Search Results (1,443)

This study aimed to determine the optimal biochar application rate for sustaining cotton productivity in moderately saline soils under dry sowing with wet emergence (DSWE) conditions in Shaya County, Xinjiang. A two-year field experiment, arranged in a randomized complete block design with two replicates, evaluated six biochar application rates (S1–S6) against a non-amended control (CK). The biochar, derived from fruit-wood via limited-oxygen pyrolysis at 500 °C (pH 9.82, porosity 64.5%), was applied as a single pre-sowing amendment. Soil water–salt dynamics, crop emergence, and growth parameters were continuously monitored. The results indicated that biochar application consistently reduced soil salinity; specifically, seedling-stage salinity decreased by 30.1–42.2% in the first year compared with the CK. Cotton emergence and yield improved significantly across both seasons. However, the optimal application rate for maximizing yield varied between years. While a high rate (S5: 25 t·hm⁻²) produced the highest first-year yield (6243.8 kg·hm⁻²), a moderate rate (S3: 15 t·hm⁻²) demonstrated greater yield stability and achieved the maximum yield (5975.2 kg·hm⁻²) in the second year. This interannual shift is likely attributable to biochar aging and structural pore saturation in the high-dose plots. Combined with high regional evaporation, these factors exacerbated secondary salinization and reduced the residual benefits of the amendment over time. In contrast, the moderate dose maintained a more effective balance between continuous water–salt regulation and nutrient availability. Under the experimental conditions, a single pre-sowing application of 15 t·hm⁻² biochar, combined with a 375 m³·hm⁻² drip irrigation volume, is recommended as an effective strategy to ameliorate salinity and support long-term yield stability. Full article

Blind image watermarking models such as HiDDeN have laid an important foundation for end-to-end watermarking. Nevertheless, they still suffer from three major limitations: single-scale feature extraction, fixed fusion weights, and slow training convergence. To address these issues, this paper proposes an adaptive multi-scale watermarking algorithm based on collaborative dual-attention mechanisms. The algorithm designs an adaptive multi-scale feature fusion module (MA-FFM) with a dynamic gating network in the encoder, which flexibly combines local multi-scale textures with global contextual information, overcoming the limitation of fixed fusion weights. In the decoder, a multi-level channel attention module is embedded to strengthen the extraction of watermark signals. The two attention modules work synergistically: the encoder focuses on adaptive feature fusion while the decoder leverages channel attention to selectively enhance watermark-related features, forming a dual-attention synergy that balances robustness and imperceptibility. Moreover, the dynamic gating network adaptively adjusts the contribution of local versus global features via learnable weights, whose evolution from approximately 0.51 to about 0.89 improves model interpretability. Experiments are conducted on the COCO 2017 dataset. Compared with HiDDeN, the proposed algorithm reduces the bit error rate (BER) from 0.1696 to 0.1538 under no attack with a relative reduction of 9.3%, increases PSNR by 0.61 dB, and improves SSIM from 0.9058 to 0.9077. Under various attacks—including JPEG compression, Gaussian noise, salt-and-pepper noise, and brightness/contrast adjustments—the BER remains consistently lower than that of HiDDeN. Ablation studies confirm the effectiveness of each module. Overall, the proposed algorithm preserves visual quality, improves the accuracy of watermark embedding and extraction, and exhibits strong generalization robustness against common image distortions. Full article

Carbon capture, utilization, and storage (CCUS) is critical for carbon neutrality, and deep saline aquifers are promising reservoirs for CO₂ sequestration. CO₂ diffusion in brine directly affects dissolution trapping efficiency and is strongly influenced by salt ions. Molecular dynamics simulations were employed to investigate CO₂ diffusion in NaCl brines under varying concentrations (0.1–5.0 mol/L), temperatures (298–353 K), and pressures (3–40 MPa). Diffusion coefficients were derived from mean square displacement, and radial distribution functions combined with hydrogen bond analysis were used to elucidate microscopic mechanisms. Results show that as NaCl concentration increases from 0.1 to 5.0 mol/L, the diffusion coefficient decreases by ~50%, reflecting the kinetic consequence of the salting-out effect. Raising temperature from 298 to 353 K enhances diffusion by ~149%, following Arrhenius behavior, while pressure shows negligible influence below 30 MPa but causes a 15% drop at 40 MPa. RDF analysis reveals that higher salinity densifies the CO₂ hydration shell without changing its coordination number, and ions do not accumulate near CO₂. Hydrogen bond analysis indicates that slower diffusion arises primarily from increased viscosity and steric hindrance from hydrated ions rather than disruption of hydrogen bonds. These molecular-level insights can guide site selection and injection strategy optimization for CO₂ geological storage in saline aquifers. Full article

Polyampholyte (PA) hydrogels have attracted considerable attention due to their unique dynamic network structures and favorable biocompatibility. However, their low modulus severely limits applications in load-bearing aspects. Herein, we report ultrastiff PA nanocomposite hydrogels through the synergistic strategy of effective aggregation of hydrophilic silica (SiO₂) nanoparticles and multi-bond networks. Specifically, a high content of SiO₂ nanoparticles is first incorporated into a dynamic ionic PA network via in situ polymerization. The resulting hydrogel is subsequently dialyzed in a zirconium salt solution with strong coordination capability, achieving the ultrastiff nanocomposite hydrogel. In this strategy, the dynamic PA network infiltrated between the aggregated SiO₂ nanoparticles enables effective particle aggregation, while the dynamic PA network, consisting of ionic and metal-coordination bonds, provides efficient energy dissipation, resulting in a synergistic reinforcement effect. The effects of dialysis time, concentration of zirconium salt, and particle content on the swelling and mechanical behaviors of the hydrogels are systematically investigated. The optimized nanocomposite hydrogel exhibits a Young’s modulus and a tensile strength as high as 87.9 ± 5.9 MPa and 7.9 ± 0.1 MPa, respectively, which are 976 and 8.8 times those of the original neat PA hydrogel. This work provides an effective strategy for designing hydrogels with ultrahigh mechanical performance. Full article

Global climate change and soil salinization pose challenges to licorice cultivation. Evaluating seed vigor based on the dynamic changes in radicle morphology is crucial for screening and cultivating licorice varieties that are tolerant to low temperatures and salts. Traditional manual measurement of licorice radicle characteristics suffers from issues such as high cost, long time consumption, and large errors. The YOLOv11 instance segmentation model in the field of deep learning offers advantages including a simple architecture, strong lightweight properties, and a unified detection-segmentation framework. Therefore, this study selected the YOLOv11 model to build a deep learning framework and used the continuous time-series crop growth vitality monitoring system to collect full-time-series images of 18 groups of licorice seeds germinating under different temperature and salt stress conditions. The YOLOv11-seg model was improved by adding a Spatial Strip Attention mechanism (SSA) to enhance the spatial correlation of radicle features, replacing ordinary convolutions with a Multi-scale Edge Detail Enhancement Module (MEEM) to optimize multi-scale feature extraction capabilities, and embedding a Normalized Weighted Distance (NWD) loss function to strengthen the segmentation ability for tiny targets. The YOLOv11-LicoSeg model was constructed for segmenting and extracting licorice radicle features and calculating root length. The experimental results showed that the mAP50 of the model’s detection reached 97.4%, mAP50–95 reached 81.7%, the mAP50 of the segmentation mask reached 97.0%, and mAP50–95 reached 78.2%. Compared with the unimproved YOLOv11-seg, the mAP50 of detection increased by 0.7%, mAP50–95 increased by 1.3%, the mAP50 of segmentation increased by 0.7%, and mAP50–95 increased by 0.8%. The linear regression coefficient between manual measurement and machine-vision measurement was 0.94218, and the goodness of fit R² was 0.94408. Using this model and the monitoring system, the morphological evolution of the licorice radicle contour characteristics over the germination time was obtained. The study indicated that the growth of licorice radicles was optimal under salt stress of 1200 µs/cm and 1800 µs/cm. YOLOv11-LicoSeg accurately segmented licorice radicles and calculated radicle length, with the performance to segment 100 licorice radicle images within 7 s. After deployment, it significantly reduced the labor cost and time consumption for acquiring licorice radicle phenotypes. In conclusion, YOLOv11-LicoSeg provides a rapid and accurate method for variety screening in licorice breeding and cultivation. Full article

Traditional Chinese sticky rice–lime mortar, a key material for restoring historic masonry buildings, suffers significant degradation under combined salt erosion and freeze–thaw cycling. This study experimentally investigated the coupled effects of chloride, sulfate, and freeze–thaw action on sticky rice–lime mortar under simulated service conditions. Specimens prepared using traditional methods were subjected to freeze–thaw cycling in pure water, 5% Na₂SO₄ solution, 5% NaCl solution, and 5% NaCl + 5% Na₂SO₄ solution. Their mechanical properties, phase compositions, and pore structures were characterized through compressive, dynamic elastic modulus, X-ray diffraction (XRD), and mercury intrusion porosimetry (MIP) tests. After six freeze–thaw cycles, the relative dynamic elastic modulus (0.72, 0.58, 0.57, 0.55), mass loss (1.7%, 3.69%, 4.82%, 5.60%), and compressive strength loss (30.05%, 43.90%, 47.56%, 52.43%) progressively worsened from pure water to Na₂SO₄ to NaCl to compound salt conditions, indicating that under the same concentration, the deterioration induced by sodium chloride freeze–thaw is more severe than that caused by sodium sulfate, while the compound salt freeze–thaw condition leads to the most severe deterioration. Under compound salt freeze–thaw, the deterioration mechanisms include expansion due to gypsum formation, salt crystallization, ice formation, and the dissolution of cementitious phases driven by CaCl₂ attack. Furthermore, clear correlations are observed among the mass loss rate, compressive strength loss rate, and relative dynamic elastic modulus, as well as between the peak strain and secant modulus. These findings provide valuable insights for improving the durability of historic restoration mortars. Full article

Wheat (Triticum aestivum L.), a key grain food crop worldwide, faces increasing threats from combined abiotic stresses exacerbated by climate change. However, the comprehensive effects of drought, salinity, and high-temperature pressure on wheat seedlings remain poorly understood. Using the cultivar “Yannong 1212”, we conducted hydroponic experiments to investigate the physiological, morphological, antioxidant, osmoregulatory, membrane lipid peroxidation, and molecular responses of wheat seedlings to single and combined stresses, and then conducted multivariate statistical analyses. The results showed that drought or salt stress inhibited seed germination in a concentration-dependent manner. However, the combined stresses significantly inhibited germination and seedling growth, leading to leaf chlorosis, chlorophyll degradation, stomatal closure, and chloroplast damage. Physiologically, the combined effect of multiple stresses induced excessive ROS and MDA accumulation, promoted proline and soluble sugar synthesis, and triggered the dynamic responses of antioxidant enzymes. Drought stress increased SOD, POD, and CAT activities, whereas salt stress had the opposite effect, and combined stresses further increased SOD and POD activities, but reduced CAT activity. Additionally, stress-responsive genes were rapidly upregulated. Multivariate analyses confirmed that the combined stress of drought and heat was the most damaging. These findings explain the synergistic damage mechanisms of combined stresses, providing a theoretical basis for genetic improvement of wheat’s stress tolerance. Full article

Salinity is a dominant ecological driver shaping microbial community structure and function in hypersaline environments. Here, we investigated transcriptional responses to rapid salinity fluctuations using metatranscriptomic analyses of an intermediate-salinity brine sample from the Santa Pola solar salterns (Alicante, Spain). To this end, two experimental conditions were applied: salinity increase (12.4% to 17%) and salinity dilution (12.4% to 7%). Differential gene expression, functional enrichment, and protein isoelectric point (pI) distributions were analyzed to characterize osmoadaptive mechanisms. Salinity increase triggered a stress-dominated response characterized by upregulation of compatible solute biosynthesis (e.g., glycine betaine and ectoine), protein turnover, and chaperone activity, alongside repression of translation, energy metabolism, and transport systems. In contrast, salinity dilution induced metabolic reactivation, including enhanced translation, energy production, and osmolyte degradation pathways, indicating recovery from osmotic stress. Functional shifts were accompanied by changes in proteome physicochemical properties, with increased salinity promoting a shift toward higher pI proteins, consistent with salt-out strategies. These findings reveal a highly dynamic and asymmetric transcriptional plasticity, where osmotic upshift imposes stronger constraints than downshift, driving coordinated metabolic reprogramming and proteome restructuring in intermediate-salinity microbial communities. Full article

Water management in high-temperature and high-salinity reservoirs remains a critical challenge for oilfield operations, with conventional polymer gel systems exhibiting insufficient thermal stability and salt tolerance under extreme conditions. Here, we establish an integrated computational–experimental platform combining density functional theory (DFT) and molecular dynamics (MD) simulations to rationally design a novel AM/AMPS/AMB (Acrylamide/2-acrylamido-2-methylpropanesulfonic acid/sodium 3-acrylamido-3-methylbutanoate) terpolymer gel plugging agent tailored for the Tahe Oilfield (140 °C, Ca²⁺/Mg²⁺ 10,000 mg L⁻¹). Density functional theory (DFT) calculations of fourteen functional monomers identified AMB as the optimal candidate, achieving further hydrogen bond interactions that stabilize the crosslinked architecture under extreme conditions. This computational pre-screening reduced experimental iterations by over 60% and significantly shortened development cycles compared to conventional trial-and-error approaches. Experimentally, the optimized terpolymer exhibited a 40% increase in storage modulus (150 Pa) relative to AM/AMPS binary systems, 25% improvement in thermal stability (residual carbon at 300 °C), and plugging efficiency exceeding 92% in core flooding tests. Full article

Salinity stress progressively restricts rapeseed (Brassica napus L.) growth and productivity. However, the molecular mechanism underlying its tolerance remains poorly understood. This study aims to shed light on differential responses between shoots and roots, and further clarify the regulatory mechanisms of ion homeostasis and oxidative defense under early-and long-term salt stress. Under salt stress, the Na⁺/K⁺ ratio increased by 46.26% and 26.33% in shoots and roots, respectively. Activities of SOD and POD increased in both tissues, while CAT activity declined in shoots. MDA content was significantly higher in roots. Transcriptome PCA clearly separated samples of early-term (3–48 h for shoots, 3–24 h for roots) from long-term (72 h 25 d for shoots, 48 h 25 d for roots) salt stress. SOD2 and UGT72E1 were significantly up-regulated in shoots but down-regulated in roots. CAT2 exhibited strongly up-regulation in roots than shoots, whereas RBOHC was markedly down-regulated in roots relative to shoots. Additionally, CAT1 was mainly up-regulated at the early-term salt stress. Most DEGs involved in phenylpropanoid biosynthesis (CYP73A5, PAL2, CCR1/2, CAD1/5, COMT1 and PER66) were up-regulated in both tissues. Notably, HCT and CSE exhibited a striking tissue-specific antioxidant pattern, down-regulated in shoots but up-regulated in roots. PER34 was specifically induced at early-term, and PER31/63/169 were exclusively activated under long-term salt stress in roots. Moreover, we performed weighted gene co-expression network analysis (WGCNA) to describe tissue- and time-specific transcriptional dynamics that occur in rapeseed under salt stress. Several hub genes, including ABI5, MPK6, CAD5, NADK1 and LFG2, exhibited high correlations with early-term salt stress responses in roots. These genes are mainly enriched in transcription factors and hormone signaling pathways, and function in antioxidant defense and redox homeostasis. This study suggests distinct spatiotemporal salt stress response patterns in rapeseed and identifies key genes for salt-tolerance breeding. Full article

Arid and semi-arid shelterbelts must provide long-term ecological protection under chronic water scarcity, high evaporative demand, and rising salinization risk, yet management still lacks an integrated framework linking irrigation, root-zone salt dynamics, and woody plant performance. Here, we synthesize evidence on water–salt–root linkages in drip-irrigated shelterbelts and related dryland woody systems from a structured Web of Science Core Collection search (1 January 2000–1 January 2026). The evidence shows that shelterbelt performance is governed not by water or salinity alone, but by a coupled root-zone system: localized irrigation creates moisture–salt heterogeneity, salts accumulate near evaporative fronts and emitter margins, and roots redistribute depth, density, and uptake zones. In hyper-arid saline-drip systems, precipitation may be only ~24.6 to <50 mm yr⁻¹, evaporation > 3000–3639 mm yr⁻¹, groundwater salinity 2.8–29.7 g L⁻¹, active roots 20–80 cm, and salt mainly in the 0–20 cm surface layer. Irrigation thus acts as both the basis of establishment and a source of long-term vulnerability, particularly where saline groundwater or other non-conventional water sources are used. Management options can improve root-zone habitability, but shelterbelt-specific thresholds and integrated indicators remain limited. This review proposes a root-zone-centered framework supporting predictive regulation. Full article

Liquid–liquid phase separation (LLPS) of RNA drives the formation of membraneless organelles, and its dysregulation is closely linked to major human diseases, including cancer, neurodegenerative disorders, and various rare genetic diseases. Current strategies for modulating LLPS often require the introduction of exogenous molecules or specific genetic modifications. Here, coarse-grained molecular dynamics (CGMD) simulations suggest that terahertz (THz) oscillatory fields may influence the condensation of pathogenic G4C2 RNA repeats under the simulated conditions. Oscillatory fields at 10 THz and 37.3 THz are shown to effectively counteract salt-induced condensate dissolution. At the molecular level, THz oscillatory fields are associated with reduced phosphate–sodium contacts at low ionic strengths and with faster water diffusion in the hydration layer at higher salt levels. These changes correlate with an increase in stable intermolecular contacts and a more compact RNA state, suggesting a field-driven shift in the balance of interactions. These findings provide a conceptual and mechanistic basis for understanding how oscillatory fields may influence biomolecular condensation, establishing a microscopic framework for using external variable fields to manipulate biomolecular assemblies. Full article

This study investigated the stage-dependent effects of salt, nitrite, heat treatment, and water activity (aW) on physicochemical and microbiological parameters during fermented meat manufacture. Eight formulations representing a fractional subset of a 2 × 2 × 3 × 2 factorial design were evaluated across four processing stages (pre-fermentation, post-fermentation, post-heat treatment, and post-drying). A stage-resolved multivariate analysis of variance (MANOVA) framework was applied, followed by univariate testing with Benjamini–Hochberg false discovery rate (FDR) correction. Results demonstrated that hurdle effects were strongly stage dependent. Nitrite and its interaction with salt were associated with early stage microbial variation (η² ≤ 0.72), while heat treatment was the dominant factor influencing microbial reduction at the post-processing stage. Notably, short high-temperature heat treatments were most effective at microbial reduction, followed by longer lower-temperature heat treatments, with the intermediate treatment being the least effective, indicating that equivalent time–temperature combinations did not yield equivalent microbiological outcomes. At the final stage, salt and nitrite were associated with compositional, microbial, and quality-related parameters, while aW influenced product structure and concentration effects but was not retained as an independent factor in the multivariate model. These findings indicate that hurdle effects evolve throughout processing and should be considered within a dynamic, stage-specific framework. The results provide a basis for the development of integrated reformulation strategies to reduce salt and nitrite levels while maintaining microbial stability and product quality. Full article

Aquaculture ponds and salt pans represent the dominant forms of coastal production spaces along the Jiangsu coast, China; however, their long-term co-evolution and mutual transitions remain poorly understood. To bridge this gap, this study developed a 40-year (1985–2025) spatiotemporal dataset of these land covers leveraging Landsat imagery via the Google Earth Engine (GEE) platform. We established an integrated classification workflow encompassing single-scene water mask extraction, annual Modified Normalized Difference Water Index (MNDWI)-based water frequency statistics, Otsu automatic thresholding, connected-component labeling, and the masking of natural water bodies. The resulting dataset demonstrated high reliability, achieving overall accuracies (OA) ranging from 92.32% to 94.15% and an average Kappa coefficient of 0.89. Based on multi-metric analyses of area dynamics, annual change rates, and transition patterns, we identified three distinct co-evolutionary stages: simultaneous expansion (1985–1995), internal reorganization (1995–2015), and overall contraction (2015–2025). Notably, transitions between the two production spaces were highly asymmetric over the 40-year period; the area converted from salt pans to aquaculture ponds was approximately 15.23 times greater than the reverse conversion. Furthermore, their distribution exhibited strong spatial heterogeneity at the county level, underscoring the critical role of localized coastal planning in balancing economic production and wetland conservation. Ultimately, this work provides foundational data and methodological insights for long-term coastal ecological monitoring and sustainable production space management. Full article

This study develops an integrated framework combining emergy analysis, carbon footprint accounting, and long short-term memory neural network modeling to investigate the effects of nature-based solutions on coastal ecosystem services and blue carbon functions from the perspective of river–coast connectivity. Three transects along a connectivity gradient were established in the Yellow River Delta, a typical large river delta in temperate China, covering riparian zones, estuarine transition areas, intertidal wetlands, and seagrass beds, with multi-source data collected over three consecutive hydrological years. Emergy–carbon coupling analysis based on this case study indicates that the high-connectivity transect shows a higher emergy yield ratio and net carbon sink compared to the low-connectivity transect, with salt marshes being most sensitive to connectivity change. Threshold analysis, specific to this delta, identifies a three-phase response pattern of carbon burial rate with increasing sediment connectivity, and reveals that wave attenuation efficiency declines notably when hydrological connectivity falls below approximately 0.5, although this value may vary across different coastal settings. A higher sea level rise rate raises the critical connectivity level required to maintain carbon sink function. The long short-term memory neural network trained on observational data achieves better prediction accuracy for blue carbon accumulation rates than traditional statistical methods, and SHAP value analysis suggests the possible existence of synergistic effects among connectivity dimensions. Based on these findings, three optimization strategies including tiered restoration, a dynamic pathway, and spatial configuration are proposed as case-specific recommendations for the Yellow River Delta. Framework-based simulations indicate the potential for connectivity-informed strategy adjustments to improve restoration efficiency under local conditions. This study concludes that river–coast connectivity represents an important lever regulating the ecological benefits of nature-based solutions, but emphasizes that all quantitative thresholds and benefit magnitudes reported here are case-specific estimates that require recalibration when applied to other coastal systems. Full article