Search Results (1,259)

The downstream irrigation district of the Yarkant River basin has experienced increasing soil salinization driven by shallow groundwater levels, constraining the sustainable development of regional agriculture. However, the dynamic relationship between soil salinity and groundwater depth in this region remains unclear, limiting the effectiveness of saline–alkali land remediation strategies based on groundwater level regulation. In this study, field data were collected in 2025 on total soil salinity, concentrations of eight major ions, groundwater depth, and groundwater salinity in the irrigation district. The spatiotemporal distribution patterns of soil salinity, groundwater depth, and groundwater salinity were analyzed, along with their interrelationships. The soils in the irrigation district are predominantly mildly to moderately saline. Overall, soil salinity exhibits clear seasonal patterns, characterized by accumulation due to evaporation in spring and autumn and dilution through irrigation in summer. The dominant anions in the soil were SO₄²⁻ and Cl⁻, while Ca²⁺ and Na⁺ were the dominant cations, indicating a chloride–sulfate salinity type. Soil salinity shows a significant positive correlation with groundwater mineralization. A clear Boltzmann function relationship was identified between soil salinity and groundwater depth, revealing a critical groundwater depth of 2.10–2.18 m for salt accumulation in the irrigation district. The critical groundwater depths corresponding to soil salinity and major salt ions, from lowest to highest, are Cl⁻ < Na⁺ < total salts < SO₄²⁻ < Ca²⁺. Random forest regression analysis identified the main factors influencing soil salinity and their relative importance, ranked from highest to lowest as follows: groundwater depth > Na⁺ > Cl⁻ > groundwater salinity > Ca²⁺ > SO₄²⁻ > Mg²⁺ > HCO₃⁻ > K⁺ > CO₃²⁻. Maintaining groundwater depth below the critical threshold and focusing on groundwater ions that strongly influence soil salinity can effectively alleviate soil salinization in the lower Yarkant River irrigation district caused by shallow, highly mineralized groundwater. Full article

Post-translational modifications (PTMs) are crucial chemical alterations occurring on proteins post-synthesis, impacting various cellular processes. During viral infections, PTMs are shown to play a multitude of roles in viral replication, host interaction, and immune evasion. Thus, these modifications can influence infectivity, with direct impact on the anti-viral host immune responses and potentially viral adaptation across species. This field is still scarcely explored, whilst understanding PTMs is not only important to advance the knowledge of virus pathology but also potentially to provide insights for vaccine development. In this review, we attempt to summarize the latest findings mainly published over the last 10 years, focusing on the roles of PTMs involved in virus infection and anti-viral immune responses, in the context of relevant human respiratory infections: influenza A virus (IAV), respiratory syncytial virus (RSV), and SARS-CoV-2. We decided to concentrate on these three viruses because they currently represent a global health problem due to recurrent outbreaks and pandemic potential. A deeper characterization of the PTMs may help in understanding virus–host interaction with possible implications on curative strategies. Further, we will report on cutting-edge technologies to study in vitro virus infection in different cellular-based systems. In particular, we describe and discuss the application of 2D and 3D lung organoid cell-culture systems as in vitro models to mimic respiratory environments and to study the PTMs in a controlled setting. Finally, we will discuss the importance of PTMs in the context of next-generation vaccine design, especially for their potential role to offer effective protection against respiratory viruses. Full article

Soda saline–alkaline soils have seriously restricted the sustainable development of agriculture in the Songnen Plain, China. Applying soil amendments has proven to be an effective remediation strategy for these sodic soils; however, conventional amendments face limitations, including prolonged remediation periods and the potential to cause secondary pollution upon misapplication. In this study, we combined three different amendments and applied them as four distinct treatments—citric acid + nano-silica (CS), citric acid + nano-silica + humic acid (CSH), nano-silica + humic acid (SH), and citric acid + humic acid (CH)—with no amendment used as the control (CK). The effects of these treatments on improving the soda saline–alkali soil was evaluated using a field positioning experiment. The results indicate that, compared to the CK treatment, applying the amendments significantly increased the concentrations of available phosphorus (AP) (9.19% to 44.43%) and organic matter (SOM) (3.53% to 16.48%) while decreasing alkalinity and salinity indicators (pH, EC (electrical conductivity), ESP (exchangeable sodium percentage), SAR (sodium adsorption ratio), and TA (total alkalinity)) and soil alkali stress ions (water-soluble and exchangeable Na⁺, CO₃²⁻, and HCO₃⁻). The partial least squares path modeling analysis (PLS-PM) demonstrated that the application of the amendments improved soil quality by changing its alkalinity and ion composition, thereby increasing the maize yield (from 3.01% to 9.80%). Full article

CO₂ miscible flooding provides dual advantages in enhancing oil recovery and facilitating geological sequestration, and has become a key technical approach for developing low-permeability oil reservoirs and carbon emission reduction. The pore-scale flow mechanisms governing CO₂ behavior during miscible flooding are crucial for achieving efficient oil recovery and secure geological storage of CO₂. In this study, pore-scale two-phase flow simulations of CO₂ miscible flooding in porous media are performed using a coupled laminar-flow and diluted-species-transport framework. The model captures the effects of diffusion, concentration distribution, and pore structure on the behavior of CO₂ miscible displacement. The results indicate that: (1) during miscible flooding, CO₂ preferentially displaces oil in larger pore throats and subsequently invades smaller throats, significantly improving the mobilization of oil trapped in small pores; (2) increasing the injection velocity accelerates the displacement front and improves oil utilization in dead-end and trailing regions, but a “velocity saturation effect” is observed—when the inject velocity exceeds 0.02 m/s, the displacement pattern stabilizes and further gains in ultimate recovery become limited; (3) higher injected CO₂ concentration accelerates CO₂ accumulation within the pores, enlarges the miscible sweep area, promotes a more uniform concentration field, leads to a smoother displacement front, and reduces high-gradient regions, thereby suppressing local instabilities, and improves displacement efficiency, although its effect on overall recovery remains modest; (4) CO₂ dynamic viscosity strongly influences flow stability: low-viscosity conditions promote viscous fingering and severe local bypassing, whereas higher viscosity stabilizes flow but increases injection pressure drop and energy consumption, indicating a necessary trade-off between flow stability and operational efficiency. Full article

The brown marmorated stink bug (Halyomorpha halys Stål, 1855) is a globally invasive polyphagous pest that challenges conventional chemical control. We evaluated caffeine-based preparations—alone and combined with chitosan, acetic acid, and ethanol—against adults under laboratory conditions using topical application and 72 h mortality readouts. Among caffeine-in-water treatments, 3% (w/v) yielded the highest mortality (52.5%), indicating an efficacy peak constrained by solubility/precipitation. The most effective overall formulation was 1% caffeine + 1% chitosan + 3% acetic acid, reaching 57.5% mortality and outperforming higher caffeine loads (3–5%). Ethanol as a co-solvent consistently reduced efficacy across concentrations. Patterns across treatments indicate that bioefficacy was driven predominantly by formulation chemistry rather than dose: the chitosan–acetic acid matrix enhanced cuticular deposition, retention, and diffusion of caffeine, whereas high caffeine levels likely triggered detoxification responses and/or reduced bioaccessible dose due to precipitation. By enabling lower active ingredient loads with equal or greater bioactivity, the biodegradable chitosan–acid system improves the environmental profile of caffeine-based insecticides. These results identify a practical, low-complexity path to optimize caffeine delivery for H. halys control and support integration into IPM frameworks. Field validation, testing on earlier life stages, and assessment of non-target effects and resistance biomarkers are warranted to translate these findings into robust, sustainable pest management strategies. Full article

Landfills are vital waste management techniques in South Africa but are significant sources of greenhouse gases (GHGs) and air pollutants that can threaten nearby communities. This study provides a novel integrated assessment approach by combining high-resolution TROPOMI satellite observations with AERMOD dispersion modelling. This study investigates the dispersion characteristics and potential health impacts of landfill gas (LFG) emissions from the Thohoyandou landfill. Unlike previous studies that rely solely on modelling or field measurements, this work offers the first satellite-validated landfill gas dispersion analysis in South Africa. The modelling results indicated that the highest hourly concentrations reached 456,056 µg/m³ for CH₄ and 735,108 µg/m³ for CO₂, while annual maximum concentrations were 15,699 µg/m³ and 30,590 µg/m³, respectively. Health risk assessments were performed for 26 volatile organic compounds and hazardous air pollutants (VOCs/HAPs) using the USEPA methodology. Most individual hazard quotient (HQ) values were below 1, except for 1,1,2-trichloroethane (HQ = 1.27). The cumulative HQ of 1.86 suggested a potential non-carcinogenic risk for nearby residents. Carcinogenic risk analysis identified 13 compounds, with hydrogen sulphide posing the highest probability of cancer risk. The findings reveal that LFG emissions may adversely affect air quality and present both non-carcinogenic and carcinogenic health risks to populations living or working near the landfill. Full article

Straw returning is a common agricultural practice that can enhance rice (Oryza sativa L.) yield in paddy systems. However, it also leads to a significant increase in greenhouse gas emissions (GHG). Fortunately, this negative impact can be mitigated by implementing enhanced oxygenation strategies during rice cultivation. This study explored the effects of various oxygenation measures on GHG under straw-returning conditions through controlled pot experiments. Six distinct treatments were applied. These included straw not returned (NR, no straw applied), straw returned (SR), controlled irrigation (CI), oxygenation irrigation (OI), application of oxygenated fertilizer (OF, CaO₂), and use of biochar-based fertilizer (CF). All treatment groups, with the exception of the NR group, involved the return of straw to the field. Creating rice production methods that increase yield and decrease emissions is of great importance to agricultural ecology. We postulated that using aeration methods under straw return conditions would stabilize rice yield and reduce GHG. The experimental results were consistent with our hypothesis. The experiment evaluated multiple parameters, including rice yield, leaf photosynthetic performance, soil ammonium and nitrate nitrogen (N) levels, and greenhouse gas emissions. The findings revealed that different oxygenation approaches significantly promoted rice tillering. Oxygenation measures have been shown to enhance rice yield by 19% to 65%. The highest tiller numbers were observed in the SR (22.75) and CF (21.6) treatments. Among all treatments, the CF achieved the highest seed setting rate at 0.94, which was notably greater than that of the other treatments. Total plant biomass was also significantly higher in the straw returning treatment (109.36 g), surpassing all other treatments. In terms of soil nitrogen dynamics, the OF treatment resulted in the highest nitrate nitrogen content. Meanwhile, the ammonium nitrogen concentrations across the four oxygenation treatments (CI, OI, OF, CF) ranged from approximately 7 to 8.9 mg kg⁻¹. Regarding GHG, the CF treatment exhibited the lowest methane emissions, which were 33% lower compared to the straw returning treatment. The OF led to a 22% reduction in carbon dioxide emissions (CO₂) relative to straw returning. Most notably, the CF reduced nitrous oxide emissions by 37% compared to the straw returning treatment. Overall, SR was found to substantially increase GHG. In contrast, all tested oxygenation measures—CI, OI, OF, and CF—were effective in suppressing GHG to varying degrees. Among these, the CF and OF demonstrated the most balanced and outstanding effects, both in reducing emissions and maintaining stable rice yields. Full article

Surface-enhanced Raman scattering (SERS) is a highly sensitive analytical technique capable of single-molecule detection, yet its performance strongly depends on the underlying plasmonic architecture. In this study, we developed a robust SERS platform based on long-range–ordered bullseye plasmonic nano-gratings with tunable period and filling fraction, fabricated via electron beam lithography and reactive ion etching and uniformly coated with a thin gold film. These concentric nanostructures support efficient surface plasmon resonance and radial SPP focusing, enabling intense electromagnetic field enhancement across the substrate. Using this platform, we achieved quantitative detection of Rhodamine 6G with enhancement factors of ${10}^5$. Notably, our results reveal a previously unrecognized mechanistic insight: the geometric configuration producing the strongest local electric fields does not yield the highest SERS enhancement, due to misalignment between the dominant field orientation and the molecular polarizability tensor. This finding explains the non-monotonic dependence of SERS performance on grating geometry and introduces a new design principle in which both field strength and field–molecule alignment must be co-optimized. Overall, this work provides a mechanistic framework for rationally engineering plasmonic substrates for sensitive and quantitative molecular detection. Full article

Generative artificial intelligence (GenAI) is rapidly permeating research practices, yet knowledge about its use and topical profile remains fragmented across tools and disciplines. In this study, we present a cross-disciplinary map of GenAI research based on the Web of Science Core Collection (as of 4 November 2025) for the ten tool lines with the largest number of publications. We employed a transparent query protocol in the Title (TI) and Topic (TS) fields, using Boolean and proximity operators together with brand-specific exclusion lists. Thematic similarity was estimated with the Jaccard index for the Top–50, Top–100, and Top–200 sets. In parallel, we computed volume and citation metrics using Python and reconstructed a country-level co-authorship network. The corpus comprises 14,418 deduplicated publications. A strong concentration is evident around ChatGPT, which accounts for approximately 80.6% of the total. The year 2025 shows a marked increase in output across all lines. The Jaccard matrices reveal two stable clusters: general-purpose tools (ChatGPT, Gemini, Claude, Copilot) and open-source/developer-led lines (LLaMA, Mistral, Qwen, DeepSeek). Perplexity serves as a bridge between the clusters, while Grok remains the most distinct. The co-authorship network exhibits a dual-core structure anchored in the United States and China. The study contributes to bibliometric research on GenAI by presenting a perspective that combines publication dynamics, citation structures, thematic profiles, and similarity matrices based on the Jaccard algorithm for different tool lines. In practice, it proposes a comparative framework that can help researchers and institutions match GenAI tools to disciplinary contexts and develop transparent, repeatable assessments of their use in scientific activities. Full article

Thin-film organic solar cells (TFOSCs) are gaining momentum as next-generation photovoltaic technologies due to their lightweight nature, mechanical flexibility, and low cost-effective fabrication. In this pioneering study, we report for the first time the incorporation of cobalt-doped zinc sulfide $(\mathrm{Z}\mathrm{n}\mathrm{S}/\mathrm{C}\mathrm{o})$ nanoparticles (NPs) into a poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PC61BM) bulk-heterojunction photoactive layer. $\mathrm{Z}\mathrm{n}\mathrm{S}/\mathrm{C}\mathrm{o}$ NPs were successfully synthesized via a wet chemical method and integrated at varying concentrations (1%wt, 3%wt, and 5%wt) to systematically investigate their influence on device performance. The optimal doping concentration of 3%wt yielded a remarkable power conversion efficiency (PCE) of 4.76%, representing a 102% enhancement over the pristine reference device (2.35%) under ambient laboratory conditions. The observed positive trend is attributed to the localized surface plasmon resonance (LSPR) effect and near-field optical enhancement induced by the presence of ZnS/Co NPs in the active layer, thereby increasing light-harvesting capability and exciton dissociation. Comprehensive morphological and optical characterizations using high-resolution scanning electron microscopy (HRSEM), high-resolution transmission electron microscopy (HRTEM), and spectroscopic techniques confirmed uniform nanoparticle dispersion, nanoscale crystallinity, and effective light absorption. These findings highlight the functional role of $\mathrm{Z}\mathrm{n}\mathrm{S}/\mathrm{C}\mathrm{o}$ NPs as dopants in enhancing TFOSC performance, providing valuable insights into optimizing nanoparticle concentration. This work offers a scalable and impactful strategy for advancing high-efficiency, flexible, and wearable organic photovoltaic devices. Full article

Carbon dots (CDs) have recently emerged as a novel class of eco-friendly and multifunctional corrosion inhibitors owing to their nanoscale dimensions, tunable surface functionalities, and sustainable synthesis pathways. This review summarizes the latest progress in CD-based inhibitors, focusing on synthesis methods, applications, and inhibition mechanisms. Various strategies—including hydrothermal/solvothermal treatment, microwave irradiation, pyrolysis, electrochemical synthesis, and chemical oxidation—have been employed to obtain CDs with tailored size, heteroatom doping, and surface groups, thereby enhancing their inhibition efficiency. CDs have demonstrated remarkable applicability across diverse corrosive environments, including acidic, neutral chloride, CO₂-saturated, microbiologically influenced, and alkaline systems, often achieving inhibition efficiencies exceeding 90%. Mechanistically, their performance arises from strong adsorption and compact film formation, heteroatom-induced electronic modulation, suppression of anodic and cathodic reactions, and synergistic effects of particle size and structural configuration. Compared with conventional inhibitors, CDs offer higher efficiency, environmental compatibility, and multifunctionality. Despite significant progress, challenges remain regarding precise structural control, scalability of synthesis, and deeper mechanistic understanding. The effectiveness of CDs inhibitors is highly dependent on factors such as pH, temperature, inhibitor concentration, and exposure time, which should be tailored for specific applications to maximize performance. Future research should focus on integrating sustainable synthesis with rational heteroatom engineering and advanced characterization to achieve long-term, cost-effective, and environmentally benign corrosion protection solutions. Compared to earlier reviews, this review discusses the emerging trends in the field of CDs as corrosion inhibitors. Full article

In this study, the effects of highly active alkaline electrolyzed water (AEW) on the mechanical properties, shrinkage behavior, alkali activation reaction characteristics, and microstructure of alkali-activated fly ash/slag mortars at different alkali concentrations are systematically investigated, with ordinary tap water as the reference (OM group). The results showed that the EM group exhibited improved strength compared with the OM group. Specifically, the 28 d compressive and flexural strength of EM mortar at an alkali concentration of 4.0% were 13.5% and 7.5% higher than those of OM mortar, respectively. The 28 d drying shrinkage rate of the EM group was reduced by 7.3–11.2%. The EM group had a higher mass loss in the bounding water decomposition stage and a lower mass loss in the Ca(OH)₂ and CaCO₃ decomposition stages. XRD results showed that the EM group had a broader and stronger characteristic peak of N-A-S-H/C-A-S-H gel and a weaker characteristic peak of Ca(OH)₂ than the OM group. The enhancement mechanism of AEW was attributed to its high ion activity, the dense microstructure formed by sufficient alkali activation reaction reduced the pore content, thereby improving the strength. The AEW-based alkali-activated material in this study can be widely used in green low-carbon infrastructure fields such as new energy infrastructure and ocean engineering. Full article

The extensive area of goaf makes high-temperature points highly concealed, and prolonged heating can easily trigger spontaneous coal combustion. Traditional temperature monitoring methods are limited in spatial coverage and thus fail to detect high-temperature points in a timely manner. To address this issue, this study proposes an integrated analytical method combining numerical simulation and intelligent inversion, with Taihe Coal Mine as the research object. First, A coupled flow–temperature–gas field model of the goaf was established in COMSOL Multiphysics 6.3 to simulate working-face CO concentration distributions corresponding to high-temperature points at different locations, thereby constructing a comprehensive dataset. Then, a BP neural network prediction model improved by the dung beetle optimization algorithm (DBO-BP) was trained to infer the spatial location of high-temperature points based on CO concentration distributions. Finally, a geometric prediction method was introduced to guide precise drilling within the predicted high-risk areas for field verification. The results demonstrate that the proposed DBO-BP model can effectively trace the locations of high-temperature points from CO concentration data. When combined with the geometric prediction method, it provides an efficient and reliable technical solution for the early prevention of spontaneous coal combustion in goaf. Full article

In controlled environment agriculture (CEA), CO₂ enrichment can promote photosynthesis while simultaneously reducing evapotranspiration, but the optimal settings vary depending on crop type, growth stage, and microclimate. This study presents a near-field remote sensing framework that fuses RGB image features with environmental variables to predict the CO₂ uptake/respiration dynamics of five leafy vegetables grown in a hydroponic culture system and evaluate their impact on resource efficiency under CO₂ control. A hybrid deep model incorporating You Only Look Once version 11 (YOLOv11) and a Residual Network with 50 layers (ResNet50) extracts growth-related visual cues and integrates them with tabular features (CO₂, temperature, and light conditions) to predict chamber CO₂ dynamics. Performance was evaluated by Mean Absolute Error (MAE)/Mean Squared Error (MSE) on withheld data, and the system-level impacts on water use (ET), pumping energy, and relative yield were analyzed using a conventional greenhouse model. The model exhibited high accuracy (MAE = 0.95; MSE = 1.62). Scenario analysis results showed that increasing ambient CO₂ concentration from 400 to 1200 ppm reduced modeled water demand by approximately 11%, increased modeled yield by approximately 9%, and resulted in a corresponding reduction in pumping energy per unit area. Unlike conventional single-crop, table-based approaches, this study demonstrates multi-crop generalization and image-environment fusion for CO₂ dynamic prediction, establishing proximity sensing as a viable decision-making layer for CEA. While yield/ET results were simulated rather than measured in long-term trials, and leaf area normalization was not available, the proposed framework provides a viable path for data-driven CO₂ control in indoor farms by linking image-based monitoring with operational optimization. Full article

Cadmium (Cd) accumulation in rice poses a serious threat to global food safety and human health. Foliar application of nano-silica (Si) offers a promising remediation strategy, but its efficacy is often limited by poor droplet retention on hydrophobic leaf surfaces. This study hypothesized that surfactants could overcome this barrier by enhancing the foliar performance of nano-Si. Through field experiments, we evaluated the synergistic effects of five surfactants (Polyvinylpyrrolidone (PVP) powder, Aerosol OT (AOT), Rhamnolipid (RH), Didecyldimethylammonium bromide (DDAB), and Alkyl Polyglycoside (APG)) when combined with nano-silica. The results demonstrated that all surfactants significantly improved wetting and retention, with alkyl polyglycoside (APG) and polyvinylpyrrolidone (PVP) being the most effective. These improvements translated into a remarkable suppression of Cd translocation within rice plants. The PVP–nano-Si combination emerged as the most potent treatment, reducing grain Cd content by 50% and achieving the lowest levels of As and Cr among all treatments. Furthermore, this synergistic effect was linked to a significant increase in grain concentrations of manganese (Mn) and zinc (Zn), which exhibit a competitive relationship with Cd. The findings reveal that surfactant co-application not only optimizes the physical application of nano-Si but also triggers beneficial nutrient–Cd interactions, providing a novel and efficient strategy for mitigating Cd contamination in rice. This study provides critical theoretical support for developing efficient and environmentally friendly foliar barrier technologies and supports safe production of rice in lightly to moderately contaminated paddy fields. Full article