Jing Wang

Monitoring water surface algal blooms from surveillance perspectives faces challenges such as small objects, low texture contrasts, dynamic background interferences, and limited labeled datasets. In this study, we propose GECA-YOLOv26, a lightweight model that integrates Ghost Convolution (GhostConv) and Efficient Channel Attention (ECA) modules. First, the GhostConv lightweight module is introduced in the first layer of the YOLOv26 backbone, reducing parameters from 4608 to 2704 and achieving a 41% reduction in computational cost. Second, eight ECA modules are embedded at key locations after backbone downsampling and neck feature fusion to enhance feature representation and mitigate degradation caused by model lightweighting. Finally, the MuSGD optimizer is used for training, with adaptive modifications to resolve tensor shape conflicts with the ECA modules. Experimental results indicate that the model achieves a mAP50 of 82.16%. Compared with the YOLOv26 baseline, our model improves mAP50 by 6.42%, while mAP@0.5:0.95 decreases by 0.79% and inference speed reduces from 143 FPS to 123 FPS. The model also reduces parameters and size, achieving 5.19 MB and 1864 fewer parameters. Compared with YOLOv8, YOLOv10, and YOLOv11, the proposed model improves mAP50 by 2.12%, 5.99%, and 2.79%, respectively. To evaluate the stability of the results under small-sample conditions, we conducted 3-fold and 5-fold cross-validation experiments, which demonstrated that the model performs robustly across different folds and random seeds. Ablation studies further confirm the effectiveness of each module. Heatmap analysis demonstrates that the proposed model effectively highlights small object regions, remains robust under limited-sample conditions, and reduces model complexity. This study provides a novel solution for algal bloom detection in surveillance scenarios.

The pore structure of cocopeat-based substrates critically influences their hydraulic properties, directly affecting water use efficiency in soilless cultivation systems. Previous macroscopic modeling approaches infer pore structures indirectly from water retention curves and rely on empirical parameterization of pore geometry and connectivity, overlooking microscale features that directly control fluid pathways and permeability. To address this gap, this study employed micro-CT imaging to reconstruct the three-dimensional pore structures of coarse cocopeat and a fine cocopeat–perlite mixture. Nine regions of interest (ROIs), representing three typical pore types in each substrate, were selected for quantitative pore structure analysis and pore-scale saturated flow simulations. Results show that over 90% of pore diameters in both substrates fall within the 0–400 μm range, and variations in cocopeat particle size and perlite addition significantly affect average pore diameter, porosity, fractal dimension, and tortuosity, thereby influencing permeability and local flow distribution. This study provides new insights into the microscale mechanisms governing water movement in cocopeat-based substrates and reveals key structural factors regulating hydraulic behavior in soilless cultivation systems.

P-wave first-motion polarity is a critical parameter for determining earthquake focal mechanisms. Extracting relative P-wave arrival times and polarity information using waveform cross-correlation techniques can enhance the accuracy of earthquake location and focal mechanism inversion. However, seismic noise severely hampers the reliable detection of P-wave onsets and their first-motion polarities. To address this issue, we propose a noise-resistant polarity detection method based on the normal time–frequency transform (NTFT), termed the time–frequency similarity coefficient (TFSC). The TFSC method computes relative delays and similarity coefficients by calculating the real part of the NTFT coefficients between two seismic signals. We validated the proposed approach using both synthetic and real earthquake data. Without any filtering or preprocessing, the TFSC method demonstrated significantly greater robustness and reliability compared to the conventional time-domain normalized cross-correlation (NCC) method. These results indicate that the TFSC method has strong potential for practical application and provides a novel perspective for accurate detection of P-wave first-motion polarity in noisy seismic environments.

The global water scarcity crisis is escalating, necessitating the urgent development of innovative water treatment technologies to address freshwater shortages. Capacitive Deionization (CDI) stands out due to its efficient and environmentally friendly advantages. In the application of CDI, researching electrode materials to achieve higher adsorption capacities is crucial. Tableting electrodes have advantages as they can increase mass loading, but they are seldom discussed in the field of capacitive water purification. Therefore, this study applies tableting electrodes to CDI, breaking through the low mass loading bottleneck (50 mg cm^− 2), and explores their desalination effect and kinetics. We found that at a voltage window of 0–1.2 V and a flow rate of 10 ml min^− 1, tableting electrodes had the best desalination effect. The desalination ability in different salt solutions is greatly influenced by ion diffusion performance, with the best performance observed in LiCl solution (8.9 mg g^− 1). Additionally, the manufacturing process of tableting electrodes has the advantages of simple operation, environmental friendliness, and low cost. This study explores for the first time the kinetics and desalination effect of tableting electrodes in CDI devices, providing informational references for the application of tableting electrodes in capacitive desalination.

Panax notoginseng (Burkill) F. H. Chen, as a traditional Chinese medicinal herb with significant therapeutic effects, is highly sensitive to environmental factors during its growth process, particularly light and water conditions. Under traditional field conditions, natural limitations make it difficult to achieve optimal yield and quality. This study aimed in the past to determine the optimal light–water interaction model for the year-round cultivation of P. notoginseng in a controlled plant factory environment. The experiment used one-year-old, uniformly grown P. notoginsen seedlings. At the beginning of the experiment, the light source, without any shading treatment, provided a photosynthetically active radiation (PAR) intensity of 200 μmol·m⁻²·s⁻¹, measured at a distance of 30 cm from the plant canopy. A total of 18 treatment combinations were established, specifically two different light quality treatments (A Treatment with a red-to-blue light ratio of 4:1 and B Treatment with a red-to-blue light ratio of 5:1) were each combined with three irrigation levels (field water capacities of 40%, 50%, and 60%) and three shading levels (one layer of 60% shading net, two layers of 60% shading net, and three layers of 60% shading net). Each light quality treatment was combined with all three irrigation levels and all three shading levels, resulting in 18 distinct treatment combinations. The effects of different light–water interactions on P. notoginseng growth were evaluated by measuring key agronomic traits, chlorophyll fluorescence parameters, and ginsenoside content. The results indicate that light–water interactions significantly affect the agronomic traits, chlorophyll fluorescence parameters, and ginsenoside content of P. notoginseng (light treatment had a more significant impact on the growth of P. notoginsen than water treatment). The best performance in terms of plant height (15.3 cm), stem diameter (3.45 mm), leaf length (8.6 cm), fresh weight (3.382 g), and total ginsenoside content (3.8%) was observed when the red-to-blue light ratio was 4:1 (A Treatment), the field water capacity was 50%, and the shading level was three layers. Based on this, the Pearson correlation analysis was used to identify eight highly correlated indicators, and the entropy-weighted TOPSIS model was applied to comprehensively evaluate the cultivation schemes. The evaluation results show that the optimal cultivation scheme for P. notoginseng is under the conditions of a red-to-blue light ratio of 4:1 (A Treatment), field water capacity of 50%, and three-layer shading.

Per- and polyfluoroalkyl substances (PFAS) have been detected in lake ecosystems globally, even in remote areas at high altitudes. Compared to plain lakes with short water change cycles and significant human influence, plateau lakes are primarily tectonic closed or semi-closed lakes with steep terrain. Their long water change cycles lead to an obvious cumulative effect on pollutants. In this study, a targeted screening method for 74 PFAS in aquatic environment was established. The contamination characteristics of PFAS in surface water samples (0.5 m below the water surface) and bottom samples (0.5 m above the lake bottom) of plateau Lake Yangzonghai were studied and compared to a reference site in Dianchi Lake which has been severely affected by anthropogenic sources. Results showed that 32 PFAS were detected in Lake Yangzonghai with the total concentration (∑₃₂PFAS) ranging from 14.95 to 26.42 ng L⁻¹. Among the 27 PFAS with available standards for accurate quantification, 22 PFAS were detected, with the concentration of ∑₂₂PFAS ranging from 13.27 to 20.17 ng L⁻¹. Significant differences (p < 0.05) in PFAS concentrations were observed between surface water (22.12 ng L⁻¹) and bottom water (18.18 ng L⁻¹), demonstrating a stratification phenomenon. The spatial differences in PFAS concentrations in surface water were minimal, indicating that the surface water was uniformly mixed with limited local disturbance from human pollution. The main PFAS monomers were perfluorooctanoic acid (PFOA), 8-3 fluorotelomer carboxylic acid (8-3 FTCA), perfluoroheptanoic acid (PFHpA) and 2H-perfluoro-2-decenoic acid (8-2 FTUCA), while PFBA was not detected. This distribution remarkably differed from many other plain lakes and the reference lake. Source apportionment analysis showed that PFAS primarily originated from atmospheric transport and precursor degradation. The results provide a background pollution level of PFAS in the plateau lake near the city and will benefit for formulating control policies.