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Bacterial communities play a crucial role in maintaining the stability of river ecosystems and driving biogeochemical cycling, exhibiting high sensitivity to environmental change. However, understanding the spatial scale effects and assembly mechanisms of riverine bacterial communities under distinct anthropogenic disturbances remains a challenge. Here, we investigated bacterial communities across three distinct watersheds [i.e., intensive urban (UW), intensive agricultural (AW), and natural (NW)] in both dry and wet seasons. We explored biogeographic patterns of bacterial communities and the influence of landscape patterns at multi-spatial scales and water chemistry on bacterial communities. Results showed that α diversity was significantly lower in UW and AW compared to NW, particularly in the dry season. A gradient of β diversity with NW > UW > AW was observed across both seasons (p

Silicon-based anodes have emerged as a promising advancement in lithium-ion battery technology, offering significantly higher lithium storage capacities than traditional graphite. However, the volumetric expansion of silicon-anodes can swell by up to 300 % during lithiation-presents serious challenges to their structural integrity and electrochemical stability. This study investigates the internal structural dynamics of silicon anodes during lithiation and delithiation cycles. A novel cell design for a 18,650 cylindrical cell featuring micro-sized internal speckles within the silicon anode is presented. This design improves the simulation of electrochemical conditions and allows for precise displacement tracking, mitigating impacts on capacity and cycle performance while enhancing Digital Volume Correlation (DVC) analysis. The research prioritizes reducing scan time and radiation exposure in micro-CT assessments of Li-ion cells, and improves the accuracy of internal strain mapping via DVC. Displacement fields over three charging and discharging cycles are documented. Notably, uneven volumetric changes are observed, with local displacements reaching up to 35 µm in areas smaller than 2.5 mm in radius, which contracted during charging and expanded during discharging. This protocol offers insights into the relationship between electrode mechanics and cell performance, promoting non-destructive evaluations of internal structures in commercial cells.

Abstract Background Rapid identification and classification of bats are critical for practical applications. However, species identification of bats is a typically detrimental and time-consuming manual task that depends on taxonomists and well-trained experts. Deep Convolutional Neural Networks (DCNNs) provide a practical approach for the extraction of the visual features and classification of objects, with potential application for bat classification. Results In this study, we investigated the capability of deep learning models to classify 7 horseshoe bat taxa (CHIROPTERA: Rhinolophus) from Southern China. We constructed an image dataset of 879 front, oblique, and lateral targeted facial images of live individuals collected during surveys between 2012 and 2021. All images were taken using a standard photograph protocol and setting aimed at enhancing the effectiveness of the DCNNs classification. The results demonstrated that our customized VGG16-CBAM model achieved up to 92.15% classification accuracy with better performance than other mainstream models. Furthermore, the Grad-CAM visualization reveals that the model pays more attention to the taxonomic key regions in the decision-making process, and these regions are often preferred by bat taxonomists for the classification of horseshoe bats, corroborating the validity of our methods. Conclusion Our finding will inspire further research on image-based automatic classification of chiropteran species for early detection and potential application in taxonomy.

This study aimed to address the challenges encountered in traditional bulk wave delamination detection methods characterized by low detection efficiency. Additionally, the limitations of guided wave delamination detection methods were addressed, particularly those utilizing reflected waves, which are susceptible to edge reflections, thus complicating effective defect extraction. Leveraging the full waveform inversion algorithm, an innovative approach was established for detecting delamination defects in multi-layered structures using ultrasonic guided wave arrays. First, finite element modeling was employed to simulate guided wave data acquisition by a circular array within an aluminum–epoxy bilayer structure with embedded delamination defects. Subsequently, the full waveform inversion algorithm was applied to reconstruct both regular and irregular delamination defects. Analysis results indicated the efficacy of the proposed approach in accurately identifying delamination defects of varying shapes. Furthermore, an experimental platform for guided wave delamination defect detection was established, and experiments were conducted on a steel–cement bilayer structure containing an irregular delamination defect. The experimental results validated the exceptional imaging precision of our proposed technique for identifying delamination defects in multi-layered boards. In summary, the proposed method can accurately determine both the positions and sizes of defects with higher detection efficiency than traditional pulse-echo delamination detection methods.

Combining with the dispersion characteristics of ultrasonic guided waves, full waveform inversion method shows great application potential in the quantificational detections of defects in plate- and pipe- like structures. Owing to the inversion efficiency problem, the forward modeling is generally based on the acoustic equation approximation, and a reference signal unaffected by the defects needs to be artificially selected to correct the approximation forward simulation results. This study presents an auto-calibration (without artificial selection of the reference signal) and high-precision imaging method based on the combination of the full waveform inversion and ray tomography algorithm. The ray tomography results are not only used to automatically select the reference signal based on an auto-calibration process, but also used as the macro initial model for the full waveform inversion method, which decreases the possibility of losing in local minimum values during the inversion process and enhances the robustness of the inversion method. Therefore, compared with the classical guided wave tomography method based on full waveform inversion, relatively high-frequency transducers can be used to acquire high-frequency signals, and thus, the imaging accuracy could be effectively improved. Simulation and experiment results have verified that the global relative error of the auto-calibration method is smaller than the classical method. The good imaging results of irregular complex defects confirmed the effectiveness and applicability of the new method.

An accurate assessment of sediment transport can assist land and resource managers in any region. The primary objective of this study was to develop a distributed hydrological model for calculating rainfall-runoff coupled with sediment transport to provide a practical method for estimating sediment transport in western Heilongjiang Province, China. The Alun River Basin, which has typical meteorological and hydrological characteristics of western Heilongjiang Province, was chosen as the study area. A sediment transport calculation module was developed based on physically based formulas for the suspended load and bedload, which was coupled with a numerical model of the physical distributed rainfall-runoff process. The model’s ability was validated by comparing the sediment sampling survey results of the particle size group distribution (PSGD) in the flow and the corresponding value of the model calculation results for a control case. The root mean square error ( RMSE ) and the mean absolute error ( MAE ) were mostly 15%. The results provide a basis for the assessment of sediment transport and the development of a numerical platform for modeling hydrological processes coupled with land surface processes in western Heilongjiang Province, China.

Corrosion detection for industrial settings is crucial for safe and efficient operations. Due to its high imaging resolution, the guided–wave full–waveform inversion tomography technique has significant potential for corrosion detection of plate metals. Limited by the long wavelengths of A0 and S0 mode waves, this method exhibits inadequate detection resolution for the earlier shallow and small corrosion defects. Based on the relatively short wavelength characteristics of the SH1 mode wave, we propose a high–precision corrosion detection method via SH1 guided wave using the full waveform inversion algorithms. By conducting finite element simulations of ultrasonic–guided waves on aluminum plates with varying corrosion defects, a comparison was made to assess the detection precision across A0, S0, and SH1 modes. The comparison results showed that, whether for regular or irregular defects, the SH1 mode wave always exhibited higher imaging accuracy than the A0 and S0 mode waves for shallow and small–sized defects. The corresponding experiments were conducted on an aluminum plate with simple or complex defects. The results of the experiments reconfirmed that the full waveform inversion method using SH1 guided wave can effectively reconstruct the shape and size of small and shallow corrosion defects within aluminum plates.

Ligusticum chuanxiong Hort. as an important Chinese medicinal herb clinically used as anti-inflammatory, antioxidant, and hepatoprotective agents, is widely planted in China. However, related studies on L. chuanxiong’s distribution and significant environmental factors that affect its growth are insufficient. Based on climatic, topographic and soil factors, this study predicted current and future distributions of L. chuanxiong and analyzed the distribution transformation under different scenarios. Moreover, the most important environmental factors for modeling were explored using maximum entropy models, chemical analysis and molecular analysis. Results suggested that the predicted distribution of L. chuanxiong was wider than previously reported. Among these environmental variables, climate factors, especially the minimum temperature of the coldest month (Bio6, 46.7%) and solar radiation (SRAD, 43.4%) contributed more than others to L. chuanxiong’s distribution with optimum values of 0–1.5 °C and 5000–11,000 kJ/m2 per day. Total and highly suitable areas respectively increased by 26,788–943,820 km2 and 34,757–340,417 km2 in the future (2061–2080, 2081–2100). The distribution centers of suitable zones were predicted to migrate north in the future, and the migration distance was 135.74–479.77 km from current center. Results of chemical content determination suggested that L. chuanxiong should be cultivated in high-suitable places to improve medicinal quality by evaluating contents of ferulic acids and Z-ligustilide. Correlation analysis suggested that both chemical contents and gene expression levels decreased with decreasing habitat suitability, suggesting a strong link between environments, chemical constituents, and gene expression. These findings improve the comprehension of the effects of environments on the distribution patterns of L. chuanxiong, as well the relation between environmental suitability and medicinal quality. These findings provide a useful foundation for the planting, cultivation and conservation of L. chuanxiong.

Gallic acid (GA) is a natural polyphenolic compound with many health benefits. To assess the potential risk of long-term consumption of GA to gut health, healthy dogs were fed a basal diet supplemented with GA (0%, 0.02%, 0.04%, and 0.08%) for 45 d, and fecal microbiota and metabolomics were evaluated. This study demonstrated that GA supplementation regulated serum lipid metabolism by reducing serum triglyceride, fat digestibility, and Bacteroidetes/Firmicutes ratio. In addition, the relative abundance of Parasutterella was significantly lower, and the SCFAs-producing bacteria were increased along with fecal acetate and total SCFAs contents accumulation in the 0.08% GA group. Metabolomics data further elucidated that 0.08% GA significantly affected carbohydrate metabolism by downregulating succinic acid in fece, thereby alleviating inflammation and oxidative stress. Overall, this study confirmed the beneficial effects of long-term consumption of GA on lipid metabolism and gut health, and the optimal level of GA supplementation was 0.08%.

The aqueous metal species with similar chemical properties are usually extracted together, limiting deep separation for high-purity metal. However, rare attention has been paid to metal speciation characterization and transformation during separation. Herein, the hydrolysis evolution of polymeric metal species was investigated systematically by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The transformation evolutions were visualized with respect to characteristic vanadium species (V1, V2, V3, V4 and V10), chromium species (Cr1 and Cr2), tungsten (W1, W2, W4, W6 and W10) and molybdenum (Mo1, Mo2 and Mo4) species. The key characteristics (such as specfic pHs and concentrations) for speciation variation were revealed. The polymerization behavior of several transition metals can be semiquantitative characterized by this strategy. The sufficient speciation transformation provides a solid base for metal speciation chemistry, and guides further development of high-purity metal recovery.

Stress exposure is a potential threat to humans who live or work in extreme environments, often leading to oxidative stress, inflammatory response, intestinal dysbiosis, and metabolic disorders. Gallnut tannic acid (TA), a naturally occurring polyphenolic compound, has become a compelling source due to its favorable anti-diarrheal, anti-oxidative, anti-inflammatory, and anti-microbial activities. Thus, this study aimed to evaluate the anti-stress effects of gallnut TA on the stress-induced inflammatory response, dysbiotic gut microbiota, and alterations of serum metabolic profile using beagle models. A total of 13 beagle dogs were randomly divided into the stress (ST) and ST + TA groups. Dietary supplementation with TA at 2.5 g/kg was individually fed to each dog in the ST + TA group for 14 consecutive days. On day 7, all dogs were transported for 3 h from a stressful environment (days 1–7) to a livable site (days 8–14). In our results, TA relieved environmental stress-induced diarrheal symptoms in dogs and were shown to protect from myocardial injury and help improve immunity by serum biochemistry and hematology analysis. Also, TA inhibited the secretion of serum hormones [cortisol (COR), glucocorticoid (GC), and adrenocorticotropic hormone (ACTH)] and the expression of heat shock protein (HSP) 70 to protect dogs from stress-induced injury, thereby relieving oxidative stress and inflammatory response. Fecal 16S rRNA gene sequencing revealed that TA stimulated the growth of beneficial bacteria (Allobaculum, Dubosiella, Coriobacteriaceae_UCG-002, and Faecalibaculum) and suppressed the growth of pathogenic bacteria (Escherichia-Shigella and Streptococcus), thereby increasing fecal butyrate levels. Serum metabolomics further showed that phytosphingosine, indoleacetic acid, arachidonic acid, and biotin, related to the metabolism of sphingolipid, tryptophan, arachidonic acid, and biotin, respectively, could serve as potential biomarkers of stress exposure. Furthermore, Spearman’s correlation analysis showed strong relationships between the four potential serum biomarkers and differential bacteria. Overall, gallnut TA may be a potential prebiotic for the prevention and treatment of stress-induced metabolic disorders by targeting intestinal microbiota.

Transportation is common in cats and often causes stress and intestinal disorders. Antimicrobial peptides (AMPs) exhibit a broad spectrum of antibacterial activity, and they may have the capacity for antioxidant and immune regulation. The objective of this study was to investigate the effects of dietary supplementation with AMPs on stress response, gut microbiota and metabolites of cats that have undergone transport stress. A total of 14 Ragdoll cats were randomly allocated into 2 treatments: basal diet (CON) and a basal diet supplemented with 0.3% AMPs. After a 6-week feeding period, all cats were transported for 3 h and, then, fed for another week. The results show that the diarrhea rate of cats was markedly reduced by supplementation with AMPs throughout the trial period (p < 0.05). In addition, AMPs significantly reduced serum cortisol and serum amyloid A (p < 0.05) and increased apolipoprotein 1 after transportation (p < 0.05). Moreover, AMPs reduced the level of inflammatory factors in the serum caused by transportation stress, including tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β) (p < 0.05). The AMPs enhanced the activities of glutathione peroxidase (p < 0.01) and superoxide dismutase (p < 0.05). Furthermore, cats fed AMPs had higher levels of branched chain fatty acids (BCFAs) and a relative abundance of Blautia and a lower relative abundance of Negativibacillus after transportation (p < 0.05). The serum metabolome analysis further revealed that AMPs markedly regulated lipid metabolism by upregulating cholic acid expression. In conclusion, AMP supplementation alleviated oxidative stress and inflammatory response in transportation by regulating the gut microbiota and metabolites, thereby relieving stress-induced diarrhea and supporting gut and host health in cats.