Search Results (42)

By integrating EarthCARE W-band doppler cloud radar observations with GPM Ku/Ka-band dual-frequency precipitation radar data, this study constructs a novel global “pseudo tripe-frequency” radar coincidence dataset comprising 2886 coincidence events (about one-third of the events detected precipitation), aiming to systematically investigating band-dependent responses to cloud and precipitation structure. Results demonstrate that the W-band is highly sensitive to high-altitude cloud particles and snowfall (reflectivity < 0 dBZ), yet it experiences substantial signal attenuation under heavy precipitation conditions, and with low-altitude reflectivity reductions exceeding 50 dBZ, its probability density distribution is more widespread, with low-altitude peaks increasing first, and then decreasing as precipitation increases. In contrast, the Ku and Ka-band radars maintain relatively stable detection capabilities, with attenuation differences generally within 15 dBZ, but its probability density distribution exhibits multiple peaks. As the precipitation rate increases, the peak value of the dual-frequency ratio (Ka/W) gradually rises from approximately 10 dBZ to 20 dBZ, and can even reach up to 60 dBZ under heavy rainfall conditions. Several cases analyses reveal clear contrasts: In stratiform precipitation regions, W-band radar reflectivity is higher above the melting layer than below, whereas the opposite pattern is observed in the Ku and Ka bands. Doppler velocities exceeding 5 m s⁻¹ and precipitation rates surpassing 30 mm h⁻¹ exhibit strong positive correlations in convection-dominated regimes. Furthermore, the dataset confirms the impact of ice–water cloud phase interactions and terrain-induced precipitation variability, underscoring the complementary strengths of multi-frequency radar observations for capturing diverse precipitation processes. Full article

Traditional methods, such as full-factorial, orthogonal, and empirical experiments, show limited accuracy and efficiency in selecting cleaning agents for decommissioned oil and gas pipelines. They also lack the ability to quantitatively analyze the impact of multiple variables. This study proposes a data-driven optimization approach to address these limitations. Residue samples from six regions, including Dalian and Shenyang, were analyzed for inorganic components using XRD and for organic components using GC. Citric acid was used as a model cleaning agent, and cleaning efficiency was tested under varying temperature, agitation, and contact time. Key variables showed significant correlations with cleaning performance. To further quantify the combined effects of multiple factors, multivariate regression methods such as multiple linear regression and ridge regression were employed to establish predictive models. A weighted evaluation approach was used to identify the optimal model, and a method for inverse prediction was proposed. This study shows that, compared with traditional methods, the data-driven approach improves accuracy by 3.67% and efficiency by 82.5%. By efficiently integrating and analyzing multidimensional data, this method not only enables rapid identification of optimal formulations but also uncovers the underlying relationships and combined effects among variables. It offers a novel strategy for the efficient selection and optimization of cleaning agents for decommissioned oil and gas pipelines, as well as broader chemical systems. Full article

Rock slopes, composed of intact rock masses and relatively weak discontinuities, exhibit stability primarily governed by the spatial distribution of these discontinuities. Under the framework of structural control theory, acquiring discontinuity information is a fundamental prerequisite for rock slope stability analysis. However, advancements in measurement methods have significantly enhanced slope modeling precision while paradoxically reducing the efficiency of discontinuity data acquisition. To address this challenge, this study proposes a novel discontinuity identification method on the basis of high-precision UAV (unmanned aerial vehicle) point clouds, integrating principal component analysis (PCA), multi-channel gradient fusion, and cascaded edge detection techniques. Applying this approach, a high-resolution UAV-derived 3D model was constructed, and surface discontinuities were systematically identified for a slope case study in the North Qinling Belt, Shanxi Province, China. Results demonstrate that the proposed method achieves effective discontinuity identification performance, cumulatively detecting 1401 discontinuities. Statistical analysis of the identified discontinuities reveals three dominant orientation groups: I: S085° E/80°, II: S015° W/15°, and III: S005° W/85°. Full article

Objective: The purpose of this study was to investigate the association of built environment and intrapersonal factors with leisure-time physical activity (LTPA), and the possible moderating effect of intrapersonal factors on the association between the built environment and LTPA. Methods: A total of 514 older people in the village of Fuwen were included in this study. Data on LTPA, intrapersonal factors (social, fitness, medical, benefits/challenges, recognition), and the built environment (traffic safety, street connectivity, walking facilities, access to services, crime safety, aesthetics, residential density, land use mix diversity) were collected. Multivariate linear regression analysis with the “enter” method was conducted to analyze the association of perceived scores of built environment and intrapersonal factors with LTPA. Results: Among the intrapersonal factors, fitness was positively related to LTPA (p = 0.012). Among the built environment factors, traffic safety (p = 0.02) and crime safety (p = 0.047) were positively related to LTPA, while walking facilities was negatively associated with LTPA (p = 0.007). Additionally, fitness had a significant moderating effect on the association between walking facilities and LTPA (p = 0.025). Conclusions: Older people with higher fitness requirements and better perceived traffic safety and crime safety tend to engage in greater levels of LTPA. The findings provide valuable insights for policymakers, particularly in designing ecologically livable villages that promote physical activity among older populations. Full article

Microplastics (MPs), as emerging pollutants, have elicited global concerns. However, few studies have evaluated MPs with varying sizes and their adverse effects on plant growth in farmland soils. In this study, a greenhouse pot experiment was conducted to evaluate the effects of polyethylene (PE) and polybutylene adipate terephthalate (PBAT) with two particle sizes (100 μm and 1000 μm) on the growth, photosynthetic properties, and antioxidant enzyme activity of buckwheat (Fagopyrum esculentum Moench), as well as soil properties. Overall, the results showed that MPs had a certain inhibitory effect on buckwheat growth, especially with the PE treatment of 100 μm particle size. The addition of PE and PBAT inhibited photosynthesis, induced oxidative stress, and decreased soil nutrient availability (specifically ammonium nitrogen, nitrate nitrogen, available potassium, and available phosphorus content), reducing above and belowground biomass. In addition, we observed that the type and size of MPs had a significant effect on buckwheat growth parameters. Degradable MPs (PBAT) showed less toxicity than non-degradable MPs (PE), and MPs with a smaller microplastic particle size (100 μm) displayed a greater inhibitory effect than larger ones (1000 μm). In conclusion, MPs showed significant inhibitory effects on the growth of buckwheat plants, highlighting the necessity for further research in this area. Full article

Ciprofloxacin has been extensively utilized in aquaculture due to its remarkable efficacy in preventing and treating bacterial infections in fish animals. However, the widespread application of ciprofloxacin has led to significant residue accumulation, necessitating the development of rapid, sensitive and specific detection methods. In this study, we developed a novel dual-mode quantitative immunochromatographic assay based on a portable reader and a photothermal instrument, enabling on-site ciprofloxacin detection. Under optimized conditions, the portable reader mode (Mode 1) achieved a detection range of 0.1–100.0 ng/L with a limit of detection (LOD) of 0.1 ng/mL. The photothermal instrument mode (Mode 2) achieved a detection range of 0.1–500.0 ng/mL with an LOD of 0.1 ng/mL. The sensitivity and accuracy of the method were validated using an Enzyme-Linked Immunosorbent Assay. This developed method successfully detected ciprofloxacin residues in samples of Parabramis pekinensis, Larimichthys crocea, Channa argus, Carassius auratus and Micropterus salmoides, with satisfactory recovery rates. The results demonstrated excellent specificity and applicability across various fish product matrices, offering a reliable and efficient solution for the on-site monitoring of ciprofloxacin residues in fish products. Full article

The inherent uncertainties in traditional hydrological models present significant challenges for accurately simulating runoff. Combining machine learning models with traditional hydrological models is an essential approach to enhancing the runoff modeling capabilities of hydrological models. However, research on the impact of mixed models on runoff simulation capability is limited. Therefore, this study uses the traditional hydrological model Simplified Daily Hydrological Model (SIMHYD) and the machine learning model Long Short Term Memory (LSTM) to construct two coupled models: a direct coupling model and a dynamically improved predictive validity hybrid model. These models were evaluated using the US CAMELS dataset to assess the impact of the two model combination methods on runoff modeling capabilities. The results indicate that the runoff modeling capabilities of both combination methods were improved compared to individual models, with the combined forecasting model for dynamic prediction effectiveness (DPE) demonstrating the optimal modeling capability. Compared with LSTM, the mixed model showed a median increase of 12.8% in Nash Sutcliffe efficiency (NSE) of daily runoff during the validation period, and a 12.5% increase compared to SIMHYD. In addition, compared with the LSTM model, the median Nash Sutcliffe efficiency (NSE) of the hybrid model simulating high flow results increased by 23.6%, and compared with SIMHYD, it increased by 28.4%. At the same time, the stability of the hybrid model simulating low flow was significantly improved. In performance testing involving varying training period lengths, the DPE model trained for 12 years exhibited the best performance, showing a 3.5% and 1.5% increase in the median NSE compared to training periods of 6 years and 18 years, respectively. Full article

Under the global dual-carbon background, heightened public awareness of climate change and strengthened carbon taxation policies are increasing pressure on the steel industry to transition. Given the urgent need for carbon reduction, the exploration of low-carbon pathways in a blast furnace (BF) metallurgy emerges as crucial. Evaluating both asset retention and technological maturity, the development of low-carbon technologies for BFs represents the most direct and effective technical approach. This article introduces global advancements in low-carbon metallurgical technologies for BFs, showcasing international progress encompassing hydrogen enrichment, oxygen enrichment, carbon cycling technologies, biomass utilization, and carbon capture, utilization, and storage (CCUS) technologies. Hydrogen enrichment is identified as the primary technological upgrade currently, although its carbon emission reduction potential is limited to 10% to 30%, insufficient to fundamentally address high carbon emissions from BFs. Therefore, this article innovatively proposes a comprehensive low-carbon metallurgical process concept with the substitution of carbon-neutral biomass fuels at the source stage—intensification of hydrogen enrichment in the process stage—fixation of CCUS at the end stage (SS-IP-FE). This process integrates the cleanliness of biomass, the high-efficiency of hydrogen enrichment, and the thoroughness of carbon fixation through CCUS, synergistically enhancing overall effectiveness. This integrated strategy holds promise for achieving a 50% reduction in carbon emissions from BFs in the long processes. Critical elements of these core technologies are analyzed, assessing their cost-effectiveness and emission reduction potential, underscoring comprehensive low-carbon metallurgy as a pivotal direction for future steel industry development with high technological feasibility and emission reduction efficacy. The article also proposes a series of targeted recommendations, suggesting short-term focus on technological optimization, the medium-term enhancement of technology research and application, and the long-term establishment of a comprehensive low-carbon metallurgical system. Full article

Humic acid (HA) is considered a promising soil amendment for improving soil fertility. However, the effects of HA application on the microbial community, especially in aeolian sandy soils of semi-arid regions, remain insufficiently elucidated. To address this gap, a field experiment was conducted to investigate the changes in soil properties, bacterial and fungal diversity, and community structure in a buckwheat field in the fourth year after a single application of lignite humic acid (L-HA) at 0 (L-HA0), 2 (L-HA1), 4 (L-HA2), and 6 (L-HA3) ton·ha⁻¹ in an aeolian sandy soil in Inner Mongolia, China. The results demonstrated that four years after L-HA application, there was a significant (p < 0.05) decrease in soil pH, accompanied by an increase in soil water content and nutrient levels, including organic matter and total N, available P, and K. Additionally, the application of L-HA enhanced microbial biomass C and N and stimulated enzyme activities, such as urease and invertase, with these effects being more pronounced at higher application rates (L-HA2 and L-HA3). However, HA addition did not significantly (p < 0.05) affect soil microbial biomass P or alkaline phosphatase activity. The L-HA amendment enhanced the α-diversity indices of soil bacteria but did not significantly (p < 0.05) affect soil fungal diversity. The addition of L-HA induced significant changes in the composition of the soil microbial community at both the phylum and genus levels, with significant variability in microbial responses observed across the different L-HA application rates. The incorporation of L-HA notably enriched the composition of bacterial and fungal communities at the phylum level, particularly those involved in carbon cycling, including the bacterial phyla Proteobacteria and Actinobacteriota and the fungal phyla Ascomycota and Rozellomycota. At the genus level, higher L-HA application rates, specifically L-HA2 and L-HA3, exerted statistically significant (p < 0.05) effects on most bacterial and fungal genera. Specifically, these treatments increased the abundance of bacterial genera, such as Rokubacterium and fungal genera, including Plectosphaerella, Tausonia, Talaromyces, and Clonostachys. Conversely, the relative abundance of the bacterial genera Vicinamibacter and Subgroup_7, as well as the fungal genus Niesslia, was significantly reduced. Redundancy analysis (RDA) indicated that bacterial community compositions were closely associated with soil parameters, such as available P (AP), microbial biomass carbon (SMC), microbial biomass nitrogen (SMN), microbial biomass phosphorus (SMP), and invertase, while all tested soil parameters, except for alkaline phosphatase, significantly influenced the fungal community structure. Given that the changes in these soil parameters were highly correlated with the amounts of L-HA addition, this suggests that the impacts of long-term L-HA amendment on the soil bacterial and fungal communities were linked to alterations in soil physicochemical and biological properties. Full article

It is rare to conduct a comparative analysis of precipitation characteristics across regions based on long-term homogeneous active satellite observations. By collocating the Global Precipitation Measurement Dual-frequency Precipitation Radar (GPM DPR) observations with European Centre for Medium-Range Weather Forecasts 5th Reanalysis (ERA5) data, this study comparatively examines the microphysics of monsoon precipitation in the rainy season over the Yangtze-and-Huai River Basin (YHRB) and South China (SC) from 2014 to 2023. The comparative analysis is made in terms of precipitation types and intensities, precipitation efficiency index (PEI), and ice phase layer (IPL) width. The results show that the mean near-surface precipitation rate and PEI are generally higher over SC (2.87 mm/h, 3.43 h⁻¹) than over YHRB (2.27 mm/h, 3.22 h⁻¹) due to the more frequent occurrence of convective precipitation. The DSD characteristics of heavy precipitation in the wet season for both regions are similar to those of deep ocean convection, which is associated with a greater amount of water vapor. However, over SC, there are larger but fewer raindrops in the near-surface precipitation. Moreover, moderate PEI precipitation is the main contributor to heavy precipitation (>8 mm/h). Stratiform precipitation over YHRB is frequent enough to contribute more than convective precipitation to heavy precipitation (8–20 mm/h). The combined effect of stronger convective available potential energy and low-level vertical wind favors intense convection over SC, resulting in a larger storm top height (STH) than that over YHRB. Consequently, it is conducive to enhancing the microphysical processes of the ice and melt phases within the precipitation. The vertical wind can also influence the liquid phase processes below the melting layer. Collectively, these dynamic microphysical processes are important in shaping the efficiency and intensity of precipitation. Full article

Recombination-activating genes (RAGs) play a crucial role in the V(D)J recombination process and the development of immune cells. The development of the immune system and its mechanisms in pigs exhibit greater similarity to those of humans compared to other animals, thus rendering pigs a valuable tool for biomedical research. In this study, we utilized CRISPR/Cas9 gene editing and somatic cell nuclear transfer technology to generate RAG2 knockout (KO) pigs. Furthermore, we evaluated the impact of RAG2 KO on the immune organs and immune cell development through morphological observations, blood analysis and flow cytometry technology. RAG2 KO cell lines were used as donors for cloning. The reconstructed embryos were transplanted into 4 surrogate sows, and after 116 days of gestation, 2 sows gave birth to 12 live piglets, all of which were confirmed to be RAG2 KO. The thymus and spleen sizes of RAG2 KO pigs were significantly smaller than those of wild-type (WT) pigs. Hematoxylin-eosin staining results revealed that the thymus and spleen tissue structures of RAG2 KO pigs were disorganized and lacked the characteristic structures, indicating that RAG2 KO leads to dysplasia of the thymus and spleen. Hematological analysis demonstrated that the total number of white blood cells and lymphocytes in the circulation of RAG2 KO pigs was significantly lower, while the number of eosinophils was higher. Flow cytometry results indicated that the proportions of mature T and B lymphocytes were significantly reduced compared to WT pigs. These findings successfully verified the immunodeficiency phenotype of RAG2 KO pigs. This study may provide experimental animals for the development of tumor models and humanized animals. Full article

When using runoff infiltration devices to remove nitrogen and phosphorus pollutants from urban runoff, the quality of the effluent is affected by the length of dry spells between rain events. This study presents a novel analysis of how these dry periods impact the device’s effectiveness in removing pollutants and the resulting biological succession within the filter. Our analysis examines nitrogen and phosphorus removal in a rainwater filtration context, providing new insights into how dry period duration influences infiltration system performance. The results indicate that biological processes have a significant impact on reducing total nitrogen (TN) and total phosphorus (TP) contents under different drying periods. A 3-day drying period is most effective for reducing TN through biological processes, while a 7-day period is best for TP reduction. This suggests that moderately extending the drying period improves TP removal efficiency but does not enhance TN removal. The dominant bacterial phylum responsible for denitrification and phosphorus removal is Proteobacteria, with Pseudomonas and Acinetobacter as the leading genera. As the drying period lengthens, the dominant genera shift from Pseudomonas to Massilia. At a 3-day drying period, denitrification primarily occurs through Pseudomonas on the surfaces of maifanite and zeolite. At a 7-day dry-out period, Acinetobacter is mainly responsible for phosphate removal on maifanite surfaces. However, after a 14-day dry-out period, both biomass and bioactivity of Pseudomonas and Acinetobacter decrease, leading to reduced efficiency in removing nitrogen and phosphorus pollutants from runoff infiltration devices. These results aid in developing runoff infiltration devices for specific scenarios and offer crucial guidance for regulating runoff pollution control technologies. Full article

Bare soil will cause soil erosion and contribute to air pollution through the generation of dust, making the timely and effective monitoring of bare soil an urgent requirement for environmental management. Although there have been some researches on bare soil extraction using high-resolution remote sensing images, great challenges still need to be solved, such as complex background interference and small-scale problems. In this regard, the Hybrid Attention Network (HA-Net) is proposed for automatic extraction of bare soil from high-resolution remote sensing images, which includes the encoder and the decoder. In the encoder, HA-Net initially utilizes BoTNet for primary feature extraction, producing four-level features. The extracted highest-level features are then input into the constructed Spatial Information Perception Module (SIPM) and the Channel Information Enhancement Module (CIEM) to emphasize the spatial and channel dimensions of bare soil information adequately. To improve the detection rate of small-scale bare soil areas, during the decoding stage, the Semantic Restructuring-based Upsampling Module (SRUM) is proposed, which utilizes the semantic information from input features and compensate for the loss of detailed information during downsampling in the encoder. An experiment is performed based on high-resolution remote sensing images from the China–Brazil Resources Satellite 04A. The results show that HA-Net obviously outperforms several excellent semantic segmentation networks in bare soil extraction. The average precision and IoU of HA-Net in two scenes can reach 90.9% and 80.9%, respectively, which demonstrates the excellent performance of HA-Net. It embodies the powerful ability of HA-Net for suppressing the interference from complex backgrounds and solving multiscale issues. Furthermore, it may also be used to perform excellent segmentation tasks for other targets from remote sensing images. Full article

Friction stir processing (FSP) was performed on an AZ91 magnesium alloy cladding layer fabricated by a cold metal transfer (CMT) technique. Electrochemical properties and immersion corrosion behavior of the cladding layer before and after FSP in 3.5 wt.% NaCl solution were investigated. After applying the FSP, the corrosion potential and corrosion current density of the cladding layer increased from −1.455 V to −1.397 V and decreased from 4.135 μA/cm² to 1.275 μA/cm², respectively. The results of OM and SEM displayed the refinement of grains and the dispersion of β-Mg₁₇Al₁₂ second phase in the friction stir processed (FSPed) cladding layer and more severe corrosion of the unprocessed sample. The corrosion rate of the FSPed cladding layer was lower, and a more compact corrosion product film was formed on the surface of the FSPed cladding layer. EDS results and XRD patterns showed that the corrosion products was mainly composed of Mg(OH)₂. The increase in Al content in the α-Mg matrix, grain refinement, and fragmentation and dispersion of the β-Mg₁₇Al₁₂ second phase induced by FSP were the main factors that led to the improvement in corrosion resistance of the cladding layer of the AZ91 magnesium alloy fabricated by CMT. Full article

Biochar application to soil is widely recognized as a promising agricultural management practice to increase crop production by enhancing the physical, chemical, and microbiological properties of the soil. Despite the fact that numerous studies have investigated biochar production and alterations in soil properties, the effects of biochar on contrasting soils within the same region remain poorly understood, especially for semi-arid regions. Therefore, a three-year field experiment was initiated in 2020 wherein biochar was applied once to a buckwheat field at rates of 0, 20, 40, and 60 Mg ha⁻¹ (BC0: no biochar; BC1: 20 Mg ha⁻¹; BC2: 40 Mg ha⁻¹; BC3: 60 Mg ha⁻¹) for two soil types (aeolian sandy and grey meadow soil) in the northeast of Inner Mongolia, China. The soil water storage (SWS), nutrient contents (organic matter, available nitrogen, phosphorus, and potassium), microbial biomass (carbon, nitrogen, and phosphorus), and enzyme activities (urease, invertase, and alkaline phosphatase) were assessed at a soil depth of 0–15 cm as part of the soil quality assessment, and the buckwheat grain yield was estimated for crop productivity evaluation. The results showed that biochar amendment improved selected soil physicochemical and microbiological properties and buckwheat yields for both soil types. Compared to BC0, the biochar addition increased buckwheat yields, on average, by 11.23% to 22.82% in aeolian sandy soil and by 7.36% to 14.87% in grey meadow soil across three years. The results of principal component analysis (PCA) and random forest analysis (RFA) indicate that soil available nutrients and microbiological properties were the most important factors influencing buckwheat yields in aeolian sandy soil and grey meadow soil, respectively. Based on RFA, the available potassium, phosphorus, and nitrogen were found to contribute at rates of 13.10%, 10.06%, and 8.12%, respectively, to buckwheat yields in aeolian sandy soil. In contrast, alkaline phosphatase, urease, and microbial biomass carbon contribute 20.26%, 8.48%, and 7.82%, respectively, to the buckwheat yields in grey meadow soil. Following biochar addition, there was greater improvement in soil health and buckwheat production for aeolian sandy soil than grey meadow soil. In conclusion, biochar addition is an effective practice for improving soil health and crop productivity in both aeolian sandy soil and grey meadow soil in semi-arid regions. Full article