Search Results (1,556)

The low water and fertiliser utilisation efficiency and soil quality degradation caused by high water and fertiliser inputs are the primary challenges facing goji berry cultivation in arid regions. A two-year field experiment was conducted from 2021 to 2022. The experiment included three irrigation rates (I₁, I₂, I₃) of 2160, 2565, and 2970 m³·hm⁻² and three nitrogen application rates (N₁, N₂, N₃) of 165, 225, and 285 kg·hm⁻² to quantify their impacts on soil nutrients, enzyme activity, and goji berry yield in the root zone. Results indicate that the indicators of soil nutrients decrease with increasing soil depth, with depths of 0–20 cm accounting for 24.80–72.48% of total content. With fertility period progression, soil organic matter at depths of 0–80 cm exhibits a “folded-line” trend, while total nitrogen, nitrate nitrogen, and available phosphorus show an “M”-type trend. At depths of 0–40 cm, the proportions of urease, sucrase, and alkaline phosphatase activities all exceeded 70%. At I₁ irrigation rate, enzyme activities gradually increased with rising nitrogen application rates. At I₂ and I₃ irrigation rates, enzyme activities first increased, then decreased with increasing nitrogen application. The highest yields of both fresh and dried fruits were achieved at I₂N₂ treatment, increasing by 14.17% and 14.78%, respectively, compared to conventional management (CK). Analysis of the random forest model indicates that the soil-driven factors influencing yield formation include SA, UA, APA, HPA, SOM, NH₄⁺-N, and TP. Analysis of SQI and yield fitted data indicates that water–nitrogen coupling significantly influences wolfberry yield by regulating soil quality. Partial least squares (PLS-PM) showed that N application and irrigation of soil nutrients did not cause a significant indirect impact on goji berry yield, but a significant positive effect on goji berry yield occurred through enzyme activity. Full article

Circulation type classification (CTC) is an important method in atmospheric sciences, which reveals the relationship between atmospheric circulation and regional weather and climate. Accurate circulation classification helps to improve weather forecasting accuracy and supports climate change research. China has complex topography and significant spatiotemporal variability in its circulation patterns, making the study of circulation type classification in this region highly significant. This study aims to evaluate the applicability of several mainstream objective CTC methods in the China region. We applied methods including T-mode principal component analysis (PCT), Ward linkage, K-means, and Self-Organizing Maps (SOM) to classify the sea-level pressure daily mean fields from 1993 to 2023 in the study area, and compared the classification results in terms of internal metrics, continuity, seasonal variation, separability of related meteorological variables (e.g., temperature, precipitation), and stability to spatiotemporal resolution. The results show that each method has its advantages in different contexts, with the K-means method showing the best overall performance. Additionally, an optimized approach combining PCT and K-means is proposed. Full article

Intensive land use in the Argentine Pampas has led to soil degradation, yet links between soil organic matter (SOM) composition, enzyme activity, and fungal communities remain unclear. This study compared contrasting ecoregions and land uses: pristine (PI), pasture (PA), crop rotation with cover crops (RO), and monoculture (MO). Infrared spectra showed that PI soils in Anguil had higher absorbance in hydroxyl/amine (3400 cm⁻¹: 0.90 ± 0.08) and carbonyl (1750 cm⁻¹: 0.52 ± 0.12) bands than MO soils (0.47 ± 0.30 and 0.35 ± 0.06; p < 0.05), indicating greater SOM diversity. Pergamino soils showed smaller differences, reflecting site-specific effects. Enzyme activities also responded to land use. In Anguil, xylosidase, β-1,4-N-acetylglucosaminidase, and phosphatase peaked under PI (40, 127, and 443 nmol g⁻¹ h⁻¹). In Pergamino, xylosidase and β-1,4-N-acetylglucosaminidase were higher under PA and PI, indicating enhanced microbial functionality under low disturbance. Fungal composition varied with land use and location: Mortierellomycetes dominated in Pergamino, while Leotiomycetes and Agaricomycetes were more abundant in PI and PA, and Dothideomycetes increased in MO and RO. Despite compositional shifts, fungal diversity changed little. Integrating chemical, biochemical, and molecular indicators revealed how land-use intensification modifies SOM and microbial processes in Pampas soils. Full article

Population mobility links cities, propelling the spatiotemporal spread of urban pandemics and adding complexity to disease dynamics. It also closely shapes, and is shaped by, the selection and intensity of intervention measures. Revealing the multistage spatial-temporal dynamics of cross-regional epidemic continuity under this interaction is often overlooked but critically important. This study innovatively applies a self-organizing map (SOM) neural network to classify cities into six distinct types based on population mobility characteristics: high-inflow core (HIC), low-inflow core (LIC), low-inflow sub-core (LISC), high-outflow semi-peripheral (HOSP), equilibrious semi-peripheral (ESP), and low-outflow peripheral (LOP). Building on this, we propose a novel SEIR-AHQ theoretical framework and construct an epidemiological model using network-coupled ordinary differential equations (ODEs). This model captures the dynamic interplay between inter-city population mobility and intervention measures, and quantifies how heterogeneous city types shape the evolution of epidemic transmission across the coupled mobility network. The results show that: (1) Cities with stronger population mobility face significantly higher infection risks and longer epidemic durations, characterized by “higher peaks and longer tails” in infection curves. HIC cities experience the greatest challenges, and LOP cities experience the least. (2) Both higher transmission rates and delayed intervention timings lead to exponential growth in infections, with nonlinear effects amplifying small changes disproportionately. (3) Intervention efficacy follows a “diminishing marginal returns” pattern, where the incremental benefits of increasing intervention intensity gradually decrease. This study offers a novel perspective on managing interregional epidemics, providing actionable insights for crafting tailored and effective epidemic response strategies. Full article

Energy poverty (EP) is a complex socio-economic phenomenon of growing importance in European Union (EU) countries. The level of EP, along with the health of the population and the level of perceived well-being (H&W), is a fundamental element of socioeconomic development and a determinant of the quality of life of individuals and entire societies. In this study, two main research objectives were set: a comparison of country classification results obtained using a classical method (QGIS) and a method based on artificial intelligence (SOM) and assessment of the complementarity of both approaches in studying the diversity of EU countries in terms of EP and H&W. The classification results made it possible to demonstrate changes in the studied phenomena over time. The analysis was carried out using data from the Eurostat database from 2019 and 2023. The results presented in this study indicate that countries with the highest EP levels are located in two distinct regions: Eastern and Southern Europe. Countries with the lowest EP levels are located in Northern and Central Europe. In the case of H&W, higher levels were observed in northern and western European countries, while lower levels were observed in eastern and central European countries. The use of an AI-based method in socio-economic research and the comparison of the results with those obtained using the traditional method provides a more complete picture of the diversity of EU countries in terms of EP and H&W, broadening knowledge in empirical and methodological terms. Full article

Drought poses a severe challenge to ornamental tree growth under climate change. This study employed a 2 × 4 factorial design—with two soil moisture levels (80–85% vs. 50–55% field capacity) and four nitrogen treatments (NN: no nitrogen; NO: nitrate nitrogen; NH: ammonium nitrogen; MN: mixed nitrate-ammonium nitrogen)—to examine the efficacy of nitrogen addition in enhancing drought resistance in Machilus yunnanensis seedlings. Results revealed that (1) drought stress leads to the acidification of rhizosphere soil, resulting in a decrease of 7.67%, 29.51%, 14.07%, and 44.09% in the content of soil organic matter (SOM), available phosphorus (AP), available potassium (AK), and dissolved organic nitrogen (DON), respectively. This adverse change directly impacts plant growth; it is manifested by a significant reduction of 45% in total chlorophyll (T Chl), a 67.18% decrease in photosynthetic rate (Pn), as well as reductions of 10.61%, 27.59%, 14.81%, and 12.35% in plant height, leaf, stem, and total biomass, respectively. (2) The application of all three forms of nitrogen helps alleviate drought stress, as evidenced by the recovery of photosynthetic levels and the reduction in malondialdehyde (MDA) content, with ammonium-N exhibiting superior efficacy over nitrate-N across most metrics. (3) Strikingly, the mixed nitrogen form outperformed singular applications by demonstrating multifaceted advantages: It maintains soil pH levels and rhizosphere nutrient availability under drought conditions, particularly with a 10.99% and 33.44% increase in dissolved organic nitrogen and available phosphorus content, respectively. More importantly, under drought stress, it increased leaf water content by 20.31%, nitrogen use efficiency by 15.67%, and photosynthetic nitrogen use efficiency by 439.44%, promoted the accumulation of osmolytes, while upregulating antioxidant enzyme activity to counteract osmotic imbalance and alleviate oxidative damage. These findings highlight that nitrogen supplementation, particularly mixed nitrogen application, enhances drought resistance in M. yunnanensis, offering a viable management strategy to sustain urban tree landscapes in water-limited environments. Full article

Global amphibian populations are declining rapidly and the development of effective cryopreservation protocols for germ cells has become a critical tool in ex situ conservation programs. Post-thaw membrane-integrity viability in four endangered Korean amphibians (Dryophytes suweonensis, Pelophylax chosenicus, Kaloula borealis, and Hynobius yangi) were evaluated. Sperm were cryopreserved using dimethyl sulfoxide (DMSO) or N,N-dimethylformamide (DMF) at 10–30% (v/v) in combination with 0.6 M sucrose, and were frozen at two suspension heights (5 cm vs. 10 cm) above liquid nitrogen. Post-thaw membrane-integrity viability was assessed using a SYBR-14/propidium iodide membrane-integrity assay (LIVE/DEAD kit). Low concentrations of permeating cryoprotectants (CPs) improved membrane-integrity viability, whereas high concentrations led to high toxicity, particularly with DMSO. Across species, DMF produced the highest membrane-integrity viability and the most consistent performance. The cooling rate influenced membrane-integrity viability, with samples frozen at 10 cm exhibiting greater viability, reflecting the balance between intracellular ice formation during rapid cooling and solution effects during slow cooling. Optimal conditions for D. suweonensis were 15% DMSO at 10 cm (86.5% membrane-integrity viability); for P. chosenicus, 10% DMF at 10 cm (75.5%); and for K. borealis, 10% DMSO at 5 cm (81.6% membrane-integrity viability). Hynobius yangi showed modest improvement under 15% DMF at 5 cm (19.7%), although overall membrane-integrity viability was low. ED₅₀ modeling indicated species-specific thresholds requiring low CP concentrations. Sperm cryopreservation outcomes in amphibians are strongly influenced by CP type, concentration, cooling regime, and species physiology. GLM and ED₅₀ modeling provide a methodological framework for refining cryopreservation strategies for non-model, endangered species. Full article

Soil organic matter (SOM) is a key component of nutrient cycling and soil fertility in terrestrial ecosystems. SOM is of great significance to the stability of terrestrial ecosystems and the improvement of soil productivity; to further exert its role, it is first necessary to clarify its actual distribution and occurrence status in specific regions. Under the combined impacts of intensive agriculture, unreasonable farming practices, and climate change, the SOM content in the Songnen Plain is showing a degradation trend, posing multiple stresses on its soil ecosystem functions. This study aims to systematically track the dynamic changes of SOM in the Songnen Plain, assess its spatiotemporal evolution characteristics, and reveal its driving mechanisms. A total of 113 representative soil profiles were selected in 2023; standardized excavation and sampling procedures were employed in the Songnen Plain. Soil pH, SOM, total nitrogen (TN), total phosphorus (TP), total potassium (TK), particle size (PSD), texture, and Munsell soil colors of samples were determined. Temporal variation characteristics, as well as horizontal and vertical spatial distribution patterns, in SOM content in the Songnen Plain were assayed. Structural equation modeling (SEM), together with freeze–thaw of soil and soil color mechanism analyses, was applied to reveal the spatiotemporal dynamics and driving mechanisms of SOM. The result indicated that the distribution pattern of SOM content in horizontal space shows higher levels in the northeastern region and lower levels in the southwestern region, and decreased with increasing soil depth. SEM analysis indicated that TN and PSD were the main positive factors, whereas bulk density exerted a dominant negative effect. The ranking of contribution rates is TN > TK > TP > PSD > annual average temperature > annual precipitation > bulk density. Mechanistic analysis revealed a significant negative correlation between SOM content and R, G, B values, with soil color intensity serving as a visual indicator of SOM content. Freeze–thaw thickness of soil was positively correlated with SOM content. These findings provide a scientific basis for soil fertility management and ecological conservation in cold regions. Full article

Landslides are a major natural hazard capable of causing severe damage to infrastructure, ecosystems, and human life. They result from complex interactions of geological, hydrological, and environmental factors, with soil properties playing a crucial role by influencing the mechanical behavior and moisture dynamics of slope materials that drive initiation and progression. In South Africa, few studies have examined soil influences on landslide susceptibility, and none have been conducted in the Eastern Cape Province. This study investigated the role of soil physical and chemical properties in landslide susceptibility by comparing profiles from landslide scars and stable sites in the Port St. Johns and Lusikisiki region. Samples from topsoil and subsoil horizons were analyzed for soil organic matter (SOM), cation exchange capacity (CEC), saturated hydraulic conductivity (Ksat), exchangeable sodium adsorption ratio (SARexc), and texture. Statistical analyses included the Shapiro–Wilk test to evaluate data normality. For inter-profile comparisons, Welch’s t-test was applied to normally distributed data, while the Mann–Whitney U test was used for non-normal distributions. Intra-profile differences across more than two groups were assessed using the Kruskal–Wallis test for the non-normally distributed data. Results showed that landslide-prone soils had higher SOM, CEC, and Ksat in topsoil, promoting moisture retention and rapid infiltration, which favor pore pressure build-up and slope failure. Non-landslide soils displayed higher sodium-related indices and finer textures, suggesting more uniform water retention and resilience. Vertical variation in landslide soils indicated hydraulic discontinuities, fostering perched saturation zones. Findings highlight landslide initiation as a product of interactions between hydromechanical gradients and chemical dynamics. Full article

With the increased demand for wearable sensors, image representations—such as persistence images and Gramian angular fields—transformed from time-series data have been investigated to address challenges in wearables arising from physiological variations, sensor noise, and limitations in capturing contextual information. To preserve the lightweight structural design of models, knowledge distillation (KD) has also been employed alongside image representations during training to distill smaller and more efficient models. Although image representations play a key role in providing richer and more informative features in training a model, their effectiveness within the KD framework has not been thoroughly explored. In this paper, we focus on image representation-driven KD to investigate whether these representations can provide useful knowledge leading to improved time-series interpretation in activity classification tasks. We explore the benefits of integrating image representations into KD, and we analyze the interplay between representation richness and model compactness with different combinations of teacher and student networks. We also introduce diverse KD strategies to utilize image representations, and we demonstrate the strategies with various perspectives, such as analysis of noises, generalizability, and compatibility, across datasets of varying scales to obtain comprehensive and insightful observations. These offer valuable insights for designing efficient and high-performance wearable sensor-based systems. Full article

The quality of groundwater, a crucial freshwater resource in cold regions, directly affects human health. This study used groundwater quality monitoring data collected in the central Songnen Plain in 2014 and 2022 as a case study. The improved DRASTICL model was used to assess the vulnerability index, while water quality indicators were selected using a random forest algorithm and combined with the entropy-weighted groundwater quality index (E-GQI) approach to realize water quality assessment. Furthermore, self-organizing maps (SOM) were used for pollutant source analysis. Finally, the study identified the synergistic migration mechanism of NH₄⁺ and Cl⁻, as well as the activation trend of As in reducing environments. The uncertainty inherent to health risk assessment was considered by developing a kernel density estimation–trapezoidal fuzzy number–Monte Carlo simulation (KDE-TFN-MCSS) model that reduced the distribution mis-specification risks and high-risk misjudgment rates associated with conventional assessment methods. The results indicated that: (1) The water chemistry type in the study area was predominantly HCO₃⁻–Ca²⁺ with moderately to weakly alkaline water, and the primary and nitrogen pollution indicators were elevated, with the average NH₄⁺ concentration significantly increasing from 0.06 mg/L in 2014 to 1.26 mg/L in 2022, exceeding the Class III limit of 1.0 mg/L. (2) The groundwater quality in the central Songnen Plain was poor in 2014, comprising predominantly Classes IV and V; by 2022, it comprised mostly Classes I–IV following a banded distribution, but declined in some central and northern areas. (3) The results of the SOM analysis revealed that the principal hardness component shifted from Ca²⁺ in 2014 to Ca²⁺–Mg²⁺ synergy in 2022. Local high values of As and NH₄⁺ were determined to reflect geogenic origin and diffuse agricultural pollution, whereas the Cl⁻ distribution reflected the influence of de-icing agents and urbanization. (4) Through drinking water exposure, a deterministic evaluation conducted using the conventional four-step method indicated that the non-carcinogenic risk (HI) in the central and eastern areas significantly exceeded the threshold (HI > 1) in 2014, with the high-HI area expanding westward to the central and western regions in 2022; local areas in the north also exhibited carcinogenic risk (CR) values exceeding the threshold (CR > 0.0001). The results of a probabilistic evaluation conducted using the proposed simulation model indicated that, except for children’s CR in 2022, both HI and CR exceeded acceptable thresholds with 95% probability. Therefore, the proposed assessment method can provide a basis for improved groundwater pollution zoning and control decisions in cold regions. Full article

Saline–alkali soils represent a significant reserve of arable land, playing a vital role in ensuring national food security. Given that saline–alkali soil has low soil organic matter (SOM) and soil nutrient contents, and that soil quality degradation poses a threat to regional high-quality agricultural development and ecological balance, this study took coastal saline–alkali land as a case study. It adopted the extreme gradient boosting (XGB) model optimized by the tree-structured Parzen estimator (TPE) algorithm, combined with in situ hyperspectral (ISH) and spaceborne hyperspectral (SBH) data, to predict and map soil organic matter and four soil nutrients: alkali nitrogen (AN), available phosphorus (AP), and available potassium (AK). From the research outputs, one can deduce that superior predictive efficacy is exhibited by the TPE-XGB construct, employing in situ hyperspectral datasets. Among these, available phosphorus (R² = 0.67) exhibits the highest prediction accuracy, followed by organic matter (R² = 0.65), alkali-hydrolyzable nitrogen (R² = 0.56), and available potassium (R² = 0.51). In addition, the spatial continuity mapping results based on spaceborne hyperspectral data show that SOM, AN, AP, and AK in soil nutrients in the study area are concentrated in the northern, eastern, southern, and riverbank and estuarine delta areas, respectively. The variability of soil nutrients from large to small is phosphorus, potassium, nitrogen, and organic matter. The SHAP (SHapley Additive exPlanations) analysis results reveal that the bands with the greatest contribution to the fitting of SOM, AN, AP, and AK are 612 nm, 571 nm, 1493 nm, and 1308 nm, respectively. Extending into realms of hierarchical partitioning (HP) and variation partitioning (VP), it is discerned that climatic factors (CLI) alongside vegetative aspects (VEG) wield dominant influence upon the spatial differentiation manifest in nutrients. Meanwhile, comparatively diminished are the contributions possessed by terrain (TER) and soil property (SOIL). In summary, this study effectively assessed the significant variation patterns of soil nutrient distribution in coastal saline–alkali soils using the TPE-XGB model, providing scientific basis for the sustainable advancement of agricultural development in saline–alkali coastal regions. Full article

Keystone species play a critical role in sustaining ecosystem structure and function. Thus, accurately identifying keystone species is essential for effective biodiversity conservation. This study investigates the benthic ecosystem of Yanpu Bay’s mangroves, utilizing stable isotope analysis in combination with Bayesian mixture models and ecological network analysis to characterize trophic relationships and topological network structures, with the aim of identifying keystone species within the community. The benthic food web in this study comprised 96 connections and 27 nodes. Among them, Scartelaos histophorus preyed on eight benthos species, constituting 18.51% of the total prey sources in food web. Sedimentary organic matter (SOM) was identified as a critical food source, sustaining 17 consumer species, 62.96% of the total species recorded in the community. Quantitative analysis using criticality indices and key player problem indices identified Cerithidea cingulate, Littorinopsis scabra, Periophthalmus magnuspinnatus, S. histophorus, Bostrychus sinensis, and Metaplax longipes as keystone species. The identification of these keystone species provides valuable insights for developing targeted biodiversity conservation strategies and offers a robust scientific foundation for the restoration and sustainable management of the mangrove benthic food web. Full article

Traumatic optic neuropathy (TON) causes vision loss through compression and contusion, yet there is no consensus on the most effective treatment. Polyunsaturated fatty acid (PUFA)-derived bioactive lipids metabolized by lipoxygenase (LOX), cytochrome P450 (CYP), and cyclooxygenase (COX) enzymes are known mediators of inflammation and neurodegeneration. However, their role in TON-related retinal pathology remains unclear. Controlled orbital impact (COI) was used to induce unilateral TON in mice with controlled velocity (2–3 m/s), with the fellow eye serving as an internal control. Retina tissues were collected three days post-injury and analyzed by LC/MS to quantify bioactive lipid metabolites from ω−6 and ω−3 PUFAs. Statistical analysis was performed using paired, nonparametric Wilcoxon signed-rank tests with Benjamini–Hochberg false discovery rate (FDR) correction. Results showed that among 38 reliably detected metabolites, no individual lipid showed a statistically significant difference between TON and control eyes after FDR correction (q < 0.05). However, both individual and pathway-level analysis revealed consistent trends toward increased expression of LOX- and CYP-derived metabolites across FDA PUFA substrates, including arachidonic acid (AA), linoleic acid (LA), and docosahexaenoic acid (DHA). These findings support further investigation into lipid-mediated inflammation in TON and its potential as a therapeutic target, particularly through expanding both the sample size and the post-TON time periods. Full article

Increasing attention is being paid to the use of cover crops as a means of improving soil quality, particularly in relation to soil organic matter (SOM) accumulation and aggregate stability. This study evaluated the effects of soil texture, soil depth, and cover crop type on soil organic carbon (Corg), labile carbon (C_L), and soil structure under field conditions in western Slovakia. A field experiment compared two texturally distinct Phaeozem soils—silty clay loam and sandy loam —and two cover cropping strategies: pea (Pisum sativum L.) monoculture and a four-species mixture of flax (Linum usitatissimum L.), camelina (Camelina sativa L.), white mustard (Sinapis alba L.), and Italian millet (Setaria italica L.). Fine-textured soil accumulated up to 50% more Corg and 1.5 times more C_L than sandy soil, while aggregate stability was up to 90% higher. The surface layer (0–10 cm) contained more SOM, but the deeper layer (10–20 cm) showed greater aggregate stability. Pea cultivation increased total organic carbon, whereas the diverse mixture enhanced labile carbon content and promoted the formation of smaller yet more stable aggregates. Strong correlations between C_L and aggregate stability confirmed the key role of labile organic matter fractions in soil structural stabilisation. Overall, the results demonstrate that the interaction between soil texture and cover crop diversity critically shapes SOM dynamics and soil structure. Combining diverse cover crops with fine-textured soils provides an effective strategy to enhance soil quality, carbon sequestration, and long-term agricultural sustainability. Full article