Search Results (294)

The aim of this study was to investigate the method of estimating actual crop evapotranspiration (ET_cact) in a greenhouse using other measured meteorological parameters when solar radiation (R_s) data are missing. The study estimated ET_cact of greenhouse green peppers by combining solar radiation estimation models with the Penman–Monteith (PM) model and evaluated model performance. The results showed that the prediction accuracy of the temperature-based solar radiation model was higher than the model based on sunshine hours in the Hexi Corridor region. The effect of the insulation cover on the incident solar radiation in the greenhouse is modeled by introducing a ramp function. In terms of crop coefficients (K_cb), the initial K_cb value of green peppers in the 2023 growing season was generally consistent with the updated FAO-56 standard values, whereas the initial K_cb values (0.17) were higher than the standard values in the 2023–2024 growing season. During the two growing seasons, the mid-stage K_cb values were 1.01 in the 2023 growing season and 0.82 in the 2023–2024 growing season. The study also found that PM–RT4, PM–RT5, and PM–RT6 models were all able to accurately predict the ET_cact of greenhouse green peppers during the 2023 growing season. The PM–RT4 model performed well in both growing seasons, with R² = 0.8101 in the 2023 growing season and R² = 0.7561 in the 2023–2024 growing season. Our research supports the PM–RT4 model as appropriate to estimate green pepper actual evapotranspiration in Gobi solar greenhouses (GSGs) and may be further used to improve irrigation scheduling for green peppers grown in GSGs. Full article

Gobi solar greenhouses (GSGs) enhance energy, food, and financial security in Gobi Desert regions through passive solar utilization. Thermal mass walls are critical for plant thermal comfort in GSGs but can lead to resource waste if poorly designed. This study pioneers the integration of payback period constrains into thermal mass wall optimization, establishing a new performance–cost trade-off approach for GSG wall design, balancing thermal performance and economic feasibility. We quantified energy-conserving benefits against wall-construction costs to derive the optimal inner-layer thicknesses under <25% GSG lifespan payback criteria. Three GSG thermal mass walls in China’s Hexi Corridor were optimized. For the concrete-layered, stone-layered, and pebble-soil walls, the optimum inner-layer thicknesses were 0.47, 0.65, and 1.24 m, respectively, with extra costs of 620.75, 767.60, and 194.56 RMB yuan; annual energy-conserving benefits of 82.77, 102.35, and 51.88 RMB yuan·yr⁻¹; and payback periods of 7.5, 7.5, and 3.75 years. A dynamic thermal load analysis confirmed that GSGs with optimized walls required no heating during a sunny winter solstice night. Cooling loads of 33.15–35.27 kW further indicated the potential to maintain thermal comfort under colder weather conditions. This approach improves plant thermal comfort cost-effectively, advancing sustainable Gobi agriculture. Full article

Melanin is a complex natural pigment that imparts a variety of colors to the fruiting bodies of edible fungi, influencing both their nutritional quality and commercial value. Stropharia rugosoannulata is an emerging type of edible fungus that has been widely cultivated in recent years. It can be categorized into red and yellow varieties based on cap color, while its pigment characteristics remain unclear. In this study, the melanins from the two varieties were obtained using an alkaline extraction and acid precipitation method, followed by comprehensive characterization of their chemical properties and ultrastructural features. Both melanins displayed distinct absorption maxima at approximately 211 nm. The melanin extracted from the red variety consisted of 55.63% carbon (C), 7.40% hydrogen (H), 30.23% oxygen (O), 5.99% nitrogen (N), and 0.64% sulfur (S), whereas the yellow variety comprised 52.22% C, 6.74% H, 29.70% O, 5.91% N, and 0.99% S. Both types of melanin included eumelanin and phaeomelanin forms, with eumelanin being the predominant type. Variations in the quantities and relative proportions of eumelanin and phaeomelanin contributed to the observed color differences in the mushroom caps. Ultrastructural micrographs revealed the melanins were primarily localized in the cell wall, consistent with findings in other fungal species. These findings contribute valuable insights into fundamental knowledge and potential applications of mushroom pigments. Full article

Cotton leaf diseases can lead to substantial yield losses and economic burdens. Traditional detection methods are challenged by low accuracy and high labor costs. This research presents the ACURS-YOLO network, an advanced cotton leaf disease detection architecture developed on the foundation of YOLOv11. By integrating a medical image segmentation model, it effectively tackles challenges including complex background interference, the missed detection of small targets, and restricted generalization ability. Specifically, the U-Net v2 module is embedded in the backbone network to boost the multi-scale feature extraction performance in YOLOv11. Meanwhile, the CBAM attention mechanism is integrated to emphasize critical disease-related features. To lower the computational complexity, the SPPF module is substituted with SimSPPF. The C3k2_RCM module is appended for long–range context modeling, and the ARelu activation function is employed to alleviate the vanishing gradient problem. A database comprising 3000 images covering six types of cotton leaf diseases was constructed, and data augmentation techniques were applied. The experimental results show that ACURS-YOLO attains impressive performance indicators, encompassing a mAP_0.5 value of 94.6%, a mAP_0.5:0.95 value of 83.4%, 95.5% accuracy, 89.3% recall, an F1 score of 92.3%, and a frame rate of 148 frames per second. It outperforms YOLOv11 and other conventional models with regard to both detection precision and overall functionality. Ablation tests additionally validate the efficacy of each component, affirming the framework’s advantage in addressing complex detection environments. This framework provides an efficient solution for the automated monitoring of cotton leaf diseases, advancing the development of smart sensors through improved detection accuracy and practical applicability. Full article

To meet the growing demand for secure and reliable image protection in digital communication, this paper proposes a novel image encryption framework that addresses the challenges of high plaintext sensitivity, resistance to statistical attacks, and key security. The method combines a two-dimensional dynamically coupled map lattice (2D DCML) with elementary cellular automata (ECA) to construct a heterogeneous chaotic system with strong spatiotemporal complexity. To further enhance nonlinearity and diffusion, a multi-source perturbation mechanism and adaptive DNA encoding strategy are introduced. These components work together to obscure the image structure, pixel correlations, and histogram characteristics. By embedding spatial and temporal symmetry into the coupled lattice evolution and perturbation processes, the proposed method ensures a more uniform and balanced transformation of image data. Meanwhile, the method enhances the confusion and diffusion effects by utilizing the principle of symmetric perturbation, thereby improving the overall security of the system. Experimental evaluations on standard images demonstrate that the proposed scheme achieves high encryption quality in terms of histogram uniformity, information entropy, NPCR, UACI, and key sensitivity tests. It also shows strong resistance to chosen plaintext attacks, confirming its robustness for secure image transmission. Full article

Aims:This study aimed to identify the prognostic value of tumor invasion distance (TID) based on MRI findings in cervical-cancer (CC) patients treated with radiotherapy (RT). Methods: A total of 218 CC patients diagnosed at Fujian Cancer Hospital from December 2018 to December 2019 were included in the study. Cox regression analyses were conducted to identify independent prognostic factors for overall survival (OS), including low 1/3 vaginal involvement, a longer TID, and RT without chemotherapy. These factors were subsequently used to construct a nomogram for individualized risk prediction. Kaplan–Meier survival analysis was employed to evaluate survival outcomes and establish a risk stratification system. The performance of the new stratification was assessed using the linear trend χ² test, Akaike information criterion, and Harrell’s concordance index. Results: A longer TID was associated with worse 3-year OS (p < 0.001, HR: 3.42, 95% CI: 1.67–7.00). A longer TID, lower 1/3 vaginal involvement, and concurrent chemotherapy were independent prognostic survival factors for CC patients. Compared with the 2018 FIGO staging system, the new risk stratification system provided better monotonicity with a higher linear trend χ² value (28.03 vs. 9.35), better discriminatory ability with smaller Akaike information criterion (312 vs. 331), and a greater Harrell C statistic (0.74 vs. 0.65) for predicting 3-year OS. Conclusions: This was the first study to demonstrate the prognostic value of TID in CC patients who received RT. The new risk stratification system based on TID could complement the 2018 FIGO staging system in identifying high-risk patients for more intense treatment and care. Further prospective research with larger samples is warranted to confirm the significance of TID for CC patients treated with RT. Full article

Analcime has demonstrated potential for a variety of applications in technology, especially in adsorption and heterogeneous catalysis. In this study, synthetic analcime was investigated by using sea sand as a silica source. Sea sand was first treated with HNO₃ and NaOH. The pretreated sea sand as the silica resource and Al(NO₃)₃ as the aluminum source were used for the hydrothermal synthesis of analcime with different ratios of Si/Al and Na/Si. The products obtained under different conditions were characterized by X-ray diffraction. The results showed that analcime synthesized using acid-treated sea sand was mixed with other impurities, such as quartz and sodalite. Pure analcime was obtained using alkali-treated sea sand as the silica source. The analcime prepared under an optimized synthesis condition was further investigated via SEM, FT-IR, and TG. The particle size of the prepared analcime ranged from 40 to 50 μm. The adsorption ability of analcime was studied, and the Cu²⁺ adsorption process was found to follow a pseudo-second-order kinetic model. Full article

It has been proven that silica fume (SF), which is a by-product from the manufacturing of single-crystal silicon, is beneficial for enhancing the mechanical properties, durability, and workability of geopolymers, as it can be quickly dissolved and form silicate-based cementitious phases in alkaline environments. However, the reinforcement mechanism of SF on geopolymer remains unclear due to the chemical complexity of geopolymer and the variety of SF types. Additionally, the solubility of calcite in an alkali environment is quite limited, and thus the formation of the amorphous calcium-based gels will be thwarted due to the lack of soluble calcium ions. Most importantly, with the development of the single-crystal industry, the amorphous silica content, crystallinity, and trace elements of SF itself have changed, which blocks the understanding of the activation mechanism of geopolymers combined with SF and insoluble calcite. To unveil the underlying modification mechanisms of SF on geopolymer materials along with insoluble calcite, in this study, two types of SF were used as the fly ash replacement in a fly ash/limestone system to prepare geopolymer materials. The reinforcement effect significantly depends on the SF types even with similar particle size and chemical compositions. The results indicate that the mechanical properties of geopolymer materials modified with SFs are not only governed by the ratio and contents of Si, Ca, Al, and Mg in SFs but also depend on the crystallinity and activity of the SFs. The hydration products could be varied according to the reaction environment. The research results not only contribute to the optimization design and application of geopolymer materials but also pave new pathways for the upcycling use of solid wastes such as SF, low-grade fly ash, or even other aluminosilicate solid wastes to achieve sustainable development. Full article

Chlorophyll content is a critical indicator of the physiological status and fruit quality of pear trees, with Soil Plant Analysis Development (SPAD) values serving as an effective proxy due to their advantages in rapid and non-destructive acquisition. However, current remote sensing-based SPAD retrieval studies are primarily limited to single phenological stages or rely on a narrow set of input features, lacking systematic exploration of multi-temporal feature fusion and comparative model analysis. In this study, pear leaves were selected as the research object, and Sentinel-2 remote sensing data combined with in situ SPAD measurements were used to conduct a comprehensive retrieval study across multiple growth stages, including flowering, fruit-setting, fruit enlargement, and maturity. First, spectral reflectance and representative vegetation indices were extracted and subjected to Pearson correlation analysis to construct three input feature schemes. Subsequently, four machine learning algorithms—K-Nearest Neighbors (KNN), Random Forest (RF), Support Vector Machine (SVM), and an Optimized Integrated Algorithm (OIA)—were employed to develop SPAD retrieval models, and the performance differences across various input combinations and models were systematically evaluated. The results demonstrated that (1) both spectral reflectance and vegetation indices exhibited significant correlations with SPAD values, indicating strong retrieval potential; (2) the OIA model consistently outperformed individual algorithms, achieving the highest accuracy when using the combined feature scheme; (3) among the phenological stages, the fruit-enlargement stage yielded the best retrieval performance, with R² values of 0.740 and 0.724 for the training and validation sets, respectively. This study establishes a robust SPAD retrieval framework that integrates multi-source features and multiple models, enhancing prediction accuracy across different growth stages and providing technical support for intelligent orchard monitoring and precision management. Full article

Alkali-activated materials, as a low-carbon cementitious material, are widely known for their excellent durability and mechanical properties. In recent years, the modification of alkali-activated materials using biochar has gradually attracted attention. Fibrous biochar has a highly porous structure and large specific surface area, which can effectively adsorb alkaline ions in alkali-activated materials, thereby improving their pore structure and density. Additionally, the surface of the biochar contains abundant functional groups and chemically reactive sites. These can interact with the active components in alkali-activated materials, forming stable composite phases. This interaction further enhances the material’s mechanical strength and durability. Moreover, the incorporation of biochar endows alkali-activated materials with special adsorption capabilities and environmental remediation functions. For instance, they can adsorb heavy metal ions and organic pollutants from water, offering significant environmental benefits. However, research on biochar-modified alkali-activated materials is still in the exploratory phase. There are several challenges, such as the unclear mechanisms of how biochar preparation conditions and performance parameters affect the modification outcomes, and the need for further investigation into the compatibility and long-term stability of biochar with alkali-activated materials. Future research should focus on these issues to promote the widespread application of biochar-modified alkali-activated materials. Full article

The flight feather rachis is a lightweight, anisotropic structure that must withstand asymmetric aerodynamic loads generated during flapping flight—particularly under unidirectional compression during the wing downstroke. To accommodate this spatiotemporal loading regime, the rachis exhibits refined internal organization, especially along the dorsoventral axis. In this study, we used finite element modeling (FEM) to investigate how dorsoventral polarization in cortical keratin allocation modulates the mechanical performance of shaft-like structures under bending. All models were constructed with conserved second moments of area and identical material properties to isolate the effects of spatial material placement. We found that dorsal-biased reinforcement delays yield onset, enhances strain dispersion, and promotes elastic recovery, while ventral polarization leads to premature strain localization and plastic deformation. These outcomes align with the dorsally thickened rachises observed in flight-specialized birds and reflect their adaptation to asymmetric aerodynamic forces. In addition, we conducted a conceptual exploration of radial (cortex–medulla) redistribution, suggesting that even inner–outer asymmetry may contribute to directional stiffness tuning. Together, our findings highlight how the flight feather rachis integrates cortical material asymmetry to meet directional mechanical demands, offering a symmetry-informed framework for understanding biological shaft performance. Full article

Microbial detection in milk is crucial for food safety and quality, as beneficial and harmful microorganisms can affect consumer health and dairy product integrity. Identifying and quantifying these microorganisms helps prevent contamination and spoilage. The study employs advanced molecular techniques to detect and quantify the genomic DNA for the target hydrolytic enzyme coding genes lipA and aprX based on the multi-align sequence conserved region, specific primer pair, and hydrolysis probes designed using the singleplex qPCR and multiplex qPCR. Cultured isolates and artificially contaminated sterilized ultra-high-temperature (UHT) milk were analyzed for their specificity, cross-reactivity, and sensitivity. The finding indicated that strains with lipA and aprX genes were amplified while the other strains were not amplified. This indicated that the designed primer pairs/probes were very specific to the target gene of interest. The specificity of each design primer pair was checked using SYBR Green qPCR using 16 different isolate strains from the milk sample. The quantification specificity of each strain target gene was deemed to be with a mean Ct value for positive pseudomonas strain > 16.98 ± 1.76 (p < 0.0001), non-pseudomonas positive strain ≥ 27.47 ± 1.25 (p < 0.0001), no Ct for the negative control and molecular grade water. The sensitivity limit of detection (LOD) analyzed based on culture broth and milk sample was >10⁵ and >10⁴ in PCR amplification while it was >10⁴ and >10³ in real-time qPCR, respectively. At the same time, the correlation regression coefficient of the standard curve based on the pure culture cell DNA as the DNA concentration serially diluted (20 ng/µL to 0.0002 ng/µL) was obtained in multiplex without interference and cross-reactivity, yielding R² ≥ 0.9908 slope (−3.2591) and intercepting with a value of 37, where the efficiency reached the level of 95–102% sensitivity reached up to 0.0002 ng/µL concentration of DNA, and sensitivity of microbial load was up to 1.2 × 10² CFU/mL. Therefore, multiplex TaqMan qPCR simultaneous amplification was considered the best method developed for the detection of the lipA and aprX genes in a single tube. This will result in developing future simultaneous (three- to four-gene) detection of spoilage psychrotrophic bacteria in raw milk. Full article

Based on the formula for the sizing agent for basalt fiber, this paper presents a comprehensive study of the effects of lubricants on the properties of sizing agents, basalt fiber, and epoxy resin composite materials. Through testing and analysis of physical and chemical parameters, a new sizing agent with excellent performance was developed. The results demonstrated that the components and proportions of the lubricant significantly affected the physical and chemical parameters of the emulsion, as well as the mechanical properties of the basalt fibers and their epoxy resin composite materials. The lubricant with the combination ratio of 0.70% saturated fatty acid polyoxyethylene ester and 0.30% unsaturated fatty acid polyoxyethylene ester and imidazoline lubricant-I produced basalt fiber with the best mechanical properties. The single fiber tensile strength and yarn breaking strength increased by 18.42% and 12.5%. Furthermore, the lubricant with the combination ratio of 0.70% saturated fatty acid polyoxyethylene ester and 0.30% unsaturated fatty acid polyoxyethylene ester and imidazoline lubricant-III resulted in the best mechanical properties for Epoxy–BFRP composite materials. The tensile strength of the Epoxy–BFRP composite material increased by 13.2%, the tensile modulus increased by 45.2%, and the flexural strength increased by 12.0%. Full article

The preparation of low-cost and high-durability cement-based material systems using seawater mixing has become an urgent task in marine engineering construction. The requirements have addressed key challenges, including high transportation costs for fresh water and raw materials, poor structural durability, and difficulty in meeting actual construction schedules. Sulfatealuminate cement (CSA) has become an ideal material for marine engineering due to its high corrosion resistance, rapid early strength, which is 35–40 MPa of 3-day compressive strength and is 1.5–2 times compared ordinary Portland cement (OPC), and low-carbon characteristics, reduced production energy consumption by 35–50%, and CO₂ emissions of 0.35–0.45 tons/ton. The Cl⁻ and SO₄²⁻ in seawater can accelerate the hydration of CSA, promote the formation of ettringite (AFt), and generate Friedel’s salt fixed chloride ions, significantly enhancing its resistance to chloride corrosion. Its low alkalinity (pH ≈ 10.6) and dense structure further optimize its resistance to sulfate corrosion. In terms of environmental benefits, CSA-mixed seawater can save 15–20% fresh water. And the use of solid waste preparation can reduce environmental burden by 38.62%. In the future, it is necessary to combine multi-scale simulation to predict long-term performance, develop self-healing materials and intelligent control technologies, and promote their large-scale application in sustainable marine infrastructure. Full article

Aggressive canine behavior poses a significant threat to public health. Understanding aggressive behavior is crucial for canine socialization and human–dog interactions. This study conducted an exploratory analysis of working dogs to investigate changes in gut microbiota and neurotransmitters associated with aggressive behavior. Notably, it represents the first research to systematically differentiate canine aggression into offensive and defensive subtypes for investigation. In this study, 56 working dogs from three regions of China, comprising different breeds (11 Spaniels, 13 German Shepherds, and 32 Belgian Malinois), aged 4.89 ± 1.54 years, and of both sexes (38 males and 18 females), were assessed and grouped for aggressive behavior using a C-BARQ-based questionnaire. Then, 16S rRNA sequencing and ELISA were employed to compare differences in gut microbiota and serotonin concentrations between aggressive (n = 35) and non-aggressive (n = 21) groups, as well as between offensive (n = 26) and defensive (n = 9) aggression subgroups. β-diversity analysis confirmed no significant correlation between aggressive behavior and gut microbiota composition (p > 0.05), suggesting a limited role of gut microbiota in modulating host behavior. Comparative analysis of gut microbiota composition revealed no significant differences in phylum-level abundance among different aggression types (p > 0.05). Notably, the non-aggressive group exhibited significantly higher relative abundances of Escherichia-Shigella, Erysipelotrichaceae_UCG-003, and Clostridium_sensu_stricto_1 compared to the aggressive group (p < 0.05). Random forest analysis identified Lactobacillus as a biomarker for canine aggressive behavior and Turicibacter as a discriminatory factor between offensive and defensive aggression. The results demonstrated a strong correlation between aggression and 5-HT neurotransmission. Serum serotonin levels were significantly lower in both the defensive (39.92 ± 2.58 ng/mL) and offensive (50.07 ± 3.90 ng/mL) aggression groups compared to the non-aggressive group (59.49 ± 2.76 ng/mL), with the lowest levels found in defensively aggressive dogs. The defensive group showed significantly lower serotonin levels than the offensive group (p < 0.001). The results demonstrate that different behavioral phenotypes in aggressive dogs lead to distinct gut microbiome compositions. This suggests that microbiome analysis may facilitate early diagnosis and preventive intervention before aggressive behavior manifests. As such, 5-HT shows potential as a monitoring tool for diagnosing canine aggression, with significant practical applications in canine behavior management. Full article