Search Results (934)

As bisphenol A (BPA) has gradually become restricted in production scenarios, the ecological risk level of its main replacement chemicals, i.e., bisphenol S (BPS) and bisphenol F (BPF), should be noted. To overcome the limitations of toxicity data, two kinds of in silico toxicology models (quantitative structure–activity relationship (QSAR) and interspecies correlation estimation (ICE) models) were used to predict enough toxicity data for multiple species. The accuracy of the coupled in silico toxicology models was verified by comparing experimental and predicted data results. Reliable predicted no-effect concentrations (PNECs) of 8.04, 35.2, and 34.2 μg/L were derived for BPA, BPS, and BPF, respectively, using species sensitivity distribution (SSD). Accordingly, the ecological risk quotient (RQ) values of BPA, BPS, and BPF for aquatic organisms were assessed in 32 major Chinese surface waters; they ranged from nearly 0 to 1.86, but were <0.1 in most cases, which indicated that the overall ecological risk level of BPA and its alternatives was low. However, in some cases, the ecological risks posed by BPA alternatives have reached equivalent levels to those posed by BPA (e.g., Liuxi River, Taihu Lake, and Pearl River), which requires further attention. This study provides evidence that the application of coupled in silico toxicology models can effectively predict toxicity data for new chemicals, avoiding time-consuming and laborious animal experiments. The main findings of this study can support environmental risk assessment and management for new chemicals that lack toxicity data. Full article

Inertial navigation systems (INSs) exhibit distinctive characteristics, such as long-duration operation, full autonomy, and exceptional covertness compared to other navigation systems. However, errors are accumulated over time due to operational principles and the limitations of sensors. To address this problem, this study theoretically explores a numerically simulated integrated inertial navigation system consisting of a single-axis cold atom interferometer gyroscope (CAIG) and a conventional inertial measurement unit (IMU). The system leverages the low bias and drift of the CAIG and the high sampling rate of the conventional IMU to obtain more accurate navigation information. Furthermore, an adaptive gradient ascent (AGA) method is proposed to estimate the variance of the measurement noise online for the Kalman filter. It was found that errors of latitude, longitude, and positioning are reduced by 43.9%, 32.6%, and 32.3% compared with the conventional IMU over 24 h. On this basis, errors from inertial sensor drift could be further reduced by the online Kalman filter. Full article

Peatlands store substantial amounts of carbon (C) in the form of peat, but are increasingly threatened by drought and shrub encroachment under climate warming. However, how peat decomposition and its temperature sensitivity (Q₁₀) vary with depth and plant litter input under these stressors remains poorly understood. We incubated peat from two depths with different degrees of decomposition, either alone or incubated with Sphagnum divinum shoots or Betula ovalifolia leaves, under five temperature levels and two moisture conditions in growth chambers. We found that drought and Betula addition increased CO₂ emissions in both peat layers, while Sphagnum affected only shallow peat. Deep peat alone or with Betula exhibited higher Q₁₀ than pure shallow peat. Drought increased the Q₁₀ of both depths’ peat, but this effect disappeared with fresh litter addition. The CO₂ production rate showed a positive but marginal correlation with microbial biomass carbon, and it displayed a rather similar responsive trend to warming as the microbial metabolism quotient. These results indicate that both deep and dry peat are more sensitive to warming, highlighting the importance of keeping deep peat buried and waterlogged to conserve existing carbon storage. Additionally, they further emphasize the necessity of Sphagnum moss recovery following vascular plant encroachment in restoring carbon sink function in peatlands. Full article

Hydrogen-rich water (HRW) has shown neuroprotective effects in acute brain injury, but its role in chronic radiation-induced brain injury (RIBI) remains unclear. This study investigated the long-term efficacy of HRW in mitigating cognitive impairment and neuronal damage caused by chronic RIBI. Fifty male Sprague Dawley rats were randomly divided into five groups: control, irradiation (IR), IR with memantine, IR with HRW, and IR with combined treatment. All but the control group received 20 Gy whole-brain X-ray irradiation, followed by daily interventions for 60 days. Behavioral assessments, histopathological analyses, oxidative stress measurements, ¹⁸F-FDG PET/CT imaging, transcriptomic sequencing, RT-qPCR, Western blot, and serum ELISA were performed. HRW significantly improved anxiety-like behavior, memory, and learning performance compared to the IR group. Histological results revealed that HRW reduced neuronal swelling, degeneration, and loss and enhanced dendritic spine density and neurogenesis. PET/CT imaging showed increased hippocampal glucose uptake in the IR group, which was alleviated by HRW treatment. Transcriptomic and molecular analyses indicated that HRW modulated key genes and proteins, including CD44, CD74, SPP1, and Wnt1, potentially through the MIF, Wnt, and SPP1 signaling pathways. Serum CD44 levels were also lower in treated rats, suggesting its potential as a biomarker for chronic RIBI. These findings demonstrate that HRW can alleviate chronic RIBI by preserving neuronal structure, reducing inflammation, and enhancing neuroplasticity, supporting its potential as a therapeutic strategy for radiation-induced cognitive impairment. Full article

Actinidia arguta is a dioecious plant, and the selection of superior male germplasm is crucial for ensuring effective pollination of female cultivars, maximizing their economic traits, and achieving high-quality yields. This study evaluated 30 male germplasms for pollen quantity, germination capacity, storage characteristics, and ultrastructural features. Results revealed significant variation in pollen germination rates (1.56–96.57%) among germplasms, with ‘Lvwang’, ‘TL20083’, and ‘TG06023’ performing best (all >90% germination). The storage characteristics study demonstrated that −80 °C is the optimal temperature for long-term pollen storage in A. arguta. Significant variations were observed in storage tolerance among different germplasms. Among them, Lvwang exhibited the best performance, maintaining a germination rate of 97.40% after 12 months of storage at −80 °C with no significant difference from the initial value, followed by TT07063. Pollen morphology was closely correlated with fertility. High-fertility pollen grains typically exhibited standard prolate or ultra-prolate shapes, featuring a tri-lobed polar view and an elliptical equatorial view, with neat germination furrows and clean surfaces. In contrast, low-fertility pollen grains frequently appeared shrunken and deformed, with widened germination furrows and visible exudates. Based on these findings, the following recommendations are proposed: ① Prioritize the use of germplasms with pollen germination rates >80% as pollinizers; ② Establish a rapid screening system based on pollen morphological characteristics. This study provides important scientific basis for both male germplasm selection and efficient cultivation practices in A. arguta (kiwiberry). Full article

Accurate evaluation of the thermal conductivity of UO₂ with defects is very significant for optimizing fuel performance and enhancing the safety design of reactors. We employed a method that combines the Boltzmann transport equation with DFT+U to calculate the thermal conductivity of UO₂ containing fission products and irradiation-induced point defects. Our investigation reveals that the thermal conductivity of UO₂ is influenced by defect concentration, defect type, and temperature. Fission products and irradiation defects result in a decrease in thermal conductivity, but they have markedly different impacts on phonon scattering mechanisms. Metal cations tend to scatter low-frequency phonons (less than 5.8 THz), while the fission gas xenon scatters both low-frequency and high-frequency phonons (greater than 5.8 THz), depending on its occupancy at lattice sites. Uranium vacancies scatter low-frequency phonons, while oxygen vacancies scatter high-frequency phonons. When uranium and oxygen vacancies coexist, they scatter phonons across the entire frequency spectrum, which further results in a significant reduction in the thermal conductivity of UO₂. Our calculated results align well with experimental data across a wide temperature range and provide fundamental insights into the heat transfer mechanisms in irradiated UO₂. These findings are essential for establishing a thermal conductivity database for UO₂ under various irradiation conditions and benefit the development of advanced high-performance UO₂ fuel. Full article

This research presents DuSAFNet, a lightweight deep neural network for fine-grained bird audio classification. DuSAFNet combines dual-path feature fusion, spectral–temporal attention, and a multi-band ArcMarginProduct classifier to enhance inter-class separability and capture both local and global spectro–temporal cues. Unlike single-feature approaches, DuSAFNet captures both local spectral textures and long-range temporal dependencies in Mel-spectrogram inputs and explicitly enhances inter-class separability across low, mid, and high frequency bands. On a curated dataset of 17,653 three-second recordings spanning 18 species, DuSAFNet achieves 96.88% accuracy and a 96.83% F1 score using only 6.77 M parameters and 2.275 GFLOPs. Cross-dataset evaluation on Birdsdata yields 93.74% accuracy, demonstrating robust generalization to new recording conditions. Its lightweight design and high performance make DuSAFNet well-suited for edge-device deployment and real-time alerts for rare or threatened species. This work lays the foundation for scalable, automated acoustic monitoring to inform biodiversity assessments and conservation planning. Full article

Photocatalysis is considered to be a very promising method for the degradation of organic matter, because its process of degrading organic matter is safe. However, some problems such as weak absorption of visible light and electronic-hole recombination easily are obviously drawbacks. In this paper, three different morphologies of Bi₅O₇I (nanoball, nanosheet, and nanotube) were successfully prepared by solvothermal method, which was used for the degradation of Rhodamine B (RhB). Comparing the photocatalytic effect of three different morphologies and concluding that the optimal morphology was the Bi₅O₇I nanoball (97.8% RhB degradation within 100 min), which was analysed by the characterisation tests. Free radical trapping experiments were tested, which revealed that the main roles in the degradation process were singlet oxygen (¹O₂) and holes (h⁺). The degradation pathways of RhB were analyzed in detail. The photo/electrochemical parts of the three materials were analysed and explained the degradation mechanism of RhB degradation. This investigate provides a very valuable guide for the development of multiple morphologies of bismuth-based photocatalysts for removing organic dyes in aquatic environment. Full article

Wireless sensor networks provide a solution for structural health monitoring of aviation pipelines. In the installation environment of aviation pipelines, widespread vibrations can be utilized to extract energy through vibration energy harvesting technology to achieve self-powering of sensors. This study analyzed the vibration characteristics of aviation pipeline structures. The vibration characteristics and influencing factors of typical aviation pipeline structures were obtained through simulations and experiments. An N-shaped symmetric vibration energy harvester was designed considering the limited space in aviation pipeline structures. To improve the efficiency of electrical energy extraction from the vibration energy harvester, expand its operating frequency band, and achieve efficient vibration energy harvesting, this study first analyzed its natural frequency characteristics through theoretical analysis. Finite element simulation software was then used to analyze the effects of the external excitation acceleration direction, mass and combination of counterweights, piezoelectric sheet length, and piezoelectric material placement on the output power of the energy harvester. The structural parameters of the vibration energy harvester were optimized, and the optimal working conditions were determined. The experimental results indicate that the N-shaped symmetric vibration energy harvester designed and optimized in this study improves the efficiency of vibration energy harvesting and can be arranged in the limited space of aviation pipeline structures. It achieves efficient energy harvesting under multi-modal conditions, different excitation directions, and a wide operating frequency band, thus meeting the practical application requirement and engineering feasibility of aircraft design. Full article

Coffee is one of the most widely consumed beverages worldwide, primarily due to the stimulating effects attributed to its caffeine content. However, excessive intake of caffeine results in negative effects, including palpitations, anxiety, and insomnia. Therefore, low-caffeine coffee has captivated growing consumer interest, highlighting its significant market potential. Traditional decaffeination methods often lead to non-selective extraction, resulting in a loss of desirable flavor compounds, thereby compromising coffee quality. In recent years, microbial fermentation has emerged as a promising, targeted, and safe approach for reducing caffeine content during processing. Additionally, mixed-culture fermentation further enhances coffee flavor and overcomes the drawbacks of monoculture fermentation, such as low efficiency and limited flavor profiles. Nonetheless, several challenges are yet to be resolved, including microbial tolerance to caffeine and related alkaloids, the safety of fermentation products, and elucidation of the underlying mechanisms behind microbial synergy in co-cultures. This review outlines the variety of microorganisms with the potential to degrade caffeine and the biochemical processes involved in this process. It explores how microbes tolerate caffeine, the safety of metabolites produced during fermentation, and the synergistic effects of mixed microbial cultures on the modulation of coffee flavor compounds, including esters and carbonyls. Future directions are discussed, including the screening of alkaloid-tolerant strains, constructing microbial consortia for simultaneous caffeine degradation for flavor enhancement, and developing high-quality low-caffeine coffee. Full article

Carbon nanotubes are promising in agriculture for improving crop resilience and delivering agrochemicals. However, their effects on insect pests, especially chewing pests such as the fall armyworm (Spodoptera frugiperda), remain underexplored. In this study, we investigated how two types of functionalized multi-walled carbon nanotubes—hydroxylated (MWCNTs-OH) and carboxylated (MWCNTs-COOH), both obtained from Jiangsu Xianfeng Nano (Nanjing, China)—affect the pest’s development and reproduction. Using an age-stage two-sex life table approach, we fed larvae diets containing 0.04, 0.4, or 4 mg/g of these nanomaterials. Both types of MWCNTs exhibited concentration-dependent inhibitory effects. At the highest dose (4 mg/g), larval development was significantly prolonged, adult pre-oviposition periods increased, and fecundity (egg production) sharply declined, especially with MWCNTs-OH. Population growth parameters were also suppressed: net reproductive rate (R₀), intrinsic rate of increase (r), and finite rate of increase (λ) were reduced at 4 mg/g, particularly with MWCNTs-OH, while mean generation time (T) was extended with MWCNTs-COOH. Overall, MWCNTs-OH demonstrated a greater inhibitory impact compared to MWCNTs-COOH. These findings suggest that functionalized MWCNTs could serve as potential novel pest control agents against S. frugiperda by impeding its development and reproduction. Full article

Establishing a high-precision passenger flow prediction model is a critical and complex task for the optimization of urban rail transit systems. With the development of artificial intelligence technology, the data-driven technology has been widely studied in the intelligent transportation system. In this study, a neural network model based on the data-driven technology is established for the prediction of passenger flow in multiple urban rail transit stations to enable smart perception for optimizing urban railway transportation. The integration of network units with different specialities in the proposed model allows the network to capture passenger flow data, temporal correlation, spatial correlation, and spatiotemporal correlation with the dual attention mechanism, further improving the prediction accuracy. Experiments based on the actual passenger flow data of Beijing Metro Line 13 are conducted to compare the prediction performance of the proposed data-driven model with the other baseline models. The experimental results demonstrate that the proposed prediction model achieves lower MAE and RMSE in passenger flow prediction, and its fitted curve more closely aligns with the actual passenger flow data. This demonstrates the model’s practical potential to enhance intelligent transportation system management through more accurate passenger flow forecasting. Full article

The design of friction materials with integrated friction reduction and wear resistance functions has been a research challenge for many researchers and scholars, based on this problem, this paper proposes a nickel-based hard-soft composite coating structure. With 20CrMo steel as the matrix material, Ni20 powder doped with reinforced phase WC as hard coating material, using laser melting technology to prepare nickel-based hard coating on the surface of 20CrMo. PTFE emulsion and MoS₂ as a soft coating are prepared on the hard coating, and the nickel-based hard-soft composite coating is formed. At 6N-0.3 m/s, the new interface structure obtains the optimum tribological performance, and compared to 20CrMo, the friction coefficient and wear amount are reduced by 83% and 93% respectively. The new friction interface can obtain stable and prominent tribological properties at wide load and low to high speed, which can provide the guidance on the structural design of friction reduction and wear resistance materials. Full article

Soil available nitrogen (AN) is a critical nutrient for plant absorption and utilization. Accurately mapping its spatial distribution is essential for improving crop yields and advancing precision agriculture. In this study, 188 AN soil samples (0–20 cm) were collected at Heshan Farm, Nenjiang County, Heihe City, Heilongjiang Province, in 2023. The soil available nitrogen content ranged from 65.81 to 387.10 mg kg⁻¹, with a mean value of 213.85 ± 61.16 mg kg⁻¹. Sentinel-2 images and normalized vegetation index (NDVI) and enhanced vegetation index (EVI) time series data were acquired on the Google Earth Engine (GEE) platform in the study area during the bare soil period (April, May, and October) and the growth period (June–September). These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. The accuracy of different strategies was evaluated using 5-fold cross-validation. The research results indicate that (1) the introduction of growth information at different growth periods of soybean and maize has different effects on the accuracy of soil AN mapping. In soybean plantations, the introduction of EVI data during the pod setting period increased the mapping accuracy R² by 0.024–0.088 compared to other growth periods. In maize plantations, the introduction of EVI data during the grouting period increased R² by 0.004–0.033 compared to other growth periods, which is closely related to the nitrogen absorption intensity and spectral response characteristics during the reproductive growth period of crops. (2) Combining the crop types and their optimal period growth information could improve the mapping accuracy, compared with only using the bare soil period image (R² = 0.597)—the R² increased by 0.035, the root mean square error (RMSE) decreased by 0.504%, and the mapping accuracy of R² could be up to 0.632. (3) The mapping accuracy of the bare soil period image differed significantly among different months, with a higher mapping accuracy for the spring data than the fall, the R² value improved by 0.106 and 0.100 compared with that of the fall, and the month of April was the optimal window period of the bare soil period in the present study area. The study shows that when mapping the soil AN content in arable land, different crop types, data collection time, and crop growth differences should be considered comprehensively, and the combination of specific crop types and their optimal period growth information has a greater potential to improve the accuracy of mapping soil AN content. This method not only opens up a new technological path to improve the accuracy of remote sensing mapping of soil attributes but also lays a solid foundation for the research and development of precision agriculture and sustainability. Full article

Meaning-centered coping is regarded as an effective strategy for managing stress and preventing mental disorders. However, it remains unclear how it influences mental health by affecting both the self and social connection dimensions. This study investigated 856 college students through a questionnaire, examining how meaning-centered coping affects their mental health (depression and anxiety). Additionally, this study explored the roles of interdependent self-construal and school connectedness as mediators in this process. The results indicate that meaning-centered coping influences mental health either via the mediation of school connectedness alone (indirect effect for depression: β = −0.08, 95% CI [−0.11, −0.04]; for anxiety: β = −0.06, 95% CI [−0.10, −0.03]) or via the sequential mediation of interdependent self-construal and school connectedness (indirect effect for depression: β = −0.08, 95% CI [−0.11, −0.05]; for anxiety: β = −0.06, 95% CI [−0.10, −0.04]). This study reveals that college students who are skilled at seeking and reconstructing their sense of meaning can effectively cope with stress and alleviate related depression and anxiety. This coping mechanism operates through perceived school connectedness or through activated interdependent self-construal followed by perceived school connectedness, subsequently reducing anxiety and depression induced by chronic stress. This study theoretically deepens the comprehension of the mechanism on meaning-centered coping, while practically, the findings provide valuable insights for educating training college students to leverage the wisdom of meaning theory to sustain their mental health in future challenges. Full article