Search Results (17,512)

This study employs k-means clustering to group 30 Chinese provinces into four CO${}_2$ emission patterns, characterized by increasing emission levels and distinct energy consumption structures, and captures their dynamic evolution from 2000 to 2021 using a discrete endogenous Markov chain approach. While Shanghai, Jiangxi, and Hebei retained their original classifications, provinces such as Beijing, Fujian, Tianjin, and Anhui transitioned from higher to lower emission patterns, indicating notable reversals in emission trajectories. To identify the determinants of these transitions, GDP growth rate, population growth rate, and energy investment are incorporated as time varying covariates. The empirical findings demonstrate that GDP growth substantially increases interpattern mobility, thereby weakening state persistence, whereas population growth and energy investment tend to reinforce emission pattern stability. These results imply that policy responses must be tailored to regional dynamics. In rapidly growing regions, fiscal incentives and technological upgrading may facilitate downward transitions in emission states, whereas in provinces where emissions remain persistent due to demographic or investment related rigidity, structural adjustments and long term mitigation frameworks are essential. The study underscores the importance of integrating economic, demographic, and investment characteristics into carbon reduction strategies through a region specific and data informed approach. Full article

Cucumbers (Cucumis sativus L.) are highly sensitive to cold, but grafting onto cold-tolerant rootstocks can enhance their low-temperature resilience. This study investigates the physiological and molecular mechanisms by which exogenous vitamin C (Vc) mitigates cold stress in grafted cucumber seedlings. Using cucumber ‘Chiyu 505’ as the scion and pumpkin ‘Chuangfan No.1’ as the rootstock, seedlings were grafted using the whip grafting method. In the third true leaf expansion stage, seedlings were foliar sprayed with Vc at concentrations of 50, 100, 150, and 200 mg L⁻¹. Three days after initial spraying, seedlings were subjected to cold stress (8 °C) for 3 days, with continued spraying. After that, morphological and physiological parameters were assessed. Results showed that 150 mg L⁻¹ Vc treatment was most impactive, significantly reducing the cold damage index while increasing the root-to-shoot ratio, root vitality, chlorophyll content, and activities of antioxidant enzymes (SOD, POD, CAT). Moreover, this treatment enhanced levels of soluble sugars, soluble proteins, and proline compared to control. However, 200 mg L⁻¹ treatment elevated malondialdehyde (MDA) content, indicating potential oxidative stress. For transcriptomic analysis, leaves from the 150 mg L⁻¹ Vc and CK treatments were sampled at 0, 1, 2, and 3 days of cold stress. Differential gene expression revealed that genes associated with photosynthesis (LHCA1), stress signal transduction (MYC2-1, MYC2-2, WRKY22, WRKY2), and antioxidant defense (SOD-1, SOD-2) were initially up-regulated and subsequently down-regulated, as validated by qRT-PCR. Overall, we found that the application of 150 mg L⁻¹ Vc enhanced cold tolerance in grafted cucumber seedlings by modulating gene expression networks related to photosynthesis, stress response, and the antioxidant defense system. This study provides a way for developing Vc biostimulants to enhance cold tolerance in grafted cucumbers, improving sustainable cultivation in low-temperature regions. Full article

Forest fires are commonly regarded as negative for ecosystems; however, they also represent a major ecological force shaping the biodiversity of invertebrates and many other organisms. The aim of this study was to better understand how multiple groups of invertebrates respond to wildfire across different forest types in Central Europe. The research was conducted following a large forest fire (ca. 1200 ha) that occurred in 2022. Data were collected over two years (2023 and 2024), from April to September. The research was conducted in coniferous forests and included six pairwise study types: burnt and unburnt dead spruce (bark beetle affected), burnt and unburnt clear-cuts, and burnt and unburnt healthy stands. In total, 96 traps were deployed each year. Across both years, 220,348 invertebrates were recorded (1.Y: 128,323; 2.Y: 92,025), representing 24 taxonomic groups. A general negative trend in abundance following forest fire was observed in the groups Acari, Auchenorhyncha, Blattodea, Dermaptera, Formicidae, Chilopoda, Isopoda, Opiliones, and Pseudoscorionida. Groups showing a neutral response included Araneae, Coleoptera, Collembola, Diplopoda, Heteroptera, Psocoptera, Raphidioptera, Thysanoptera, and Trichoptera. Positive responses, indicated by an increase in abundance, were recorded in Hymenoptera, Orthoptera, Lepidoptera, and Diptera. However, considerable differences among management types (clear-cut, dead spruce, and healthy) were evident, as their distinct characteristics largely influenced invertebrate abundance in both unburnt and burnt variants of the types across all groups studied. Forest fire primarily creates favorable conditions for heliophilous, open-landscape, and floricolous invertebrate groups, while less mobile epigeic groups are strongly negatively affected. In the second year post-fire, the total invertebrate abundance in burnt sites decreased to 59% of the first year’s levels. Conclusion: Forest fire generates a highly heterogeneous landscape from a regional perspective, creating unique ecological niches that persist more than two years after fire. For many invertebrates, successional return toward pre-fire conditions is delayed or incomplete. Full article

The enteroendocrine system of the gastrointestinal (GI) tract is the largest endocrine organ in the human body, playing a central role in the regulation of hunger, satiety, digestion, and energy homeostasis. Numerous factors—including dietary components, physical activity, and the gut microbiota—affect the secretion of GI hormones. This study aims to analyze how these factors modulate enteroendocrine function and influence systemic metabolic regulation. This review synthesizes the current scientific literature on the physiology and distribution of enteroendocrine cells and mechanisms of hormone secretion in response to macronutrients, physical activity, and microbial metabolites. Special attention is given to the interactions between gut-derived signals and central nervous system pathways involved in appetite control. Different GI hormones are secreted in specific regions of the digestive tract in response to meal composition and timing. Macronutrients, particularly during absorption, stimulate hormone release, while physical activity influences hormone concentrations, decreasing ghrelin and increasing GLP-1, PYY, and leptin levels. The gut microbiota, through fermentation and metabolite production (e.g., SCFAs and bile acids), modulates enteroendocrine activity. Species such as Akkermansia muciniphila are associated with improved gut barrier integrity and enhanced GLP-1 secretion. These combined effects contribute to appetite regulation and energy balance. Diet composition, physical activity, and gut microbiota are key modulators of gastrointestinal hormone secretion. Their interplay significantly affects appetite regulation and metabolic health. A better understanding of these relationships may support the development of personalized strategies for managing obesity and related disorders. Full article

The adoption of digital technologies, such as the Internet of Things (IoT), has emerged as a key strategy to improve efficiency, sustainability, and productivity in the agricultural sector, especially in contexts of modernization and digital transformation in developing regions. This study analyzes the key factors influencing the adoption of IoT technologies by farmers in the province of Guayas, Ecuador, and their impact on agricultural yields. The research is grounded in innovation diffusion theory and technology acceptance models, which emphasize the role of perception, usability, training, and economic viability in digital adoption. A total of 250 surveys were administered, with 232 valid responses (92.8% response rate), reflecting strong interest from the agricultural sector in digital transformation and precision agriculture. Using structural equation modeling (SEM), the results confirm that general perception of IoT (β = 0.514), practical functionality (β = 0.488), and technical training (β = 0.523) positively influence adoption, while high implementation costs negatively affect it (β = −0.651), all of which are statistically significant (p < 0.001). Furthermore, adoption has a strong positive effect on agricultural yield (β = 0.795). The model explained a high percentage of variance in both adoption (R² = 0.771) and performance (R² = 0.706), supporting its predictive capacity. These findings underscore the need for public and private institutions to implement targeted training and financing strategies to overcome economic barriers and foster the sustainable integration of IoT technologies in Ecuadorian agriculture. Full article

To explore the characteristics of species diversity and phylogenetic diversity, as well as the dominant processes of community construction, in different forest types (deciduous broad-leaved forest, mixed coniferous and broad-leaved forest, and Chinese fir plantation) in subtropical regions, analyze the specific driving patterns of soil nutrients and other environmental factors on the formation of forest diversity in different forest types, and clarify the differences in response to environmental heterogeneity between natural forests and plantation forests. Based on 48 fixed monitoring plots of 50 m × 50 m in Shouchang Forest Farm, Jiande City, Zhejiang Province, woody plants with a diameter at breast height ≥5 cm were investigated. Species diversity indices (Margalef index, Shannon–Wiener index, Simpson index, and Pielou index), phylogenetic structure index (PD), and environmental factors were used to analyze the relationship between diversity characteristics and environmental factors through variance analysis, correlation analysis, and generalized linear models. Phylogenetic structural indices (NRI and NTI) were used, combined with a random zero model, to explore the mechanisms of community construction in different forest types. Research has found that (1) the deciduous broad-leaved forest had the highest species diversity (Margalef index of 4.121 ± 1.425) and phylogenetic diversity (PD index of 21.265 ± 7.796), significantly higher than the mixed coniferous and broad-leaved forest and the Chinese fir plantation (p < 0.05); (2) there is a significant positive correlation between species richness and phylogenetic diversity, with the best fit being AIC = 70.5636 and R² = 0.9419 in broad-leaved forests; however, the contribution of evenness is limited; (3) the specific effects of soil factors on different forest types: available phosphorus (AP) is negatively correlated with the diversity of deciduous broad-leaved forests (p < 0.05), total phosphorus (TP) promotes the diversity of coniferous and broad-leaved mixed forests, while the diversity of Chinese fir plantations is significantly negatively correlated with total nitrogen (TN); (4) the phylogenetic structure of three different forest types shows a divergent pattern in deciduous broad-leaved forests, indicating that competition and exclusion dominate the construction of deciduous broad-leaved forests; the aggregation mode of Chinese fir plantation indicates that environmental filtering dominates the construction of Chinese fir plantation; the mixed coniferous and broad-leaved forest is a transitional model, indicating that the mixed coniferous and broad-leaved forest is influenced by both stochastic processes and ecological niche processes. In different forest types in subtropical regions, the species and phylogenetic diversity of broad-leaved forests is significantly higher than in other forest types. The impact of soil nutrients on the diversity of different forest types varies, and the characteristics of community construction in different forest types are also different. This indicates the importance of protecting the original vegetation and provides a scientific basis for improving the ecological function of artificial forest ecosystems through structural adjustment. The research results have important practical guidance value for sustainable forest management and biodiversity conservation in the region. Full article

Oil spill simulation models are essential for predicting the oil spill behavior and movement in marine environments. In this study, we comprehensively reviewed a large and diverse body of peer-reviewed literature obtained from Scopus and Web of Science. Our initial analysis phase focused on examining trends in scientific publications, utilizing the complete dataset derived after systematic screening and database integration. In the second phase, we applied elements of a systematic review to identify and evaluate the most influential contributions in the scientific field of oil spill simulations. Our analysis revealed a steady and accelerating growth of research activity over the past five decades, with a particularly notable expansion in the last two. The field has also experienced a marked increase in collaborative practices, including a rise in international co-authorship and multi-authored contributions, reflecting a more global and interdisciplinary research landscape. We cataloged the key modeling frameworks that have shaped the field from established systems such as OSCAR, OIL-MAP/SIMAP, and GNOME to emerging hybrid and Lagrangian approaches. Hydrodynamic models were consistently central, often integrated with biogeochemical, wave, atmospheric, and oil-spill-specific modules. Environmental variables such as wind, ocean currents, and temperature were frequently used to drive model behavior. Geographically, research has concentrated on ecologically and economically sensitive coastal and marine regions. We conclude that future progress will rely on the real-time integration of high-resolution environmental data streams, the development of machine-learning-based surrogate models to accelerate computations, and the incorporation of advanced biodegradation and weathering mechanisms supported by experimental data. These advancements are expected to enhance the accuracy, responsiveness, and operational value of oil spill modeling tools, supporting environmental monitoring and emergency response. Full article

Lightweight steel-framing (LSF) systems have become increasingly prominent in modern construction due to their structural efficiency, design flexibility, and sustainability. However, traditional facade materials such as stone are often cost-prohibitive, and brick veneers—despite their popularity—pose seismic performance concerns. This study introduces an innovative porcelain sheathing system for cold-formed steel (CFS) shear walls. Porcelain has no veins thus it offers integrated and reliable strength unlike granite. Four full-scale CFS shear walls incorporating screwed porcelain sheathing (SPS) were tested under combined cyclic lateral and constant gravity loading. The experimental program investigated key seismic characteristics, including lateral stiffness and strength, deformation capacity, failure modes, and energy dissipation, to calculate the system response modification factor (R). The test results showed that configurations with horizontal sheathing, double mid-studs, and three blocking rows improved performance, achieving up to 21.1 kN lateral resistance and 2.5% drift capacity. The average R-factor was 4.2, which exceeds the current design code values (AISI S213: R = 3; AS/NZS 4600: R = 2), suggesting the enhanced seismic resilience of the SPS-CFS system. This study also proposes design improvements to reduce the risk of brittle failure and enhance inelastic behavior. In addition, the results inform discussions on permissible building heights and contribute to the advancement of CFS design codes for seismic regions. Full article

In this study, we propose a bidirectional chemical sensor platform based on a reconfigurable ion-sensitive field-effect transistor (R-ISFET) architecture. The device incorporates Ni-silicide Schottky barrier source/drain (S/D) contacts, enabling ambipolar conduction and bidirectional turn-on behavior for both p-type and n-type configurations. Channel polarity is dynamically controlled via the program gate (PG), while the control gate (CG) suppresses leakage current, enhancing operational stability and energy efficiency. A dual-control-gate (DCG) structure enhances capacitive coupling, enabling sensitivity beyond the Nernst limit without external amplification. The extended-gate (EG) architecture physically separates the transistor and sensing regions, improving durability and long-term reliability. Electrical characteristics were evaluated through transfer and output curves, and carrier transport mechanisms were analyzed using band diagrams. Sensor performance—including sensitivity, hysteresis, and drift—was assessed under various pH conditions and external noise up to 5 V_pp (i.e., peak-to-peak voltage). The n-type configuration exhibited high mobility and fast response, while the p-type configuration demonstrated excellent noise immunity and low drift. Both modes showed consistent sensitivity trends, confirming the feasibility of complementary sensing. These results indicate that the proposed R-ISFET sensor enables selective mode switching for high sensitivity and robust operation, offering strong potential for next-generation biosensing and chemical detection. Full article

Drought stress severely limits the productivity of sweet potato (Ipomoea batatas L.), yet the stage-specific molecular mechanisms of its adaptation remain poorly understood. Therefore, we integrated transcriptomics and extensive targeted metabolomics analysis to investigate the drought responses of the sweet potato cultivar ‘Luoyu 11’ during the branching and tuber formation stage (DS1) and the storage root expansion stage (DS2) under controlled drought conditions (45 ± 5% field capacity). Transcriptome analysis identified 8292 and 13,509 differentially expressed genes in DS1 and DS2, respectively, compared with the well-watered control (75 ± 5% field capacity). KEGG enrichment analysis revealed the activation of plant hormone signaling, carbon metabolism, and flavonoid biosynthesis pathways, and more pronounced transcriptional changes were observed during the DS2 stage. Metabolomic analysis identified 415 differentially accumulated metabolites across the two growth periods, with flavonoids being the most abundant (accounting for 30.3% in DS1 and 23.7% in DS2), followed by amino acids and organic acids, which highlighted their roles in osmotic regulation and oxidative stress alleviation. Integrated omics analysis revealed stage-specific regulation of flavonoid biosynthesis under drought stress. Genes such as CYP75B1 and IF7MAT were consistently downregulated, whereas flavonol synthase and glycosyltransferases exhibited differential expression patterns, which correlated with the selective accumulation of trifolin and luteoloside. Our findings provide novel insights into the molecular basis of drought tolerance in sweet potato and offer actionable targets for breeding and precision water management in drought-prone regions. Full article

Aquatic macrophytes are a vital component of lake ecosystems, profoundly influencing ecosystem structure and function. Under future scenarios of more frequent extreme floods and intensified lake eutrophication, aquatic macrophytes will face increasing challenges. Therefore, understanding aquatic macrophyte responses to flood disturbances and nutrient enrichment is crucial for predicting future vegetation dynamics in lake ecosystems. This study focuses on Huangmaotan Lake, a Yangtze River floodplain lake, where we reconstructed 200-year successional trajectories of macrophyte communities and their driving mechanisms. With a multiproxy approach we analyzed a well-dated sediment core incorporating plant macrofossils, grain size, nutrient elements, heavy metals, and historical flood records from the watershed. The results demonstrate a significant shift in the macrophyte community, from species that existed before 1914 to species that existed by 2020. Unlike the widespread macrophyte degradation seen in most regional lakes, this lake has maintained clear-water plant dominance and experienced continuous vegetation expansion over the past 50 years. We attribute this to the interrelated effects of floods and the enrichment of ecosystems with nutrients. Specifically, our findings suggest that nutrient enrichment can mitigate the stress effects of floods on aquatic macrophytes, while flood disturbances help reduce excess nutrient concentrations in the water column. These findings offer applicable insights for aquatic vegetation restoration in the Yangtze River floodplain and other comparable lake systems worldwide. Full article

Water scarcity and spatial variability in soil fertility are key constraints to stable grain production in the Huang-Huai-Hai Plain. However, the interaction mechanisms between regulated deficit irrigation and soil fertility influencing yield formation and water-nitrogen use efficiency in winter wheat remain unclear. In this study, a two-year field experiment (2022–2024) was conducted to investigate the effects of two irrigation regimes—regulated deficit irrigation during the heading to grain filling stage (D) and full irrigation (W)—under four soil fertility levels: F1 (N: P: K = 201.84: 97.65: 199.05 kg ha⁻¹), F2 (278.52: 135: 275.4 kg ha⁻¹), F3 (348.15: 168.75: 344.25 kg ha⁻¹), and CK (no fertilization). The results show that aboveground dry matter accumulation, total nitrogen content, pre-anthesis dry matter and nitrogen translocation, and post-anthesis accumulation significantly increased with fertility level (p < 0.05). Regulated deficit irrigation promoted the contribution of post-anthesis dry matter to grain yield under the CK and F1 treatments, but suppressed it under the F2 and F3 treatments. However, it consistently enhanced the contribution of post-anthesis nitrogen to grain yield (p < 0.05) across all fertility levels. Higher fertility levels prolonged the grain filling duration by 18.04% but reduced the mean grain filling rate by 15.05%, whereas regulated deficit irrigation shortened the grain filling duration by 3.28% and increased the mean grain filling rate by 12.83% (p < 0.05). Grain yield significantly increased with improved fertility level (p < 0.05), reaching a maximum of 9361.98 kg·ha⁻¹ under the F3 treatment. Regulated deficit irrigation increased yield under the CK and F1 treatments but reduced it under the F2 and F3 treatments. Additionally, water use efficiency exhibited a parabolic response to fertility level and was significantly enhanced by regulated deficit irrigation. Nitrogen partial factor productivity (NPFP) declined with increasing fertility level (p < 0.05); Regulated deficit irrigation improved NPFP under the F1 treatment but reduced it under the F2 and F3 treatments. The highest NPFP (41.63 kg·kg⁻¹) was achieved under the DF1 treatment, which was 54.81% higher than that under the F3 treatment. TOPSIS analysis showed that regulated deficit irrigation combined with the F1 fertility level provided the optimal balance among yield, WUE, and NPFP. Therefore, implementing regulated deficit irrigation during the heading–grain filling stage under moderate fertility (F1) is recommended as the most effective strategy for achieving high yield and efficient resource utilization in winter wheat production in this region. Full article

Natural disasters like wildfires pose significant threats to communities, which necessitates timely and effective disaster response strategies. While Aspect-based Sentiment Analysis (ABSA) has been widely used to extract sentiment-related information at the sub-sentence level, the corresponding field of Aspect-based Emotion Analysis (ABEA) remains underexplored due to dataset limitations and the increased complexity of emotion classification. In this study, we used EmoGRACE, a fine-tuned BERT-based model for ABEA, which we applied to georeferenced tweets of the 2020 California wildfires. The results for this case study reveal distinct spatio-temporal emotion patterns for wildfire-related aspect terms, with fear and sadness increasing near wildfire perimeters. This study demonstrates the feasibility of tracking emotion dynamics across disaster-affected regions and highlights the potential of ABEA in real-time disaster monitoring. The results suggest that ABEA can provide a nuanced understanding of public sentiment during crises for policymakers. Full article

To improve collision risk prediction in high-traffic coastal waters and support real-time decision-making in maritime navigation, this study proposes a regional collision risk prediction system integrating the Computed Distance at Collision (CDC) method with an Adaptive Neuro-Fuzzy Inference System (ANFIS). Unlike Distance at Closest Point of Approach (DCPA), which depends on the position of Global Positioning System (GPS) antennas, Computed Distance at Collision (CDC) directly reflects the actual hull shape and potential collision point. This enables a more realistic assessment of collision risk by accounting for the hull geometry and boundary conditions specific to different ship types. The system was designed and validated using ship motion simulations involving bulk and container ships across varying speeds and crossing angles. The CDC method was used to define collision, almost-collision, and near-collision situations based on geometric and hydrodynamic criteria. Subsequently, the FIS–CDC model was constructed using the ANFIS by learning patterns in collision time and distance under each condition. A total of four input variables—ship speed, crossing angle, remaining time, and remaining distance—were used to infer the collision risk index (CRI), allowing for a more nuanced and vessel-specific assessment than traditional CPA-based indicators. Simulation results show that the time to collision decreases with higher speeds and increases with wider crossing angles. The bulk carrier exhibited a wider collision-prone angle range and a greater sensitivity to speed changes than the container ship, highlighting differences in maneuverability and risk response. The proposed system demonstrated real-time applicability and accurate risk differentiation across scenarios. This research contributes to enhancing situational awareness and proactive risk mitigation in Maritime Autonomous Surface Ship (MASS) and Vessel Traffic System (VTS) environments. Future work will focus on real-time CDC optimization and extending the model to accommodate diverse ship types and encounter geometries. Full article

While boreal forests constitute 30% of the Earth’s forested area and are responsible for 20% of the global carbon sink, there is considerable concern about their sustainability. This paper focuses on the role of elevated CO₂, examining whether wood volume in these forests has responded to increased CO₂ over the last 60 years. To accomplish this, we use a rich set of wood volume measurement data from the Province of Alberta, Canada, and deploy quasi-experimental techniques to determine the effect of elevated CO₂. While the few experimental studies that have examined boreal forests have found almost no effect of elevated CO₂, our results indicate that a 1.0% increase in lifetime exposure to CO₂ leads to a 1.1% increase in aboveground wood volume in these boreal forests. This study showcases the value of research designs that use natural settings to better account for the effects of prolonged exposure to elevated CO₂. Our results should enable improved delineation of the drivers of historical changes in wood volume and carbon storage in boreal forests. In addition, when combined with other studies, these results will likely aid policymakers in designing management or policy approaches that will enhance the sustainability of forests in boreal regions. Full article