天水师范学院

Context: The Loess Plateau region faces severe soil degradation with organic carbon content typically below 1.2 %, substantially lower than the 2 % threshold for optimal soil function. Balancing soil carbon sequestration with agricultural productivity remains a critical challenge for sustainable intensification in these degraded dryland soils. Objective: This study aimed to determine whether optimized organic-inorganic fertilization could simultaneously enhance soil organic carbon sequestration and wheat productivity, and to elucidate the underlying mechanisms of carbon pool dynamics and nutrient cycling. Methods: A randomized complete block experiment with five treatments was established: control (CK), organic fertilizer only (M, 7500 kg/ha sheep manure), chemical fertilizer only (NPK: urea 212 kg/ha, calcium superphosphate 170 kg/ha, potassium sulfate 120 kg/ha), conventional organic-inorganic combination (MNPK, 7500 kg/ha sheep manure plus standard NPK rates), and doubled organic-inorganic combination (2MNPK, 15,000 kg/ha sheep manure plus doubled NPK rates: urea 424 kg/ha, calcium superphosphate 340 kg/ha, potassium sulfate 240 kg/ha). Results and conclusions: Compared to conventional chemical fertilization (NPK), the 2MNPK treatment increased grain yield by 17.2 % (from 3642 to 4268 kg/ha) and total soil organic carbon by 18.1 % (from 11.5 to 13.6 g/kg). Relative to conventional organic-inorganic fertilization (MNPK), 2MNPK enhanced light fraction organic carbon by 25.6 % (from 30.8 to 38.7 g/kg), the most dynamic carbon pool driving carbon sequestration. Compared to control, 2MNPK increased grain yield by 29.8 %, light fraction organic carbon (partially decomposed plant residue carbon) by 69.0 %, and total soil organic carbon by 34.7 %. Microbial biomass carbon and nitrogen increased by 84.2 % and 112.1 % respectively. Available nitrogen, phosphorus, and potassium increased by 106.7 %, 175 %, and 135.3 %. Structural equation modeling revealed fulvic acid carbon as a key mediator promoting light fraction organic carbon formation (beta = 0.70, P < 0.001), which dominated total carbon accumulation. Optimized organic-inorganic fertilization achieved synergistic enhancement of carbon sequestration and crop productivity through improved nutrient cycling, enhanced microbial activity, and hierarchical carbon transformation pathways.

The ultrahigh cooling rates inherent to additive manufacturing (AM) generate high-density dislocation-cellular networks within Inconel 718 superalloy. This study elucidates how these LPBF-specific substructures trigger annealing twin formation and evaluates the thermostability of the resulting twin boundary (TB) network above typical service temperatures. Annealing at 1200 degrees C for 1 h followed by two-stage aging generates a high TB fraction (63.4 %). Recrystallization-boundary migration, driven by stored energy and locally reduced stackingfault energy near dislocation-cell interfaces, produces twins via the growth-accident mechanism. Twin stabilization arises from two coupled effects: (i) intrinsic thermodynamic stability of coherent TBs (CTBs) that show no detectable solute segregation, and (ii) extrinsic Zener pinning from gamma ''/gamma ' precipitates within grains, S-Ni3Nb decorating incoherent TBs and random high-angle grain boundaries, and stable MC carbides. Isothermal exposures between 800 and 1100 degrees C reveal a stability window up to similar to 1000 degrees C with limited grain coarsening; dissolution of gamma ''/gamma '/S above similar to 1000 degrees C weakens pinning, enabling boundary migration and reducing the fraction of TBs. The introduction of high-density twins enhances both strength and ductility at room temperature, whereas subsequent thermal exposure decreases strength but increases elongation due to reduced glide resistance and removal of stress-concentrating precipitates. These results provide an effective pathway for boundary optimization and performance tailoring in additively manufactured Inconel 718 intended for elevatedtemperature service.

The residue of Malachite green (MG) in wastewater poses a severe threat to both health and the environment. To address this challenge, we developed a high-performance ZnCl2-modified cherry stone biochar (ZnBC) as sustainable adsorbent for MG removal. The underlying adsorption mechanism was comprehensively elucidated through a combination of experimental data analysis and molecular-level density functional theory (DFT) calculations. The results indicated that ZnBC exhibited a superior adsorption capacity compared to unmodified biochar (PBC), with a maximum capacity of 347.98 mg/g at 308 K. The specific surface area of ZnBC was exceptionally high (1401.47 m2/g), with a corresponding pore volume of 0.696 cm3/g. These remarkable textural properties are primarily attributed to the etching effect of zinc chloride during high-temperature pyrolysis. This process facilitates rapid volatilization, creating larger cavities. The substantial increase in surface area also exposes more active sites, thereby enhancing adsorption performance. The adsorption isotherms both Langmuir and Freundlich models, suggesting a complex mechanism involving monolayer adsorption on heterogeneous surface, which is attributed to the oxygen-containing functional groups on the biochar. Furthermore, thermodynamic analysis confirmed the process to be spontaneous and exothermic, accompanied by an increase in entropy. DFT calculations corroborated the experimental findings, revealing that MG adsorption involved both pore filling and electrostatic attraction, hydrogen bonding, van der Waals forces, and it-it interactions. For practical application, ZnBC regenerated with 75 % ethanol maintained a relatively high adsorption capacity after six cycles. Moreover, the estimated cost of treating wastewater with this adsorbent (approximately $1.108/ m3) was lower than that of commercial high-quality adsorbents such as activated carbon and carbon nanotubes. In conclusion, ZnBC is not only an efficient and low-cost method for removing organic dyes but also a viable approach for the management and utilization of cherry stone solid waste.

As the importance of public engagement monitoring grows in the face of complex social challenges, analyzing social media data from multiple perspectives has become crucial for understanding diverse public sentiments. Current methods often fall short in effectively supporting decision-making due to their inability to dynamically adapt to the evolving nature of social media discussions. They rely on static strategies that fail to capture the intricate correlations between features across different views, making it difficult to identify sentiment patterns that emerge through complex dependencies in user-generated content. To address these shortcomings, we propose a novel deep multi-view contrastive fusion network (SMOM) designed for comprehensive public opinion monitoring in social media. SMOM features a view-specific feature extractor that captures inherent information within each view. It then employs cross-view contrastive learning to maximize mutual information between view-specific representations, ensuring consistency between views and bridging semantic gaps from an information theory perspective. Furthermore, SMOM implements structure-driven adaptive fusion by combining gate strategies and graph neural networks, enabling the adaptive integration of complementary information. These components work together seamlessly to uncover sentiment patterns, achieving thorough and accurate monitoring of public opinions in social media. Experimental evaluations on social media datasets demonstrate SMOM’s superior performance in detecting nuanced public sentiments.

Zinc-aluminum layered double hydroxide (ZnAl-LDH) was successfully synthesized via a one-step coprecipitation method and directly modified onto a glassy carbon electrode (GCE) to construct a ZnAl-LDH/GCE working electrode. A systematic comparison of MAl-LDH formed from different divalent metal sources (M = Zn2+, Ca2+, Mg2+, Ni2+) revealed that ZnAl-LDH exhibited the most favorable morphology and performance. Despite the inherently poor conductivity of LDH materials, the specific interaction between metal hydroxyl groups (-M-OH) on the ZnAl-LDH surface and Pb2+ significantly enhanced the electrochemical response signal for Pb2+. Optimization of key parameters including supporting electrolyte, pH, enrichment potential, and time established optimal detection conditions at pH = 5.0 in 0.1 mol/L acetic acid-sodium acetate (ABS) buffer, with enrichment at -0.9 V for 230 s. Under these conditions, the electrochemical sensor demonstrated outstanding analytical performance for Pb2+ detection: a linear range of 0.4-25 mu mol/L, a detection limit as low as 0.031 mu mol/L (S/N = 3), along with excellent selectivity, stability, and reproducibility. Satisfactory recovery rates achieved in real-water samples further validate the sensor's practical application potential in environmental monitoring.