apigenin-7-O-glucuronide, and Baicalein 7-O-glucuronide) were significantly increased in grapes upon SO2 treatment, suggesting that SO2 treatment had a substantial regulatory effect on grape flavonoid metabolism. Importantly, we constructed complex regulatory networks by screening key enzyme genes (e.g., PAL, 4CLs, CHS, CHI2, and UGT88F3) related to the metabolism of target flavonoid, as well as potential regulatory transcription factors (TFs). Overall, our findings offer new insights into the regulatory mechanisms by which SO2 maintains the postharvest quality of table grapes.

Being a type of carbonaceous material, glassy carbon possesses thermomechanical properties akin to ceramics, offering both mechanical and chemical stability at high temperatures; therefore, it can be applied in electrochemistry and high-temperature manufacturing. However, the direct pyrolysis of a bulk precursor leads to internal pores and cracks, usually resulting in fracture. Our characterization results show that at temperatures below 400 °C, large pores do not form, and pre-carbonized glassy carbon (PGC) formed at 350 °C has a dense microstructure without cracks. It exhibits a high compressive strength of ~370 MPa and flexural strength of ~190 MPa, making it suitable for load-bearing applications. Additionally, the PGC-350 material shows small mass loss (~5%) and reasonably low thermal expansion (2.5 × 10−6/°C) when heated to 350 °C again. These properties suggest the potential of PGC for high-temperature applications. As a demonstration, PGC formed at 350 °C was employed to fabricate molds to press chalcogenide glass blanks, which exhibited favorable molding results for various surface morphologies.

With the inherent demand for hydrophobic materials in processes such as membrane distillation and unidirectional moisture conduction, the preparation and application development of profiles such as modified cellulose acetate membranes that have both hydrophobic functions and biological properties have become a research hotspot. Compared with the petrochemical polymer materials used in conventional hydrophobic membrane preparation, cellulose acetate, as the most important cellulose derivative, exhibits many advantages, such as a high natural abundance, good film forming, and easy modification and biodegradability, and it is a promising polymer raw material for environmental purification. This paper focuses on the research progress of the hydrophobic cellulose acetate preparation process and its current application in the water-treatment and resource-utilization fields. It provides a detailed introduction and comparison of the technical characteristics, existing problems, and development trends of micro- and nanostructure and chemical functional surface construction in the hydrophobic modification of cellulose acetate. Further review was conducted and elaborated on the applications of hydrophobic cellulose acetate membranes and other profiles in oil–water separation, brine desalination, water-repellent protective materials, and other separation/filtration fields. Based on the analysis of the technological and performance advantages of profile products such as hydrophobic cellulose acetate membranes, it is noted that key issues need to be addressed and urgently resolved for the further development of hydrophobic cellulose acetate membranes. This will provide a reference basis for the expansion and application of high-performance cellulose acetate membrane products in the environmental field.

Multisource data fusion technology integrates the strengths of various data sources, addressing the limitations of relying on a single source. Therefore, it has been widely applied in fields such as lithological classification and mineral exploration. However, traditional deep learning algorithms fail to distinguish the importance of different features effectively during fusion, leading to insufficient focus in the model. To address this issue, this paper introduces a ResHA network based on a hybrid attention mechanism to fuse features from ASTER remote sensing images, geochemical data, and DEM data. A case study was conducted in the Altay Orogenic Belt to demonstrate the lithological classification process. This study explored the impact of the submodule order on the hybrid attention mechanism and compared the results with those of MLP, KNN, RF, and SVM models. The experimental results show that (1) the ResHA network with hybrid attention mechanisms assigned reasonable weights to the feature sets, allowing the model to focus on key features closely related to the task. This resulted in a 7.99% improvement in classification accuracy compared with that of traditional models, significantly increasing the precision of lithological classification. (2) The combination of channel attention followed by spatial attention achieved the highest overall accuracy, 98.06%.

In recent years, remote sensing has experienced a significant transformation due to rapid advancements in deep learning technology, which have greatly outpaced traditional methodologies. This integration has attracted substantial interest within the academic community. To address the complex challenges of extracting data on intricate water bodies during disaster scenarios, this study developed a post-disaster floodwater body dataset and an enhanced multi-scale transformer model architecture. Through end-to-end training, the precision of the model in extracting floodwater contours has been significantly improved. Additionally, by utilizing the vast amounts of unannotated data in remote sensing through an unsupervised pre-training task, the model’s backbone network has been fortified, greatly enhancing its performance in remote sensing applications. Experimental analyses have shown that the multi-scale transformer-based algorithm for floodwater contour extraction proposed in this study is not only widely applicable but also excels in delivering precise segmentation results in complex environments. This refined approach ensures that the model adeptly handles the intricacies of floodwater body delineation, providing a robust solution for accurate extraction, even in disaster-stricken areas. This innovation represents a substantial leap forward in remote sensing, offering valuable insights and tools for disaster management and environmental monitoring.

Animal pose estimation is crucial for animal health assessment, species protection, and behavior analysis. It is an inevitable and unstoppable trend to apply deep learning to animal pose estimation. In many practical application scenarios, pose estimation models must be deployed on edge devices with limited resource. Therefore, it is essential to strike a balance between model complexity and accuracy. To address this issue, we propose a lightweight network model, i.e., MPE-HRNet.L, by improving Lite-HRNet. The improvements are threefold. Firstly, we improve Spatial Pyramid Pooling-Fast and apply it and the improved version to different branches. Secondly, we construct a feature extraction module based on a mixed pooling module and a dual spatial and channel attention mechanism, and take the feature extraction module as the basic module of MPE-HRNet.L. Thirdly, we introduce a feature enhancement stage to enhance important features. The experimental results on the AP-10K dataset and the Animal Pose dataset verify the effectiveness and efficiency of MPE-HRNet.L.

Ethyl acetate is a critical medical indicator for detecting certain types of cancer. However, at present, available sensitive materials often exhibit drawbacks, such as high operating temperatures and poor responses to low concentrations of ethyl acetate. In this study, a ZnO nanorod sensing material was prepared using high-temperature annealing and a hydrothermally synthesized metal-organic framework (MOF) as a template. Au nanodots (AuNDs) were subsequently modified on the ZnO nanorods using an in situ ion reduction, which provided a better dispersion of Au nanodots compared with that obtained using the common reductant method. A variety of characterization methods indicate that the highly dispersed AuNDs, which possess a high catalytic activity, were loaded onto the surface as active centers, leading to a significant augmentation in the adsorption of oxygen on the surface compared with the original ZnO material. Consequently, the AuND@ZnO material exhibited heightened responsiveness to ethyl acetate at a lower operating temperature. The Au@ZnO-based sensor has a response rate (Ra/Rg) of 41.8 to 20 ppm ethyl acetate gas at 140 °C, marking a 17.4-fold increase compared with that of the original material. Due to its low power consumption and high responsiveness, AuND@ZnO is a promising candidate for the detection of ethyl acetate gas in medical applications.

Traditional villages along the Jinzhong section of the Wanli Tea Road possess unique geographical locations and cultural heritage, showcasing a rich variety of cultural landscapes. Among these, village temple buildings play a crucial role as the core of spiritual and belief life in traditional villages. In the context of rapid urbanization and modernization, a new perspective is needed to thoroughly explore the deeper connotations of cultural landscape characteristics in traditional villages along the Wanli Tea Road, particularly by examining the composition and inherent features of their landscape genes. This study employs landscape gene theory, using the village temple system as a lens to identify and analyze the landscape genes of traditional villages along the Jinzhong section of the Wanli Tea Road. Based on the results, a genealogy and a map of landscape genes are constructed to clearly and effectively present the typical characteristics and expressions of these genes in a logical and visual manner. The findings indicate the following: (1) The village temple system in traditional villages along the Jinzhong section of the Wanli Tea Road is closely related to the formation and expression of their landscape genes and can play a critical role in the protection and transmission of cultural landscapes. (2) As important nodes along the historical trade route, the landscape gene characteristics of these villages reflect their unique natural environments and historical development trajectories, illustrating the deep intertwining of commercial activities and local cultural landscapes. (3) This study establishes a replicable research framework that is not only applicable to local studies but also provides valuable references for broader cultural landscape research.

Background: Pentosidine is an advanced glycation end product that is commonly found in heat-processed foods. Pentosidine has been involved in the occurrence and development of some chronic diseases. It was reported that pentosidine exposure can impair the function of the liver and kidneys. Adipose tissue, as an active endocrine organ, plays an important role in maintaining the normal physiological function of cells. However, the metabolic mechanism that causes pentosidine to induce toxicity in adipose tissue remains unclear. Methods: In the study, thirty male Sprague-Dawley rats were divided into a normal diet group, low dose group, and high dose group. A non-targeted metabolomics approach was used to compare the metabolic profiles of adipose tissue between the pentosidine and normal diet groups. Furthermore, histopathological observation and body weight change analysis were performed to test the results of the metabolomics analysis. Results: A total of forty-two differential metabolites were identified. Pentosidine mainly disturbed twelve metabolic pathways, such as ascorbate and aldarate metabolism, glycine, serine, and threonine metabolism, sulfur metabolism, pyruvate metabolism, etc. Additionally, pyruvic acid was identified as a possible key upregulated metabolite involved in thirty-four metabolic pathways. α-Ketoglutaric acid was named as a probable key downregulated metabolite involved in nineteen metabolic pathways based on enrichment network analysis. In addition, histopathological analysis and body weight changes confirmed the results of the metabolomics analysis. Conclusions: These results provided a new perspective for the molecular mechanisms of adipose tissue toxicity induced by pentosidine.

Mooring chains are key components of offshore floating photovoltaic systems. Although their service safety is often affected by the harsh service environment, the influence of surface roughness on their corrosion resistance is not clear. This study investigated the corrosion behavior of mooring chain steel using cyclic salt-spray corrosion and electrochemical tests. Scanning electron microscopy, energy-dispersive spectrometry, optical profilometry, and other analytical techniques were used to study the composition and morphology of the corrosion products. The corrosion behavior was studied by electrochemical polarization curves, alternating current impedance spectroscopy, and X-ray photoelectron spectroscopy. The results show that the salt-spray corrosion resistance of mooring chain steel significantly improved with the reduction in specimen surface roughness, and the number and depth of corrosion pits were reduced. Mass loss after 24 h of salt-spray corrosion was exponentially related to initial roughness (Ra). Improved surface roughness significantly increased the pitting potential of the specimens, widened the passivation range, and enhanced the repassivation capability, thus significantly improving the pitting resistance. The pitting potential is linearly related to the initial roughness of the specimen. The oxide contents of Fe, Mo, and Si in the passivation film tended to increase with a smoother surface, which contributes to its densification. This effectively blocks chloride ion attack, thus improving the corrosion resistance of the mooring chain steel.

The utilization of SPI-Flash in embedded systems is widespread, primarily serving as program storage during the boot process. As a result, the boot process is influenced to some extent by the SPI-Flash controller. This paper presents a lightweight SPI-Flash controller that simplifies the boot process design by establishing a direct connection between the SPI-Flash and AHB-lite bus interface, enabling rapid program execution in RAM instead of directly from the SPI-Flash. Additionally, the controller can function as a bare-metal program downloader for testing the boot process functionality during FPGA-based SoC (system-on-chip) prototype verification. The system-level simulation and FPGA verification results demonstrate that the proposed SPI-Flash controller successfully achieves its intended functional impact in operations to target the Micron N25Q256A SPI-Flash chip, boot process design, and bare-metal program download. The synthesis results under the SMIC 180 nm 1P8M technology process indicate that this SPI-Flash controller exhibits remarkable performance, power consumption, and area utilization. The source code of the proposed lightweight SPI-Flash controller has been uploaded to GitHub as an open-source project.

Exopolysaccharides (EPSs) produced by microorganisms play an important role in biotolerance and reducing heavy metal (HM) contamination by limiting the migration of HMs into plants. However, research on the application of EPS-producing marine bacteria for soil heavy metal remediation remains limited, particularly regarding their mechanisms of HM immobilization in soil and impact on plant growth. In this study, the EPS-producing marine bacterium Micrococcus antarcticus HZ was investigated for its ability to immobilize Pb and produce EPSs in soil filtrate. The effects on the growth quality and biomass of pakchoi (Brassica chinensis L.), as well as bacterial communities in inter-root soil contaminated with Pb, were also investigated. The results indicated that HZ could reduce the Pb concentration in the soil filtrate, achieving a removal rate of 43.25–63.5%. The EPS content and pH levels increased in the presence of Pb. Pot experiments showed that adding HZ significantly increased the biomass of pakchoi (9.45–14.69%), vitamin C (Vc) (9.69–12.92%), and soluble protein content (22.58–49.7%). HZ reduced the Pb content in the roots (17.52–47.48%) and leaves (edible tissues) (43.82–52.83%) of pakchoi. HZ increased soil enzyme activities (alkaline phosphatase, dehydrogenase, and urease), and the contents of ammonium nitrogen and nitrate nitrogen. Additionally, HZ also increased the relative abundance of beneficial bacteria (e.g., Proteobacteria, Cyanobacteria, and Chlorobacteria) in the inter-root soil, which have prophylactic and heavy-metal fixation functions. In summary, HZ reduces effective Pb content in edible tissues, roots, and inter-root soil by regulating inter-root soil microbial community structure, increasing soil pH, nitrogen content, and soil enzyme activity, and altering dominant phylum abundance.

Porcine respiratory disease is a significant economic problem for the global swine industry. Haemophilus parasuis (H. parasuis), Streptococcus suis (S. suis), and Pasteurella multocida (P. multocida) are three important pathogenic bacteria of the swine respiratory tract. Notably, the three pathogens not only frequently manifest as mixed infections, but their striking clinical similarities also present difficulties for pig populations in terms of disease prevention and treatment. Thus, we developed a triplex real-time quantitative polymerase chain reaction (qPCR) assay based on a TaqMan probe for the detection of H. parasuis, S. suis serotype 2, and P. multocida. Primers and probes were designed to target the conserved regions of the H. parasuis OmpP2 gene, the S. suis serotype 2 gdh gene, and the P. multocida Kmt1 gene. By optimizing the reaction system and conditions, a triplex qPCR method for simultaneous detection of H. parasuis, S. suis serotype 2, and P. multocida was successfully established. The amplification efficiencies of the standard curves for all three pathogens were found to be highly similar, with values of 102.105% for H. parasuis, 105.297% for S. suis serotype 2, and 104.829% for P. multocida, and all R2 values achieving 0.999. The specificity analysis results showed that the triplex qPCR method had a strong specificity. The sensitivity test results indicated that the limit of detection can reach 50 copies/μL for all three pathogens. Both intra- and inter-assay coefficients of variation for repeatability were below 1%. This triplex qPCR method was shown to have good specificity, sensitivity, and reproducibility. Finally, the triplex qPCR method established in this study was compared with the nested PCR as recommended by the Chinese national standard (GB/T34750-2017) for H. parasuis, the PCR as recommended by the Chinese national standard (GB/T 19915.9-2005) for S. suis serotype 2, and the PCR as recommended by the Chinese agricultural industry standard (NY/T 564-2016) for P. multocida by detecting the same clinical samples. Both methods are reasonably consistent, while the triplex qPCR assay was more sensitive. In summary, triplex qPCR serves not only as a rapid and accurate detection and early prevention method for these pathogens but also constitutes a robust tool for microbial quality control in specific pathogen-free pigs.

The effects of fallow season water and straw management on methane (CH4) emissions during the fallow season and the subsequent rice-growing season are rarely reported, and the underlying microbial mechanisms remain unclear. A field experiment was conducted with four treatments: (1) fields flooded in both the fallow and rice seasons (FF), (2) fields drained in the fallow season and flooded in the rice season (DF), (3) FF with straw retention (FFS), and (4) DF with straw retention (DFS). The CH4 emissions in fields under different water and straw treatments were monitored using the static closed chamber method. Methanogenic and methanotrophic communities in these fields were examined using terminal restriction fragment length polymorphism (T-RFLP) analysis based on the mcrA gene and pmoA gene encoding methyl coenzyme M reductase and particulate methane monooxygenase, respectively. The results showed that CH4 emissions were significantly affected by water management, straw retention, season, and their interactions. Over 80% of CH4 emissions occurred during the rice season. Field drainage during the fallow season reduced CH4 emissions by 47.0% and 53.8% with and without straw during the rice season, respectively. Water management altered the abundance and composition of methanogens and methanotrophs, whereas the effects of straw retention were less pronounced. The quantitative polymerase chain reaction (qPCR) assay revealed that field drainage in the fallow season decreased the mcrA gene abundance by 30.0% and 23.2% with and without straw in rice season, respectively, and increased the pmoA gene abundance by 108.9% and 213.7% with and without straw in rice season, respectively. CH4 flux was significantly positively associated with mcrA gene copy number and the ratio of mcrA to pmoA gene copy number, whereas it was significantly negatively correlated with the pmoA gene copy number. Results indicated that fallow drainage greatly decreased CH4 emission not only during the fallow season but also during the subsequent rice season by altering the community composition of methanogens and methanotrophs. These findings provide scientific insight into the role of water and straw management in controlling CH4 emissions through microbial community dynamics.

Aimed at the problem of gas flurries in carbon dioxide (CO2) geologic sequestration in the wellbore, this paper proposes a sealing method in which the downhole casing is processed with threaded grooves and then plugged with a low-melting-point alloy plug. Based on this method, a small-scale experimental setup was developed for alloy plug molding and gas sealing in this study. Molding and gas sealing experiments with Sn58Bi alloy plugs inside casings with different surface morphologies were carried out. The gas leakage pathway was determined. The microstructure of the interface between the alloy plug and casing was analyzed using an optical microscope. The influence of the inner surface roughness, threaded groove, length-to-diameter ratio, and ambient temperature on the gas sealing performance of the alloy plugs was analyzed. The experimental results show that, with an increase in ambient temperature, the gas sealing performance of the casing increases significantly; when the inner surface of the casing is processed through threaded grooves, the gas sealing performance is better than with smooth hole casing; the gas sealing performance of the alloy plug presents an obvious linear positive correlation with their length-to-diameter ratio. This research provides theoretical support for downhole CO2 plugging using Sn58Bi in the casing.

This study develops a framework for the impact mechanism based on the “homo urbanicus” theoretical perspective, linking indoor and outdoor fitness environmental elements to residents’ subjective perceptions and their activity intensity. An empirical investigation is conducted using structural equation modeling (SEM) with data from 286 valid questionnaires (N = 421). The results demonstrate that both indoor and outdoor fitness environmental elements—specifically spatial, facility, and environmental factors—significantly positively influence residents’ fitness activity intensity, with this relationship mediated by perceptions of safety, convenience, comfort, and aesthetics. Furthermore, the study uncovers variations in the types and degrees of influence across indoor and outdoor settings. Based on these findings, the author proposes several planning and design strategies: “In indoor environments, it is essential to ensure that fitness spaces feature bright lighting and thoughtful design to enhance aesthetic appeal; additionally, optimizing spatial layouts and integrating information services can foster greater social interaction. For outdoor environments, prioritizing locations near aesthetically pleasing architecture, adjacent to blue landscapes, and within open areas, as well as sites that are close to community amenities and abundant surrounding facilities, will enhance residents’ fitness activity intensity”.

How to improve the gel properties of protein has become a research focus in the field of seafood processing. In this paper, a fucoidan (FU)–vegetable oil emulsion was prepared, and the mechanism behind the effect of emulsion on protein conformation and the heat-induced gel properties was studied. The results revealed that the FU–vegetable oil complex caused the aggregation and cross-linking of myosin, as well as increased the surface hydrophobicity and total sulfhydryl content of myosin. In addition, the addition of the compound (0.3% FU and 1% vegetable oil) significantly improved the gel strength, hardness, chewiness, and water-holding capacity of the myosin gel (p < 0.05). In particular, when the addition of camellia oil was 1%, the gel strength, hardness, chewiness, and water-holding capacity had the highest values of 612.47 g.mm, 406.80 g, 252.75 g, and 53.56%, respectively. Simultaneously, the emulsion (0.3% FU-1% vegetable oil) enhanced the hydrogen bonds and hydrophobic interaction of the myosin gels. The image of the microstructure showed that the emulsion with 0.3% FU-1% vegetable oil improved the formation of the stable three-dimensional network structure. In summary, the FU–vegetable oil complex can promote unfolding of the protein structure and improve the gel properties of myosin, thus providing a theoretical basis for the development of functional surimi products.

Temporal and spatial factors regulate the interactions between apex predators, mesocarnivores, and herbivores. Prey adjust their activity patterns and spatial utilization based on predator activities; in turn, predators also adapt to the activities of their prey. To elucidate the factors influencing the daily activity rhythms of animals, 115 camera traps were established from September 2019 to June 2023 to assess the influences of interspecific relationships and seasons on the daily activity rhythms of animals in the southwest mountains of China. The species captured by the cameras included six Carnivora (such as Panthera pardus and Lynx lynx), six Artiodactyla (such as Moschus spp. and Rusa unicolor), one Primate (Macaca mulatta), and two Galliformes (Crossoptilon crossoptilon, Ithaginis cruentus). The results demonstrated that the 15 species exhibited different activity rhythms and peak activities to reduce intense resource competition. There were differences in the species’ activity rhythms in different seasons, with competition among different species being more intense in the cold season than in the warm season. In predation relationships, the overlap coefficient in the cold season exceeded that of the warm season, possibly due to the abundant resources in summer and food scarcity in winter. In competitive relationships, 15 pairs of species exhibited significantly higher overlap coefficients in the cold season compared to the warm season, possibly due to increased demands for energy during the cold period or seasonal changes in predatory behavior. By analyzing the daily and seasonal activity patterns of dominant species in the study area, temporal niche overlaps were established to compare the competition levels between species. These findings indicate that the activity rhythms of the animals in this area not only result from evolutionary adaptation but are also influenced by season, food resources, and interspecific relationships (predation and competition). Thus, efforts should be made to reduce human interference, protect food resources in the winter, and monitor animals’ interspecific relationships to protect animal diversity and maintain the stability of the ecosystem in this biodiversity hotspot in China.

With people’s concern for health and the development of medical technology, medical products for children are gradually appearing in pharmacies and online stores. However, the appearance of most children’s household medical products tends to meet the needs of adults, which leads to low acceptance of medical products. This study aimed to explore 10- to 16-year-old children’s visual and tactile perception of different materials by researching the relationship between the psychological quantities of visual and tactile perception and the physical quantities of the material surface. Based on the theory of kansei engineering, we measured the physical quantities of nine materials used in insulin syringe products and administered a perceptual questionnaire test for children. By correlating subjective perceptions with the physical attributes of the materials’ surfaces, we determined a strong correlation between the visual and tactile psychological properties and the properties of the materials’ surfaces. Children clearly perceive materials, and materials with lower roughness can elicit calmness, while materials with higher gloss elicit negative emotions. This paper establishes an evaluation model and provides a scientific selection method for surface materials in different children’s household medical products.

The logistics demands of industries represented by e-commerce have experienced explosive growth in recent years. Vehicle path-planning plays a crucial role in optimization systems for logistics and distribution. A path-planning scheme suitable for an actual scenario is the key to reducing costs and improving service efficiency in logistics industries. In complex application scenarios, however, it is difficult for conventional heuristic algorithms to ensure the quality of solutions for vehicle routing problems. This study proposes a joint approach based on the genetic algorithm and graph convolutional network for solving the capacitated vehicle routing problem with multiple distribution centers. First, we use the heuristic method to modularize the complex environment and encode each module based on the constraint conditions. Next, the graph convolutional network is adopted for feature embedding for the graph representation of the vehicle routing problem, and multiple decoders are used to increase the diversity of the solution space. Meanwhile, the REINFORCE algorithm with a baseline is employed to train the model, ensuring quick returns of high-quality solutions. Moreover, the fitness function is calculated based on the solution to each module, and the genetic algorithm is employed to seek the optimal solution on a global scale. Finally, the effectiveness of the proposed framework is validated through experiments at different scales and comparisons with other algorithms. The experimental results show that, compared to the single decoder GCN-based solving method, the method proposed in this paper improves the solving success rate to 100% across 15 generated instances. The average path length obtained is only 11% of the optimal solution produced by the GCN-based multi-decoder method.

To fulfill the demand for high-precision underwater acoustic positioning at full sea depth, an ultra-short baseline (USBL) positioning method with the square array based on the least squares estimating signal parameters via rotational invariance techniques (LS-ESPRIT) algorithm is presented in this paper. A combination of beam tracking and beamforming is employed to improve the accuracy of direction-of-arrival (DOA) estimation and, consequently, enhance overall positioning accuracy. In order to mitigate the issue of position jumping resulting from phase ambiguity in traditional four-element cross arrays, we have improved the stability of the positioning algorithm by utilizing a multi-element square array and employing the LS-ESPRIT algorithm for DOA estimation. Furthermore, the signal detection method integrating the correlation coefficient and ascending/descending chirp signals is employed to enhance the reliability of the location algorithm. Simulation analysis and experimental results demonstrate that the proposed algorithm effectively enhances positioning accuracy and improves the problem of jumping in positioning results.

Morchella spp. (true morels) are precious edible mushrooms consumed around the world, with a delicious taste, rich nutritional value, and unique healthcare effects. Various fungi and bacteria have been reported to colonize the ascocarps of Morchella, damaging their fruiting bodies and leading to serious economic losses in cultivation. The species identification of these colonizing organisms is crucial for understanding their colonization mechanisms on morels. Slime molds, which have characteristics of both “fungi” and “animals”, can occasionally colonize crops and edible fungi. However, there have been no reports of dictyostelid cellular slime molds (dictyostelids) colonizing plants and fungi to date. In this study, we discovered that dictyostelids colonized the surface of one wild ascoma of Morchella in the forest of Chongqing, China, with the tissues being black and rotten. Macro- and micro-morphological observations, along with molecular phylogenetic analyses, identified the specimens investigated in this study as Dictyostelium implicatum and Morchella sp. Mel-21. The results provide new knowledge of dictyostelid colonization on organisms and contribute to the diversity of species colonizing true morels. Moreover, this is also the first report of dictyostelids distributed in Chongqing, China. This study enhances our insights into the life history and potential ecological significance of dictyostelids and updates their distribution area in China. Further research will be conducted to uncover the mechanisms behind the colonization observed in this study.

Objectives: To address the poor efficacy and percutaneous penetration of grape seed oil, ionic liquids and nanotechnology were combined to prepare a grape seed oil emulsion. Methods: A novel Menthol-CoQ10 ionic liquid and ionic liquid based grapeseed oil emulsion were prepared and confirmed. Results: The average size of the grapeseed oil emulsion was 218 nm, and its zeta potential was −33.5 mV. The ionic liquid-based grape seed oil emulsion exhibited a transdermal penetration effect 4.63-fold higher than that of ordinary grape seed oil emulsion. Ionic liquid also displayed enhanced efficiency both in vitro and in vivo. It significantly inhibited the production of DPPH free radicals and tyrosinase, inhibited melanin and matrix metalloproteinase-1 (MMP-1) produced by cells, and promoted type I collagen expression in fibroblasts. After 28 days of continuous use, the grapeseed oil emulsion improved the water content of the stratum corneum and the rate of transepidermal water loss, enhanced the firmness and elasticity of the skin, and significantly improved the total number and length of under-eye lines, tail lines, nasolabial folds, and marionette lines on the face. Conclusions: Menthol-CoQ10 ionic liquid is a promising functional excipient for both transdermal delivery increase and efficient enhancement. Ionic liquid and nanotechnology for grape seed oil facial mask displayed significantly enhanced efficacy and permeability.

With the rapid development of industrialization, the problem of heavy metal wastewater treatment has become increasingly serious, posing a serious threat to the environment and human health. Biochar shows great potential for application in the field of wastewater treatment; however, biochars prepared from different biomass sources and experimental conditions have different physicochemical properties, resulting in differences in their adsorption capacity for uranium, which limits their wide application in wastewater treatment. Therefore, there is an urgent need to deeply explore and optimize the key parameter settings of biochar to significantly improve its adsorption capacity. This paper combines the nonlinear mapping capability of SCN and the ensemble learning advantage of the Adaboost algorithm based on existing experimental data on wastewater treatment. The accuracy of the model is evaluated by metrics such as coefficient of determination (R2) and error rate. It was found that the Adaboost–SCN model showed significant advantages in terms of prediction accuracy, precision, model stability and generalization ability compared to the SCN model alone. In order to further improve the performance of the model, this paper combined Adaboost–SCN with maximum information coefficient (MIC), random forest (RF) and energy valley optimizer (EVO) feature selection methods to construct three models, namely, MIC-Adaboost–SCN, RF-Adaboost–SCN and EVO-Adaboost–SCN. The results show that the prediction model with added feature selection is significantly better than the Adaboost–SCN model without feature selection in each evaluation index, and EVO has the most significant effect on feature selection. Finally, the correlation between biochar adsorption properties and production parameters was discussed through the inversion study of key parameters, and optimal parameter intervals were proposed to improve the adsorption properties. Providing strong support for the wide application of biochar in the field of wastewater treatment helps to solve the urgent environmental problem of heavy metal wastewater treatment.

Recent studies have shown that epigallocatechin-3-gallate (EGCG), as an effective antioxidant, could attenuate the oxidative damage, inflammation and necrosis in the liver in response to oxidative stress. The present study investigated whether oral administration of EGCG could effectively alleviate the hepatic histopathological changes and oxidative damage in yellow-feathered broilers induced by tert-butyl hydroperoxide (t-BHP). Broilers were exposed to 600 μmol t-BHP/kg body weight (BW) to induce oxidative stress by intraperitoneal injection every five days, followed by oral administration of different doses of EGCG (0, 20, 40 and 60 mg/kg BW) and 20 mg vitamin E (VE)/kg BW every day during 5–21 days of age. The results showed that t-BHP injection decreased (p < 0.05) body weight and the relative weight of the spleen; the enzyme activities of total antioxidant capacity (T-AOC), catalase (CAT) and total superoxide dismutase (SOD); and gene mRNA expressions of nuclear factor erythroid 2-related factor 2 (Nrf2), CAT, SOD1, SOD2 and acetyl-CoA carboxylase (ACACA); as well as increased (p < 0.05) necrosis formation, malondialdehyde (MDA) content, reactive oxygen species (ROS)accumulation, and peroxisome proliferator activates receptor-α (PPARα) mRNA expression in the liver of yellow-feathered female broilers at 21 days of age. Treatment with 60 mg EGCG/kg BW orally could enhance antioxidant enzyme activities and reverse the hepatic damage induced by t-BHP injection by reducing the accumulation of ROS and MDA in the liver and activating the Nrf2 and PPARα pathways related to the induction of antioxidant gene expression (p < 0.05). In conclusion, intraperitoneal injection of t-BHP impaired body growth and induced hepatic ROS accumulation, which destroyed the antioxidant system and led to oxidative damage in the liver of yellow-feathered broilers from 5 to 21 days of age. It is suggested that EGCG may play an antioxidant role through the Nrf2 and PPARα signaling pathways to effectively protect against t-BHP-induced hepatic oxidative damage in broilers, and the appropriate dose was 60 mg EGCG/kg BW by oral administration.

Foundation Models (FMs) are gaining increasing attention in the biomedical artificial intelligence (AI) ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capabilities make FMs a valuable tool for a variety of tasks, including biomedical reasoning, hypothesis generation, and interpreting complex imaging data. In this review paper, we address the unique challenges associated with establishing an ethical and trustworthy biomedical AI ecosystem, with a particular focus on the development of FMs and their downstream applications. We explore strategies that can be implemented throughout the biomedical AI pipeline to effectively tackle these challenges, ensuring that these FMs are translated responsibly into clinical and translational settings. Additionally, we emphasize the importance of key stewardship and co-design principles that not only ensure robust regulation but also guarantee that the interests of all stakeholders—especially those involved in or affected by these clinical and translational applications—are adequately represented. We aim to empower the biomedical AI community to harness these models responsibly and effectively. As we navigate this exciting frontier, our collective commitment to ethical stewardship, co-design, and responsible translation will be instrumental in ensuring that the evolution of FMs truly enhances patient care and medical decision-making, ultimately leading to a more equitable and trustworthy biomedical AI ecosystem.

Background: Osteoporosis, a prevalent bone metabolic disease, often requires long-term drug treatments that may lead to serious side effects. Trehalose, a natural disaccharide found in various organisms, has been shown to have a promoting effect on autophagy. However, whether trehalose can improve bone mass recovery in ovariectomized rats and its underlying mechanisms remains unclear. In this study, trehalose was administered to ovariectomized rats to evaluate its therapeutic potential for osteoporosis following ovariectomy. Methods: Micro-computed tomography (Micro-CT), hematoxylin and eosin (HE) and immunohistochemical staining techniques were utilized to evaluate the impact of trehalose on osteoporosis induced by ovariectomy (OVX) in mice, both in imaging and histological dimensions. Furthermore, the influence of trehalose on osteoblastogenesis and functional activity was quantified through Alizarin Red S (ARS) staining and immunoblotting assays. Results: Trehalose effectively mitigated bone loss, elevated autophagy and suppressed pyroptosis in ovariectomized rats. Furthermore, 3-methyladenine diminished the protective effects of trehalose, particularly in promoting autophagy and inhibiting pyroptosis. Conclusions: Trehalose demonstrates significant potential in treating osteoporosis by suppressing NLRP3 inflammasome-driven pyroptosis, primarily through autophagy promotion. This suggests that trehalose could be a promising, safer alternative treatment for osteoporosis.

Traditional seismic wave-based tunnel advanced geological forecasting techniques are primarily designed for drill and blast method construction tunnels. However, given the fast excavation speed and limited prediction space in tunnel boring machine (TBM) construction tunnels, traditional methods have significant technical limitations. This study analyzes the characteristics of different types of TBM construction tunnels and, considering the practical construction conditions, identifies an effective observation system and data acquisition method. To address the challenges in advanced forecasting for TBM construction tunnels, a method of ellipsoid positioning velocity analysis, which takes into account the constraints of three-component data directions, is proposed. Based on the characteristics of the advanced forecasting observation system, this method compares the maximum values on the spatial isochronous ellipsoidal surface to determine the average velocity of the geological layer rays, thereby enabling accurate inversion of the spatial distribution ahead. Utilizing numerical simulation, a model for the advanced detection of typical unfavorable geological formations is established by obtaining the wave field response characteristics of seismic waves in three-dimensional space, and the velocity structure of the model is retrieved through this velocity analysis method. In the engineering example, the fracture property, water content, and weathering degree of the surrounding rock are predicted accurately.

Helium ions implanted into metals can form ordered bubbles that are isomorphic to the host lattice. While long-range elastic interactions are generally believed to drive bubble superlattice formation, the interactions between individual helium solutes are not yet fully understood. Our first-principles calculations reveal that in molybdenum, Friedel oscillations induced by individual helium atoms generate potential barriers and wells that influence helium pairing and clustering at short He-He distances. These repulsive and attractive interactions at high concentrations provide thermodynamic driving forces that align randomly distributed helium atoms into Mo-He superlattices. Friedel oscillations may have broad impacts on solute–solute interactions in alloys.

Deep Generative Models (DGMs), as a state-of-the-art technology in the field of artificial intelligence, find extensive applications across various domains. However, their security concerns have increasingly gained prominence, particularly with regard to invisible backdoor attacks. Currently, most backdoor attack methods rely on visible backdoor triggers that are easily detectable and defendable against. Although some studies have explored invisible backdoor attacks, they often require parameter modifications and additions to the model generator, resulting in practical inconveniences. In this study, we aim to overcome these limitations by proposing a novel method for invisible backdoor attacks. We employ an encoder–decoder network to ‘poison’ the data during the preparation stage without modifying the model itself. Through meticulous design, the trigger remains visually undetectable, substantially enhancing attacker stealthiness and success rates. Consequently, this attack method poses a serious threat to the security of DGMs while presenting new challenges for security mechanisms. Therefore, we urge researchers to intensify their investigations into DGM security issues and collaboratively promote the healthy development of DGM security.

Cyclocarya paliurus tea, also known as “sweet tea”, an herbal tea with Cyclocarya paliurus leaves as raw material, is famous for its unique nutritional benefits and flavor. However, due to the unique “bittersweet” of Cyclocarya paliurus tea, it is still unable to fully satisfy consumers’ high-quality taste experience and satisfaction. Therefore, this study aimed to explore metabolites in Cyclocarya paliurus leaves during their growth period, particularly composition and variation of sweet and bitter taste compounds, by combining multi-platform metabolomics analysis with an electronic tongue system and molecular docking simulation technology. The results indicated that there were significant differences in the contents of total phenols, flavonoids, polysaccharides, and saponins in C. paliurus leaves in different growing months. A total of 575 secondary metabolites were identified as potential active metabolites related to sweet/bitter taste using nontargeted metabolomics based on UHPLC-MS/MS analysis. Moreover, molecular docking technology was utilized to study interactions between the candidate metabolites and the sweet receptors T1R2/T1R3 and the bitter receptors T2R4/T2R14. Six key compounds with high sweetness and low bitterness were successfully identified by using computational simulation analysis, including cis-anethole, gluconic acid, beta-D-Sedoheptulose, asparagine, proline, and citrulline, which may serve as candidates for taste modification in Cyclocarya paliurus leaves. These findings provide a new perspective for understanding the sweet and bitter taste characteristics that contribute to the distinctive sensory quality of Cyclocarya paliurus leaves.

N-heterocycles with quinoline structures hold significant importance within the chemical and pharmaceutical industries. However, achieving their efficient transformations remains a vital yet challenging endeavor. Herein, a series of W-doped Ga2O3-NC catalysts were synthesized using a Ga-MOF-derived strategy through a simple solvothermal method, with a remarkably high activity and selectivity towards the oxidative dehydrogenation of N-heterocycles. Furthermore, the MOF-derived W-doped Ga2O3-NC catalysts exhibit remarkable substrate tolerance and recyclability. The outstanding catalytic activity was attributed to the robust synergistic interaction between the W species and the Ga2O3-NC carrier, which facilitates the activation of hydrogen atoms in the C-H and C=N bonds on both the oxygen molecule and the substrate to produce H2O2. Additionally, the solvent effect of methanol can significantly enhance dehydrogenation due to its strong ability to donate and accept protons of hydrogen bonding. The present work provides a new approach to MOF-derived non-precious metal catalysts for achieving the efficient oxidation dehydrogenation of N-heterocycles.

Studies of the impact of biomass burning and the emissions of trace gases from biomass burning, especially using long-term observations, are scarce in China. We utilize solar absorption spectra obtained via ground-based high-resolution Fourier transform infrared (FTIR) spectroscopy to retrieve the atmospheric total columns and vertical profiles of carbon monoxide (CO), formaldehyde (H2CO), and hydrogen cyanide (HCN) in Hefei, China. Seasonal and interannual variability in the three gases from 2016 to 2022 are analyzed. Atmospheric CO shows significant seasonal variations, peaking during spring and winter, and declining during summer, with a seasonal amplitude of 8.07 × 1017 molecules cm−2 and a seasonal variability of 29.35%. H2CO and HCN have similar seasonal patterns to each other, with high concentrations in summer and low concentrations in winter. The seasonal amplitude of H2CO and HCN are 1.89 × 1016 molecules cm−2 and 2.32 × 1015 molecules cm−2, respectively, with a seasonal variability of 133.07% and 34.69%, respectively. The means of the annual variation rate for CO, H2CO, and HCN are (−2.67 ± 2.88)% yr−1, (2.52 ± 12.48)% yr−1 and (−3.48 ± 7.26)% yr−1, respectively. To assess the influence of biomass burning on the variations in column concentrations of the three gases, the correlation between CO, H2CO, and HCN was analyzed. The months during which the monthly correlation coefficient between CO and H2CO with HCN exceeds 0.8, and the fire radiative power (FRP) observed by satellites is larger than its monthly average are regarded as a biomass-burning occurrence in Anhui province. Additionally, the enhancement ratios of ΔH2CO/ΔCO and ΔHCN/ΔCO were calculated for the periods impacted by the biomass burning. Finally, backward trajectory cluster analysis and the potential source contribution function (PSCF) calculation identified the air mass transport pathways and the potential source areas at the Hefei site.

As a strategic mineral and energy resource, the enrichment and metallogenic mechanism of sandstone-hosted uranium deposits are highly dependent on hydrogeological conditions. However, the relationship between sandstone uranium mineralization and hydrogeological conditions has not received sufficient attention yet. The pumping test, hydrogeological parameters and hydrochemical characteristics were employed to analyze the change characteristics of hydrogeological conditions and evaluate the suitability of in situ leaching (ISL). The results showed that the study area in the Inner Mongolia Autonomous Region could be divided into two groundwater subsystems, namely Quanzha-Engeriyin and Luhai-Zhendai. The latter with relatively high water richness is confined and a main ore-bearing aquifer, which consists of four orebodies. The well discharge (Q) and hydraulic conductivity (K) of Orebody II ranged from 98.40 to 867.36 m3/d and 0.25 to 5.64 m/d, respectively, indicating the aquifer is suitable for the migration, enrichment and mineralization of uranium due to relatively high permeability and fast flow rate. The water storage of Orebodies III-IV gradually deteriorated from east to west in a stepped pattern. And the highest values of Q and K in Orebodies III-IV decreased from 1200 m3/d to 120 m3/d and 1.75 m/d to 0.035 m/d, respectively, suggesting these were conducive to a reduction in and accumulation of uranium under poor hydrodynamic conditions. Additionally, the study area would be defined as three grades, including favorable, relatively favorable and unfavorable areas of ISL according to a comprehensive evaluation. This study provided a scientific basis for evaluating the possibility of in situ leaching for sandstone-hosted uranium deposit.

The widespread adoption of arc additive manufacturing techniques across various industries has advanced the field of SS316L stainless steel manufacturing. It is crucial to acknowledge that different welding modes exert distinct influences on the forming and mechanical performance. This study analyzed the thermal input associated with four specific welding modes in LORCH MIG welding, clarifying the transition dynamics of molten droplets through waveform analysis and examining the resultant effects on microstructure and performance characteristics. The Pulse, Speed-Pulse-XT, and Twin-Pulse modes were found to induce spatter during the manufacturing process, consequently reducing molding efficiency in comparison to the SA-XT mode. Notably, the Twin-Pulse mode, characterized by double-pulse agitation, generated fish scale patterns along the lateral surfaces of the fabricated parts, promoting anisotropic grain growth. This microstructural refinement, compared to single-pulse samples with equivalent thermal input, resulted in enhanced mechanical properties. Nevertheless, the horizontal tensile strength of the three pulse modes was lower than the industrial standard for SA-XT mode and forging. In contrast, the SA-XT mode with an average hardness of 168.1 ± 6.9 HV and a tensile strength of 443.58 ± 5.7 MPa. Therefore, while three pulse modes offer certain microstructural advantages, the SA-XT mode demonstrates superior overall performance.

The discovery of a lead compound against Candida albicans is urgently needed because of the lack of clinically available antifungal drugs and the increase in drug resistance. Herein, a β-carboline alkaloid methylaervine (MET) exhibited potential activity against C. albicans (MIC = 16–128 μg/mL), no hemolytic toxicity, and a low tendency to induce drug resistance. An antifungal mechanism study indicated that MET effectively inhibited the biofilm formation and disrupted the mature biofilm. Moreover, filamentation formation and spore germination were also weakened. The electron microscopy analysis revealed that MET could damage the cell structure, including the cell wall, membrane, and cytoplasm. In particular, the permeability and integrity of the cell membrane were destroyed. When it entered the fungi cell, it interfered with the redox homeostasis and DNA function. Overall, MET can inhibit the growth of C. albicans from multiple channels, such as biofilm, filamentation, cell structure, and intracellular targets, which are difficult to mutate at the same time to generate drug resistance. This work provides a promising lead compound for the creation of new antifungal agents against C. albicans.

Glaucoma stands as a primary cause of irreversible blindness globally, characterized by the progressive dysfunction and loss of retinal ganglion cells (RGCs). While current treatments primarily focus on controlling intraocular pressure (IOP), many patients continue to experience vision loss. Therefore, the research focus has shifted to therapeutic targets aimed at preventing or delaying RGC death and optic nerve degeneration to slow or halt disease progression. Traditional ocular drug administration, such as eye drops or oral medications, face significant challenges due to the eye’s unique structural and physiological barriers, which limit effective drug delivery. Invasive methods like intravitreal injections can cause side effects such as bleeding, inflammation, and infection, making non-invasive delivery methods with high bioavailability very desirable. Nanotechnology presents a promising approach to addressing these limitations in glaucoma treatment. This review summarizes current approaches involving neuroprotective drugs combined with nanocarriers, and their impact for future use.

Environmental stresses, including drought stress, seriously threaten food security. Previous studies reported that wheat F-box protein, TaFBA1, responds to abiotic stresses in tobacco. Here, we generated transgenic wheat with enhanced (overexpression, OE) or suppressed (RNA interference, RNAi) expression of TaFBA1. The TaFBA1-OE seedlings showed enhanced drought tolerance, as measured by survival rate and fresh weight under severe drought stress, whereas the RNAi plants showed the opposite phenotype. Furthermore, the OE plants had stronger antioxidant capacity compared to WT and RNAi plants and maintained stomatal opening, which resulted in higher water loss under drought stress. However, stronger water absorption capacity in OE roots contributed to higher relative water contents in leaves under drought stress. Moreover, the postponed stomatal closure in OE lines helped to maintain photosynthesis machinery to produce more photoassimilate and ultimately larger seed size. Transcriptomic analyses conducted on WT and OE plants showed that genes involved in antioxidant, fatty acid and lipid metabolism and cellulose synthesis were significantly induced by drought stress in the leaves of OE lines. Together, our studies determined that the F-box protein TaFBA1 modulated drought tolerance and affected yield in wheat and the TaFBA1 gene could provide a desirable target for further breeding of wheat.

The geological environment damage caused by coal mining subsidence has become an important factor affecting the sustainable development of mining areas. Reconstruction of the Coal Mining Subsidence Field (CMSF) is the key to preventing geological disasters, and the needs of CMSF reconstruction cannot be met by solely relying on a single remote sensing technology. The combination of Unmanned Aerial Vehicle (UAV) and Synthetic Aperture Radar (SAR) has complementary advantages; however, the data fusion strategy by refining the SAR deformation field through UAV still needs to be updated constantly. This paper proposed a Prior Weighting (PW) method based on Satellite Aerial (SA) heterogeneous remote sensing. The method can be used to fuse SAR and UAV Light Detection and Ranging (LiDAR) data for ground subsidence parameter inversion. Firstly, the subsidence boundary of Differential Interferometric SAR (DInSAR) combined with the large gradient subsidence of Pixel Offset Tracking (POT) was developed to initialize the SAR preliminary CMSF. Secondly, the SAR preliminary CMSF was refined by UAV LiDAR data; the weights of SAR and UAV LiDAR data are 0.4 and 0.6 iteratively. After the data fusion, the subsidence field was reconstructed. The results showed that the overall CMSF accuracy improved from ±144 mm to ±51 mm. The relative errors of the surface subsidence factor and main influence angle tangent calculated by the physical model and in situ measured data are 1.3% and 1.7%. It shows that the proposed SAR/UAV fusion method has significant advantages in the reconstruction of CMSF, and the PW method contributes to the prevention and control of mining subsidence.

Snow cover distribution is of great significance for climate change and water resource management. Current deep learning-based methods for extracting snow cover from remote sensing images face challenges such as insufficient local detail awareness and inadequate utilization of global semantic information. In this study, a snow cover extraction algorithm integrating cross-scale edge perception and an attention mechanism on the U-net model architecture is proposed. The cross-scale edge perception module replaces the original jump connection of U-net, enhances the low-level image features by introducing edge detection on the shallow feature scale, and enhances the detail perception via branch separation and fusion features on the deep feature scale. Meanwhile, parallel channel and spatial attention mechanisms are introduced in the model encoding stage to adaptively enhance the model’s attention to key features and improve the efficiency of utilizing global semantic information. The method was evaluated on the publicly available CSWV_S6 optical remote sensing dataset, and the accuracy of 98.14% indicates that the method has significant advantages over existing methods. Snow extraction from Landsat 8 OLI images of the upper reaches of the Irtysh River was achieved with satisfactory accuracy rates of 95.57% (using two, three, and four bands) and 96.65% (using two, three, four, and six bands), indicating its strong potential for automated snow cover extraction over larger areas.