Search Results (3,885)

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

Manganese (Mn) excess and low pH often coexist in some citrus orchard soils. Little information is known about the underlying mechanism by which raising pH reduces Mn toxicity in citrus plants. ‘Sour pummelo’ (Citrus grandis (L.) Osbeck) seedlings were treated with 2 (Mn2) or 500 (Mn500) μM Mn at a pH of 3 (P3) or 5 (P5) for 25 weeks. Raising pH mitigated Mn500-induced increases in Mn, iron, copper, and zinc concentrations in roots, stems, and leaves, as well as nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, copper, iron, and zinc distributions in roots, but it mitigated Mn500-induced decreases in nitrogen, phosphorus, potassium, calcium, magnesium, sulfur, and boron concentrations in roots, stems, and leaves, as well as nutrient imbalance. Raising pH mitigated Mn500-induced necrotic spots on old leaves, yellowing of young leaves, decreases in seedling growth, leaf chlorophyll concentration, and CO₂ assimilation (A_CO2), increase in root dry weight (DW)/shoot DW, and alterations of leaf chlorophyll a fluorescence (OJIP) transients and related indexes. Further analysis indicated that raising pH ameliorated Mn500-induced impairment of nutrient homeostasis, leaf thylakoid structure by iron deficiency and competition of Mn with magnesium, and photosynthetic electron transport chain (PETC), thereby reducing Mn500-induced declines in A_CO2 and subsequent seedling growth. These results validated the hypothesis that raising pH reduced Mn toxicity in ‘Sour pummelo’ seedlings by (a) reducing Mn uptake, (b) efficient maintenance of nutrient homeostasis under Mn stress, (c) reducing Mn excess-induced impairment of thylakoid structure and PEPC and inhibition of chlorophyll biosynthesis, and (d) increasing A_CO2 and subsequent seedling growth under Mn excess. Full article

(1) Background: Fatigue impacts neuromuscular performance, especially in endurance sports like rowing. The aim is to explore how continuous workload affects explosiveness and fatigue progression. This study examines acute fatigue during repeated race events by assessing vertical jump height, force output, and subjective fatigue over three consecutive days at the 2024 Hungarian National Rowing Championships. (2) Methods: Nine rowers (five women, four men; mean age 20.17 ± 1.73 years) competed in multiple 2000 m races over three days. Lower limb explosiveness was measured via countermovement jump (CMJ) using a Kistler force plate, pre- and post-race. Heart rate data were recorded with Polar Team Pro^®. Subjective fatigue was assessed using the ‘Daily Wellness Questionnaire’. (3) Results: We found a significant difference in the pattern of the medians of the force exerted by males during the jump between the results of the Thursday preliminaries (ThuQ_Me = 13.3) and the second final (ThuF2_Me = −75.5). Women showed no notable changes. (4) Conclusion: Repeated high-intensity races induce neuromuscular fatigue in men, reflected in reduced explosiveness and increased subjective fatigue. Future research should incorporate biochemical markers to deepen the understanding of fatigue mechanisms. Full article

Solving competitive facility location problems can optimize market share or operational efficiency in environments where multiple firms compete for customer attention. In such contexts, facility attractiveness is shaped not only by geographic proximity but also by customer preference characteristics. This study presents a novel heuristic framework that integrates multi-view K-means clustering with customer behavior modeling reinforced by a co-regularization mechanism to align clustering results across heterogeneous data views. By jointly exploiting spatial and behavioral information, the framework clusters customers and facilities into meaningful market segments. Within each segment, a bilevel optimization model is applied to represent the sequential decision-making of competing entities—where a leader first selects facility locations, followed by a reactive follower. An empirical evaluation on a real-world dataset from San Francisco demonstrates that the proposed approach, using optimal co-regularization parameters, achieves a total runtime of approximately 4.00 s—representing a 99.34% reduction compared to the full CFLBP-CB model (608.58 s) and a 99.32% reduction compared to a genetic algorithm (585.20 s). Concurrently, it yields an overall profit of 16,104.17, which is an approximate 0.72% increase over the Direct CFLBP-CB profit of 15,988.27 and is only 0.21% lower than the genetic algorithm’s highest profit of 16,137.75. Moreover, comparative analysis reveals that the proposed multi-view clustering with co-regularization outperforms all single-view baselines, including K-means, spectral, and hierarchical methods. This superiority is evidenced by an approximate 5.21% increase in overall profit and a simultaneous reduction in optimization time, thereby demonstrating its effectiveness in capturing complementary spatial and behavioral structures for competitive facility location. Notably, the proposed two-stage approach achieves high-quality solutions with significantly shorter computation times, making it suitable for large-scale or time-sensitive competitive facility planning tasks. Full article

The effective design of logistics platform business models is an important means for platform-type logistics enterprises to gain a competitive advantage. This study employs RRS Logistics as a case study to clarify the dynamic environmental mechanisms of logistics platform business models from the perspective of value co-creation and build a novel structural framework for logistics platform business models with community at their core. The research findings are as follows: First, guided by the idea of “value positioning–value co–creation–value support–value maintenance–value capture”, the conceptual framework of business models is redefined. The key steps in designing logistics platform business models, which can provide guidance and assistance for different logistics platforms, are proposed. Second, the design process for logistics platform business models should be dynamically adjusted in real time according to changes and environmental uncertainty. Third, in the process of transitioning to an ecological platform, logistics platforms’ ecosystem service clusters and ecosystem envelope are key factors in achieving a win–win scenario for all the stakeholders in the community. The case studies show that in logistics platform business model design, methods and key steps based on value co-creation could enhance the core competitiveness of logistics platforms. Full article

This paper presents a multi-strategy enhanced bald eagle search algorithm (EAB-BES) for 3D UAV path planning in urban environments. EAB-BES addresses key limitations of the traditional bald eagle search (BES) algorithm, including slow convergence, susceptibility to local optima, and poor adaptability in complex urban scenarios. The algorithm enhances solution space exploration through elite opposition-based learning, balances global search and local exploitation via an adaptive weight mechanism, and refines local search directions using block-based elite-guided differential mutation. These innovations significantly improve BES’s convergence speed, path accuracy, and adaptability to urban constraints. To validate its effectiveness, six high-density urban environments with varied obstacles were used for comparative experiments against nine advanced algorithms. The results demonstrate that EAB-BES achieves the fastest convergence speed and lowest stable fitness values and generates the shortest, smoothest collision-free 3D paths. Statistical tests and box plot analysis further confirm its superior performance in multiple performance metrics. EAB-BES has greater competitiveness compared with the comparative algorithms and can provide an efficient, reliable and robust solution for UAV autonomous navigation in complex urban environments. Full article

High demand for sustainable solutions in the construction industry determines the significant relevance of developing new eco-friendly composites with a reduced carbon impact on the environment. The main aim of this study is to investigate the possibility and efficiency of using technical sulfur (TS) as a modifying additive for geopolymer composites and to select the optimal content of polypropylene fiber (PF). To assess the potential of TS, experimental samples of geopolymer solutions based on metakaolin and fly ash were prepared. The TS content varied from 0% to 9% by weight of binder in 3% increments. In the first stage, the density, compressive and flexural strength, capillary water absorption and microstructure of hardened geopolymer composites were tested. The TS additive in an amount of 3% was the most effective and provided an increase in compressive strength by 12.6%, flexural strength by 12.8% and a decrease in capillary water absorption by 18.2%. At the second stage, the optimal PF content was selected, which was 0.75%. The maximum increases in strength properties were recorded for the composition with 3% TS and 0.75% PF: 8% for compression and 32.6% for bending. Capillary water absorption decreased by 12.9%. The geopolymer composition developed in this work, modified with TP and PF, has sufficient mechanical and physical properties and can be considered for further study in order to determine its competitiveness with cement composites in real construction practice. Full article

Emerging markets face growing pressures to integrate sustainable English business practices while maintaining economic growth, particularly in addressing environmental challenges and achieving carbon neutrality goals. English Financial information extraction becomes crucial for supporting green finance initiatives, Environmental, Social, and Governance (ESG) compliance, and sustainable investment decisions in these markets. This paper presents FinATG, an AI-driven autoregressive framework for extracting sustainability-related English financial information from English texts, specifically designed to support emerging markets in their transition toward sustainable development. The framework addresses the complex challenges of processing ESG reports, green bond disclosures, carbon footprint assessments, and sustainable investment documentation prevalent in emerging economies. FinATG introduces a domain-adaptive span representation method fine-tuned on sustainability-focused English financial corpora, implements constrained decoding mechanisms based on green finance regulations, and integrates FinBERT with autoregressive generation for end-to-end extraction of environmental and governance information. While achieving competitive performance on standard benchmarks, FinATG’s primary contribution lies in its architecture, which prioritizes correctness and compliance for the high-stakes financial domain. Experimental validation demonstrates FinATG’s effectiveness with entity F1 scores of 88.5 and REL F1 scores of 80.2 on standard English datasets, while achieving superior performance (85.7–86.0 entity F1, 73.1–74.0 REL+ F1) on sustainability-focused financial datasets. The framework particularly excels in extracting carbon emission data, green investment relationships, and ESG compliance indicators, achieving average AUC and RGR scores of 0.93 and 0.89 respectively. By automating the extraction of sustainability metrics from complex English financial documents, FinATG supports emerging markets in meeting international ESG standards, facilitating green finance flows, and enhancing transparency in sustainable business practices, ultimately contributing to their sustainable development goals and climate action commitments. Full article

The electroencephalogram (EEG), widely used for measuring the brain’s electrophysiological activity, has been extensively applied in the automatic detection of epileptic seizures. However, several challenges remain unaddressed in prior studies on automated seizure detection: (1) Methods based on CNN and LSTM assume that EEG signals follow a Euclidean structure; (2) Algorithms leveraging graph convolutional networks rely on adjacency matrices constructed with fixed edge weights or predefined connection rules. To address these limitations, we propose a novel algorithm: Dynamic Graph Convolutional Network with Dilated Convolution (DGDCN). By leveraging a spatiotemporal attention mechanism, the proposed model dynamically constructs a task-specific adjacency matrix, which guides the graph convolutional network (GCN) in capturing localized spatial and temporal dependencies among adjacent nodes. Furthermore, a dilated convolutional module is incorporated to expand the receptive field, thereby enabling the model to capture long-range temporal dependencies more effectively. The proposed seizure detection system is evaluated on the TUSZ dataset, achieving AUC values of 88.7% and 90.4% on 12-s and 60-s segments, respectively, demonstrating competitive performance compared to current state-of-the-art methods. Full article

Murine microglia exhibit rapid self-renewal upon removal from the postnatal brain. However, the signaling pathways that regulate microglial repopulation remain largely unclear. To address this knowledge gap, we depleted microglia from mixed glial cultures using anti-CD11b magnetic particles and cultured them for 4 weeks to monitor their repopulation ability in vitro. Flow cytometry and immunocytochemistry revealed that anti-CD11b bead treatment effectively eliminated >95% of microglia in mixed glial cultures. Following removal, the number of CX3CR1-positive microglia gradually increased; when a specific threshold was reached, repopulation ceased without any discernable rise in cell death. Cell cycle and 5-ethynyl-2′-deoxyuridine incorporation assays suggested the active proliferation of repopulating microglia at d7. Time-lapse imaging demonstrated post-removal division of microglia. Colony-stimulating factor 1 receptor-phosphoinositide 3-kinase-protein kinase B signaling was identified as crucial for microglial repopulation, as pharmacological inhibition or neutralization of the pathway significantly abrogated repopulation. Transwell cocultures revealed that resident microglia competitively inhibited microglial proliferation probably through contact inhibition. This in vitro microglial removal system provides valuable insights into the mechanisms underlying microglial proliferation. Full article

The integration of renewable energy into power grids is imperative for reducing carbon emissions and mitigating reliance on depleting fossil fuels. In this paper, we develop symmetric and asymmetric evolutionary game-theoretic models to analyze how user–grid cooperation in peak shaving can be enhanced by incorporating whole-process democracy (deliberative governance) into decision-making. Our framework captures excess returns, cooperation-driven profits, energy pricing, participation costs, and benefit-sharing coefficients to identify equilibrium conditions under varied subsidy, cost, and market scenarios. Furthermore, this study integrates the theory, path, and mechanism of deliberative procedures under the perspective of whole-process democracy, exploring how inclusive and participatory decision-making processes can enhance cooperation in renewable energy systems. We simulate seven scenarios that systematically adjust subsidy rates, cost–benefit structures, dynamic pricing, and renewable-versus-conventional competitiveness, revealing that robust cooperation emerges only under well-aligned incentives, equitable profit sharing, and targeted financial policies. These scenarios systematically vary these key parameters to assess the robustness of cooperative equilibria under diverse economic and policy conditions. Our findings indicate that policy efficacy hinges on deliberative stakeholder engagement, fair profit allocation, and adaptive subsidy mechanisms. These results furnish actionable guidelines for regulators and grid operators to foster sustainable, low-carbon energy systems and inform future research on demand response and multi-source integration. Full article

Laser beam powder bed fusion of metals (PBF-LB/M, or simply L-PBF) has emerged as one of the most competitive additive manufacturing technologies for producing complex metallic components with high precision, design freedom, and minimal material waste. Among the various categories of additive manufacturing processes, L-PBF stands out, paving the way for the execution of part designs with geometries previously considered unfeasible. Despite offering several advantages, parts with overhang features require the use of support structures to provide dimensional stability of the part. Support structures achieve this by resisting residual stresses generated during processing and assisting heat dissipation. Although the scientific community acknowledges the role of support structures in the success of L-PBF manufacturing, they have remained relatively underexplored in the literature. In this context, the present work investigated the impact of laser power and scanning speed on the dimensioning, integrity and tensile strength of single-walled block type support structures manufactured in AISI 316L stainless steel. The method proposed in this work is divided in two stages: processing parameter exploration, and mechanical characterization. The results indicated that support structures become more robust and resistant as laser power increases, and the opposite effect is observed with an increment in scanning speed. In addition, defects were detected at the interfaces between the bulk and support regions, which were crucial for the failure of the tensile test specimens. For a layer thickness corresponding to 0.060 mm, it was verified that the combination of laser power and scanning speed of 150 W and 500 mm/s resulted in the highest tensile resistance while respecting the dimensional deviation requirement. Full article

Previous studies have mostly focused on the adsorption behavior of microplastics for antibiotics in soil or aqueous environments. This study explores the adsorption characteristics of microplastics for antibiotics under groundwater environmental conditions and the influence of typical influencing factors of the groundwater environment (pH, pollutant concentration, aquifer media, dissolved organic matter, and ionic strength) on the adsorption process. Polyethylene (PE) and tetracycline (TC) were selected as typical microplastics and antibiotics in the experiment. The study results showed that the adsorption of TC by PE reached equilibrium at 48 h, and the adsorption kinetics fitted pseudo-second-order kinetics models well. The adsorption isotherm was consistent with the Langmuir model. The adsorption capacity of PE for TC was highest under neutral conditions and positively correlated with the initial concentration of TC. The aquifer media exhibited limited effects on the adsorption process. Fulvic acid (FA) significantly suppressed TC adsorption onto PE, attributable to competitive adsorption mechanisms. TC adsorption on PE initially increased then declined with Ca²⁺ concentration due to Ca²⁺ bridging and competition. This research elucidates the adsorption mechanisms of PE towards TC, providing theoretical basis and reference for assessing the environmental risk of microplastics and antibiotics in groundwater. Full article

This study analyses the conditions under which co-opetition improves the supply of healthcare services in Benin. Using non-centralised administrative data from a sample of public and private health centres, we apply network theory and negative binomial regression to assess the extent to which competition affects collaboration between public and private healthcare providers. We found that competition reduces the degree of collaboration between private and public health providers. However, the COVID-19 pandemic significantly mitigated this effect, highlighting the potential for competition within the healthcare system without compromising social welfare. Notwithstanding that, we show that these benefits are not sustained over time. These findings have policy implications for the sustainability of health system financing in Africa, particularly by promoting sustainable financial mechanisms for the private sector and more inclusive governance structures. Full article

Construction wood has a high economic value, and its construction waste also has multiple consumption values. Natural wood has many advantages, such as thermal, environmental, and esthetic properties; however, wood sourced from artificial fast-growing forests is found to be deficient in mechanical strength. This shortcoming makes it less competitive in certain applications, leading many markets to remain dominated by non-renewable materials. To address this issue, various modification methods have been explored, with a focus on enhancing the plasticity and strength of wood. Studies have shown that hydrogen bonds in the internal structure of wood have a significant impact on its operational performance. Whether it is organic modification, inorganic modification, or a combination thereof, these methods will lead to a change in the shape of the hydrogen bond network between the components of the wood or will affect the process of its breaking and recombination, while increasing the formation of hydrogen bonds and related molecular synergistic effects and improving the overall operational performance of the wood. These modification methods not only increase productivity and meet the needs of efficient use and sustainable environmental protection but also elevate the wood industry to a higher level of technological advancement. This paper reviews the role of hydrogen bonding in wood modification, summarizes the mechanisms by which organic, inorganic, and composite modification methods regulate hydrogen bond networks, discusses their impacts on wood mechanical properties, dimensional stability, and environmental sustainability, and provides an important resource for future research and development. Full article