Search Results (6,888)

Grassland degradation, exacerbated by climate change and anthropogenic disturbances, poses a substantial barrier to ecological restoration, largely due to the invasion of toxic weeds. In the degraded grasslands of the Ili River Valley, Xinjiang, Sophora alopecuroides has emerged as the dominant toxic species; yet, its expansion mechanisms and sensitivity to management interventions remain poorly understood. This study utilized a three-year (2023–2025) field experiment to evaluate the impacts of nitrogen addition (N), mowing (M), and their combination (NM) on the stoichiometric characteristics and homeostasis of the plant–soil system. The results demonstrated that while M suppressed aboveground biomass, it facilitated the accumulation of root carbon (RC) and phosphorus (RP). Nitrogen enrichment significantly lowered soil C:N and C:P ratios, thereby alleviating phosphorus limitation. Crucially, the NM treatment effectively counteracted N-induced weed proliferation and mitigated M-induced biomass reductions. Analysis of stoichiometric homeostasis revealed that NM optimized plant adaptive strategies, maintaining strict homeostasis for RC and RP (H > 4) while preserving the sensitivity of the root N:P ratio of S. alopecuroides (RN:P). Structural equation modeling further indicated that soil C:P and N:P indirectly regulated total biomass by modulating the root C:P ratio of S. alopecuroides (RC:P). Consequently, stoichiometric coupling within the plant–soil system is essential for maintaining ecosystem functions. Integrated management (NM) optimizes soil nutrient balance and harnesses compensatory growth to suppress weed expansion, providing a robust scientific framework for the restoration of S. alopecuroides-invaded grasslands. Full article

Nitrogen gas is one of the most abundant resources on Earth, serving as a fundamental component in both biological and industrial processes. Nevertheless, this simple molecule can only be activated by a limited group of microorganisms in nature. Significant efforts have been devoted to replicating this biological activity using metalorganic approaches. However, it is becoming increasingly evident that non-covalent interactions, particularly ionic interactions, can further enhance catalytic reactions. In this work, the effect of alkali and alkaline-earth cations on dinitrogen activation was assessed using Density Functional Theory (DFT) at distances ranging from 2 to 10 Å. This analysis revealed three distinct activity regimes. In Case I, the polarization of the N₂ molecule is the primary driving force; in Case II, the polarization effect is less pronounced; and in Case III, electrostatic interactions dominate, enhancing electron delocalization within the N₂–Mⁿ⁺ system. Among the various cations, those belonging to group II-A are particularly noteworthy due to their high ionic potential and polarizing power, with Mg²⁺ standing out for its superior activity at an N₂–Mg²⁺ distance of 2.7 Å. Consequently, these theoretical insights can serve as a guiding strategy for designing efficient N₂-activating complexes that integrate covalent and non-covalent interactions synergistically. Full article

Chili pepper (Capsicum annuum L.) is a globally significant economic crop, however long-term continuous cropping often induces multifaceted constraints including soil nutrient depletion, rhizosphere microbial imbalance, and pathogen accumulation, which collectively exacerbate soil-borne diseases and substantially reduce yield. Incorporating rice (Oryza sativa L.) into rotation increases the diversity of the cultivation environment and represents a cost-effective strategy to mitigate continuous-cropping obstacles. Therefore, evaluating and elucidating the role and underlying mechanisms of the chili pepper–rice rotation system in improving soil conditions and alleviating continuous cropping obstacles in chili pepper holds significant importance. This study conducted a two-year field experiment from 2023 to 2024, setting up chili pepper–rice rotation (RVR) and chili continuous cropping (CCV) treatments, to systematically analyze the effects of chili pepper–rice rotation on chili pepper yield, disease occurrence, soil nutrients, and rhizosphere microbial communities. Across 2023–2024, RVR significantly reduced the incidence of bacterial wilt and root rot, increasing yield by 10.60% in 2023 and by 61.07% in 2024 relative to CCV. Analysis of soil physicochemical properties revealed that RVR significantly promoted the accumulation of available nitrogen, phosphorus, and potassium in the soil, as well as enhanced nutrient-acquisition enzyme activity, effectively alleviating the carbon and phosphorus limitations faced by rhizosphere microorganisms. Rhizosphere microbial analysis indicated that under the RVR treatment, the abundance of pathogen-associated taxa such as Ralstonia and Fusarium significantly decreased. The co-occurrence network modularity increased, and the negative cohesion of pathogens was strengthened, thereby inhibiting pathogen expansion. Further random forest and correlation analyses demonstrated that RVR significantly contributed to yield formation by optimizing fungal metabolic pathways, such as galactose degradation, sulfate reduction, and L-tryptophan degradation. In conclusion, the chili pepper–rice rotation significantly alleviates continuous cropping obstacles and enhances yield by improving nutrient supply and regulating microbial community composition, as well as the topological structure and functional relationships of their co-occurrence networks, particularly by strengthening the role of fungi in community function and metabolic regulation. This study provides a theoretical basis for the biological and soil regulation of pepper continuous cropping obstacles and offers a feasible pathway for sustainable cultivation and green control strategies. Full article

Electrochemical advanced oxidation processes based on peroxymonosulfate (PMS-EAOPs) have shown great promise for eliminating organic pollutants from water. However, earlier research primarily concentrated on pollutant degradation at the cathode, with little attention given to the anode’s role in PMS-EAOPs. In this work, we developed a PMS-EAOP system using nitrogen-doped carbon nanotubes (N-CNTs) as the electrocatalyst and examined the degradation of pollutants (acetamiprid (ATP) and sulfamethoxazole (SMX)) at both the cathode and anode. Our findings indicate that SMX was rapidly degraded at both electrodes, while ATP was effectively broken down only at the cathode, demonstrating the selective nature of PMS-EAOP. At a voltage of −2 V and 2.5 mM PMS, the pseudo-first-order rate constant (k_obs) for ATP at the cathode reached 0.122 min⁻¹, with over 92% removal within 30 min. In contrast, the anode exhibited high selectivity, removing ~75% of SMX (k_obs = 0.041 min⁻¹) while less than 20% of ATP was degraded. Analysis of reactive oxygen species showed that hydroxyl and sulfate radicals were produced and contributed to pollutant degradation at the cathode. In contrast, selective oxidation occurred at the anode, likely driven by direct electrolysis-induced nonradical oxidation responsible for the selective degradation. Phosphates and bicarbonates significantly inhibited the degradation of pollutants in the PMS-EAOP process (31.7–76.4%). In contrast, chloride ions exhibited an electrode-dependent effect, with the anode being less susceptible to interference from common water anions. Overall, this study highlights that while PMS-EAOP can selectively remove contaminants, the influence of water matrix components must be taken into account when treating real wastewater. Full article

The bacterial microbiome in aquaria plays an essential role in system stability by metabolizing toxic compounds like ammonia. This study monitored microbiome changes in seven zoo aquatic systems during their first year to assess responses to external influences. Over one year (October 2021–October 2022), water and swab samples were collected from one seawater tank and six filtration systems at regular intervals. Bacterial cultivation included total bacterial counts. Metagenomic analysis was performed on samples corresponding to environmental events using Oxford Nanopore sequencing. Taxonomical analysis at the phylum and genus levels used EPI2ME software. Diversity analyses and statistical tests were performed using R. Total bacterial counts increased steadily after inoculation and stabilized by the end of the collection period. Diversity analysis revealed significant differences within and between freshwater and saltwater tanks. Each aquarium exhibited a distinct bacterial community with frequent compositional changes. Despite environmental conditions and maintenance interventions and resulting disturbances that affected the microbiome, the overall nitrifying capacity remained unaffected. Nitrifying taxa emerged as potential indicators for environmental effects. Combined with investigations of ecological function, next-generation sequencing could facilitate the development of aquarium management protocols, ultimately improving fish welfare. Full article

Estimating how crop yield responds to site-specific nitrogen (N) fertilization is essential for maximizing yield potential under variable field conditions. However, classical Machine Learning (ML) approaches applied to observational farm data primarily focus on yield prediction and often fail to recover causal N response due to confounding arising from non-random fertilizer application. In this study, we develop and evaluate a Causal Machine Learning (CML) framework to estimate heterogeneous N treatment effects under real commercial rice-farming conditions in the Axios River Plain, Greece. The proposed approach combines Double Machine Learning (DML) with remote sensing, soil, climatic, and management data to adjust for confounding and identify causal relationships between N inputs, Leaf Nitrogen Concentration (LNC), and yield. A doubly robust (DR) learner is used to estimate yield sensitivity to N at key agronomic thresholds, while a Causal Forest model leverages LNC to assess crop physiological N status. Results demonstrate that the CML-based framework outperforms conventional XGBoost predictive models in identifying field plots that are responsive to additional N. By integrating causal effect estimation with plant-status information, the proposed decision support system identifies zones where yield gains can be achieved through targeted N increases while avoiding overfertilization in non-responsive areas. Full article

Critical flicker fusion frequency (CFFF) has been proposed as a rapid marker of central nervous system arousal state, but its relationship to cognitive performance under hyperbaric stress remains unclear. Forty healthy adults (20 women; age 19–46 years) underwent three hyperbaric exposures at 4 ATA (equivalent to 30 m seawater depth) while breathing air, heliox, and trimix in randomized order. CFFF and cognitive performance (Simon task, Digit Span, Corsi Block-Tapping) were assessed before compression, at 4 ATA, and after decompression. Both CFFF and reaction times increased modestly at 4 ATA across all breathing gases (3–5% elevation, p < 0.05). Following decompression, however, these measures showed divergent recovery patterns: CFFF normalized completely after heliox and trimix, but remained partially elevated after air breathing. In contrast, reaction times improved substantially after decompression (10–15% faster than baseline) regardless of breathing gas, reflecting practice effects. Weak correlations emerged between specific CFFF components and executive cognitive measures, while memory performance remained stable throughout all conditions. CFFF and cognitive performance exhibit some parallel increases under hyperbaric stress but most likely capture largely independent aspects of neural function. Breathing gas composition selectively influences CFFF recovery dynamics, with nitrogen producing prolonged neural effects relevant for assessing post-dive cognitive readiness. Full article

The field experiment was carried out in the fields of the Experimental Variety Testing Station in Chrząstów, belonging to the Central Research Centre for Cultivated Plants in Słupia Wielka. The aim of the present study was to determine the effect of residual nitrogen (N_res) remaining in the soil after cultivation of three varieties of common maize fertilized with different types of nitrogen fertilizers on nitrogen-use-efficiency indicators in subsequent crops of winter and spring common wheat. Nitrogen accumulation in both wheat cultivation systems showed a significant response to the interaction between maize varieties and the type of nitrogen fertilizer applied. Urea proved to be the most consistent source of nitrogen in the grain, regardless of the maize variety used as the preceding crop or the form of nitrogen applied. Variability in nitrogen accumulation under the U + N-Lock, Super N-46, and SG Stabilo treatments was primarily associated with a marked decrease in the SC maize variety. The SC + Roots Power maize variety left the soil in a condition highly favourable for nitrogen accumulation in wheat grain across two consecutive growing seasons. Maize variety was the primary factor influencing the proportion of fertilizer-derived nitrogen in the total nitrogen accumulated in the grain. The highest recovery of fertilizer nitrogen over the two-year production cycle was obtained in the SC + Roots Power treatment fertilized with SG Stabilo. Notably, urea demonstrated the strongest residual effect on nitrogen availability to winter wheat. Full article

Understanding how nanocomposite gels regulate pore–throat structures and flow behavior is essential for improving profile control and flow diversion in deep-water tight reservoirs. In this study, a dual-structure-regulated nanocomposite gel (DSRC-NCG) was designed, and its structure–flow coupling behavior during gel injection, curing, and degradation was systematically investigated using multiscale flow configurations, including microfluidic models, artificial cores, and sandpack systems. Microstructural evolution and pore–throat connectivity were characterized using μCT imaging, mercury intrusion porosimetry, nitrogen adsorption, and image-based flow simulations, while macroscopic flow responses were evaluated through permeability variation, dominant-channel evolution, injectivity behavior, and quantitative indices including the structure regulation index (SRI) and pore–flow matching index (HCI). The results show that increasing SiO₂ content induces a progressive optimization of pore–flow matching by refining critical throats and suppressing preferential flow channels, whereas excessive nanoparticle loading leads to aggregation and attenuation of these effects. This study proposes a multiscale structure–flow coupling framework that quantitatively connects pore–throat regulation with macroscopic flow responses during nanocomposite gel injection and degradation. These findings offer mechanistic insights and practical guidance for the design of nanocomposite gels with improved flow-regulation efficiency and reversibility in deep-water tight reservoir applications. Full article

The combined challenges of water scarcity and inefficient nitrogen use pose substantial barriers to sustainable agricultural development. Optimizing the coordinated regulation of water and nitrogen resources in fruit trees is essential for promoting water-saving agriculture in drylands. To establish a water and nitrogen collaborative management model for efficient resource utilization, this study conducted a 3-year field experiment examining different irrigation amount (W1: 4500 m³·ha⁻¹, W2: 6000 m³·ha⁻¹, and W3: 7500 m³·ha⁻¹) and nitrogen application rates (N1: 200 kg·ha⁻¹, N2: 300 kg·ha⁻¹, and N3: 400 kg·ha⁻¹), coupled with ¹⁵N isotopic labeling, to evaluate the impact of water and nitrogen regulation on the following: (i) the spatial distribution patterns of water and nitrogen in the root zone soil, (ii) dynamic characteristics of water and nitrogen across organs, and (iii) ¹⁵N absorption and utilization. The findings revealed that 20–80 cm depth was the key zone for water and nitrogen absorption by roots of pear. The W2 treatment met the optimal irrigation requirement for young pear tree roots and exhibited the optimal dynamic characteristics of water and nitrogen among the newly formed organs. At the end of the growth period, N3 treatment had the highest nitrogen content and the root system was the main organ for nitrogen absorption and storage. Water-saving irrigation coupled with optimized nitrogen application synergistically enhanced the nitrogen accumulation efficiency in fragrant pear. The W2N2 treatment exhibited the highest ¹⁵N absorption and utilization rate (40.79%), effectively promoting nitrogen absorption and assimilation, reducing nitrogen losses, and offering valuable insights for advancing sustainable practices in the fruit and forestry industries. Full article

Inert media such as plastic, ceramic or zeolite are conventionally used for wastewater biofiltration. They all need microbial activation and are essentially chosen for their surface/mass ratio, since biofiltration is entirely performed within the surface biofilm. Using biodegradable media may enhance the sustainability of the system, but it should not produce decomposition-related pollutants. Due to their surface extension, peculiar microbiota and structural resistance, aquatic moss appears to be a very good support for biofilters. Thus, in this study, we evaluated aquatic moss mats as an alternative medium for biofiltration of aquaculture or aquaponic effluents. Two moss species, Taxiphyllum barbieri and Leptodictyum riparium, were tested, also for their contribution on nitrogen metabolism and potential negative effects on hydroponic plants cultivation, due to competition for nutrients. Our proof-of-concept research demonstrates equivalence in real conditions, as inert and moss media exhibited comparable rates; however, the amount of moss required can be several times lower than that of any competing media. Preliminary results suggest the possibility to integrate moss-based biofilters in aquaculture and aquaponics technologies. Full article

Soil salinization is a major threat to agricultural sustainability. Poly-gamma-glutamic acid (γ-PGA), a biopolymer produced by microbial fermentation, has received attention as a biostimulant due to its positive effects on crop performance. However, the function of γ-PGA in crop salt stress tolerance and its effect on the rhizosphere are unclear. This study explores the effects of γ-PGA application on rhizosphere soil nutrients and the soil–physical environment and examines the salt tolerance response of maize seedlings grown in saline–alkali soil under such an application regime. The results show a significant promotion of maize seedling growth and of nutrient accumulation with γ-PGA application under salt stress; plant dry weight, stem diameter, and plant height increased 121%, 39.5%, 18.4%, respectively, and shoot accumulation of nitrogen, phosphorus, potassium, and carbon increased by 1.38, 2.11, 1.50, and 1.36 times, respectively, under an optimal-concentration γ-PGA treatment (5.34 mg kg⁻¹ (12 kg ha⁻¹)) compared with the control. γ-PGA treatment significantly decreased rhizospheric pH and soil electrical conductivity and significantly increased nutrient availability in the rhizosphere, especially available nitrogen (AN) and available potassium (AK). Compared with the control, AN, available phosphorus (AP), and AK increased by 13.9%, 7.70%, and 17.7%, respectively, under an optimal concentration treatment with γ-PGA. γ-PGA application also significantly increased the activities of urease, acid phosphatase, alkaline phosphatase, dehydrogenase, and cellulose in rhizosphere soil by 35.5–39.3%, 35.4–39.3%, 5.59–8.85%, 18.9–19.8%, and 19.2–47.0%, respectively. γ-PGA application significantly decreased Na⁺ concentration and increased K⁺ concentration in shoots, resulting in a lowering of the Na⁺/K⁺ ratio by 30.5% and an increase in soluble sugar and soluble protein contents. Therefore, rhizosphere application of water-soluble and biodegradable γ-PGA facilitates the creation of an optimized rhizospheric environment for maize seedling and overcomes osmotic and ionic stresses, offering possibilities for future use in drip-irrigation systems in the cultivation of crops on saline-alkali land. Full article

Diamond has been extensively examined as an appealing material for use in quantum optics and quantum information processing owing to the existence of various classes of optically active defects, referred to as “color centers,” which can be engineered into its crystal structure. Among these defects, the negatively charged nitrogen-vacancy center (NV⁻) stands out as the most prominent type. Despite the progress made, the number of emitters characterized by reproducible fabrication processes within the desired spectral range at room temperature, with limited or no damage to the parent diamond lattice, remains restricted. Herein, we are proposing for the first time the creation of the FV⁻ center in diamond via low-energy implantation, which is particularly interesting as it possesses characteristic light absorption and magnetic properties similar to NV⁻ centers. The low-energy ion-implanted FV centers in diamond show more desirable optical emission properties at room temperature (RT). Additionally, as per DFT calculations, the flat bands near the Fermi energy indicate dominant electron–electron interactions, an important prerequisite for observing emergent behavior as seen in systems such as twisted bi-layer graphene. Consequently, as-developed new luminescent defects such as Fluorine Vacancy Centers (FV) with desirable spectral and quantum emission properties would be a significant breakthrough in diamond-based quantum materials. Full article

TiO₂ nanoparticles were synthesized by a simple sol–gel route followed by high-temperature calcination at 800 °C, aiming to obtain an anatase-dominant reference photocatalyst with enhanced structural stability after severe thermal treatment. Raman spectroscopy and X-ray diffraction confirmed that anatase is the major crystalline phase, with only a minor rutile contribution after calcination at 800 °C. Nitrogen adsorption–desorption measurements revealed a narrow mesoporous contribution arising from interparticle voids and a relatively high specific surface area (108 m² g⁻¹) despite the severe thermal treatment, while electron microscopy showed nanometric primary particles assembled into compact agglomerates. Surface hydroxyl groups were identified by Fourier-transform infrared spectroscopy, consistent with sol–gel-derived TiO₂ systems. Diffuse reflectance UV–Vis spectroscopy combined with Kubelka–Munk and Tauc analysis yielded an optical band gap of 3.12 eV, typical of anatase TiO₂. Methylene blue (MB) was used as a probe molecule to evaluate photocatalytic activity under ultraviolet and visible light irradiation. Under UV illumination, degradation kinetics were governed by band-gap excitation and reactive oxygen species generation, whereas a slower but reproducible reference behavior under visible light was predominantly associated with surface-related effects and dye sensitization rather than intrinsic visible-light absorption. Overall, the results establish this anatase-dominant TiO₂ as a reliable high-temperature reference photocatalyst, retaining measurable activity after calcination at 800 °C and exhibiting UV-driven behavior as the dominant contribution. Full article

In energy production systems, the higher heating value (HHV), also known as the gross calorific value, is a key parameter for identifying the primary energy source. In this study, a novel artificial intelligence model was developed using support vector machines (SVM) combined with the Differential Evolution (DE) optimizer to predict coal gross calorific value (the dependent variable). The model incorporated the elements from coal ultimate analysis—hydrogen (H), carbon (C), oxygen (O), sulfur (S), and nitrogen (N)—as input variables. For comparison, the experimental data were also fitted to previously reported empirical correlations, as well as Ridge, Lasso, and Elastic-Net regressions. The SVM-based model was first used to assess the influence of all independent variables on coal HHV and was subsequently found to be the most accurate predictor of coal gross calorific value. Specifically, the SVM regression (SVR) achieved a correlation coefficient (r) of 0.9861 and a coefficient of determination (R²) of 0.9575 for coal HHV prediction based on the test samples. The DE/SVM approach demonstrated strong performance, as evidenced by the close agreement between observed and predicted values. Finally, a summary of the results from these analyses is presented. Full article