Search Results (24,113)

This paper presents a novel EEG-based learning system designed to enhance the efficiency and effectiveness of studying by dynamically adjusting the difficulty level of learning materials based on real-time attention levels. In the training phase, EEG signals corresponding to high and low concentration levels are recorded while participants engage in quizzes to learn and memorize Chinese characters. The attention levels are determined based on performance metrics derived from the quiz results. Following extensive preprocessing, the EEG data undergoes severmal feature extraction steps: removal of artifacts due to eye blinks and facial movements, segregation of waves based on their frequencies, similarity indexing with respect to delay, binary thresholding, and (PCA). These extracted features are then fed into a k-NN classifier, which accurately distinguishes between high and low attention brain wave patterns, with the labels derived from the quiz performance indicating high or low attention. During the implementation phase, the system continuously monitors the user’s EEG signals while studying. When low attention levels are detected, the system increases the repetition frequency and reduces the difficulty of the flashcards to refocus the user’s attention. Conversely, when high concentration levels are identified, the system escalates the difficulty level of the flashcards to maximize the learning challenge. This adaptive approach ensures a more effective learning experience by maintaining optimal cognitive engagement, resulting in improved learning rates, reduced stress, and increased overall learning efficiency. This adaptive approach ensures a more effective learning experience by maintaining optimal cognitive engagement, resulting in improved learning rates, reduced stress, and increased overall learning efficiency. Our results indicate that this EEG-based adaptive learning system holds significant potential for personalized education, fostering better retention and understanding of Chinese characters. Full article

Morphology is an important characteristic of the hydraulic and gravitational processes driving gully erosion. In this study, field scouring experiments were conducted on five experimental plots using terrestrial laser scanning to study gully erosion processes. The erosion and deposition on a gully slope were quantified using the M3C2 algorithm. The results show that the proportion of sediment yield of the gully slope in the whole slope–gully system ranged from 81.5% to 99.7% for different flow discharges (25, 40, 55, 70, and 85 L/min). Compared with low flow discharges (25 and 40 L/min), the gully slope presented more intense gully head retreat and higher erosion intensity under relatively high discharges (55, 70, and 85 L/min). Alcove expansion processes were characterized by horizontal and vertical cycles. Vertical dynamic changes were dominated by the co-evolution of collapses of the gully head and the deepening of the alcove. Horizontal development mainly manifested as a widening of the alcove caused by the hydraulic erosion of the gully wall. The roughness of the gully slope increased gradually with the increase in scour times and then tended towards stability. These results provide a reference for understanding the processes and mechanisms of gully erosion. Full article

Numerous studies have demonstrated the positive effects of formulated feeds on gonadal and hepatopancreatic development of Eriocheir sinensis. However, there are limited studies on the effects of formulated feeds on the immune homeostasis and metabolism of muscle tissue in E. sinensis during the fattening period. Therefore, this study used metabolomic and lipidomic to systematically analyze the effects of formulated diets on muscle metabolism in female E. sinensis. The results indicate that the formulated feeds improved immune performance by inhibiting inflammatory responses, apoptosis and autophagy. In addition, the feed promoted amino acid metabolism and protein synthesis while decreasing muscle fatty acid metabolism. Metabolomic analysis reveal that pyrimidine metabolism is involved in the regulation of muscle physiological health in fattening female crabs. Lipidomic analysis revealed that the formulated feeds play a role in muscle immune homeostasis, amino acid and fatty acid metabolism by regulating the level of ceramide (Cer (d18:1/22:0)) in sphingolipid metabolism. Through subnetwork analysis, the functional interactions of sphingolipid metabolism with the pathways of sphingolipid signaling, apoptosis regulation, inflammatory response and lipid dynamic homeostasis were identified, which further defined the important role of sphingolipid metabolism in the regulation of muscle physiological health and metabolic homeostasis was further identified. In summary, the formulated feeds effectively promote immune homeostasis and metabolism in the muscle of female E. sinensis during the fattening period. These findings provide a solid theoretical foundation for feed formulation optimization and application in fattening practices. Full article

This study investigated the individual and combined effects of α-amylase (6 and 10 ppm), xylanase (70 and 120 ppm), and cellulase (35 and 60 ppm) on the physicochemical and nutritional properties of Chinese steamed buns (CSBs) supplemented with 15% buckwheat flour. The addition of individual enzymes did not significantly affect the volume or texture of the buckwheat-enriched CSBs, although it increased the crumb moisture content and porosity. In contrast, enzyme combinations can improve specific volume and reduce hardness. The enzyme combination (α-amylase 6 ppm, xylanase 70 ppm, and cellulase 60 ppm) yielded the highest specific volume (2.50 mL/g) and the lowest hardness (271.46 g). Regarding chemical properties, individual enzymes had minimal impact, while the combined treatment (6, 70, 60 ppm) decreased starch and dietary fiber content. For nutritional properties, the glycemic response of the CSBs varied depending on the concentration of the enzyme combination used. Full article

Dietary reviews contain rich emotional and objective information; however, existing knowledge extraction methods struggle with low-resource scenarios due to sparse and imbalanced label distributions. To address these challenges, this paper proposes a few-shot supervised learning approach. First, we develop a professional dietary–emotional schema by integrating domain knowledge with real-time data to ensure the coverage of diverse emotional expressions. Next, we introduce a dataset optimization method based on dual constraints—label frequency and quantity—to mitigate label imbalance and improve model performance. Utilizing the optimized dataset and a tailored prompt template, we fine-tune the DRE-UIE model for multivariate knowledge extraction. The experimental results demonstrate that the DRE-UIE model achieves a 20% higher F1 score than BERT-BiLSTM-CRF and outperforms TENER by 1.1%. Notably, on a 20-shot subset, the model on the Chinese dataset scores 0.841 and attains a 15.16% F1 score improvement over unoptimized data, validating the effectiveness of our few-shot learning framework. Furthermore, the approach also exhibits robust performance across Chinese and English corpora, underscoring its generalization capability. This work offers a practical solution for low-resource dietary–emotional knowledge extraction by leveraging schema design, dataset optimization, and model fine-tuning to achieve high accuracy with minimal annotated data. Full article

This study aims to clarify how different types of motivation influence employee retention by identifying the distinct roles of intrinsic and extrinsic factors in shaping job satisfaction, particularly under varying levels of urban stress and generational identity. Drawing on Herzberg’s Two-Factor Theory and Self-Determination Theory, we distinguish between intrinsic drivers (e.g., autonomy, achievement) and extrinsic hygiene factors (e.g., pay, stability). Using survey data from 356 Chinese employees and applying PLS-SEM with a moderated mediation design, we investigate how urbanization and Generation Z moderate these relationships. Results show that intrinsic motivation enhances satisfaction, especially in urban settings, while extrinsic factors negatively affect satisfaction when perceived as insufficient or unfair. Job satisfaction mediates the relationship between motivation and retention, although this effect is weaker among Generation Z employees. These findings refine motivational theories by demonstrating how environmental pressure and generational values jointly shape employee attitudes. The study contributes a context-sensitive framework for understanding retention by integrating individual motivation with macro-level moderators, offering practical implications for managing diverse and urbanizing labor markets. Full article

Coupled grey and green infrastructure (CGGI) offers a promising pathway toward sustainable stormwater management in historic urban environments. This study compares CGGI and conventional grey infrastructure (GREI)-only strategies across four degrees of layout centralization (0%, 33.3%, 66.7%, and 100%) in the Quanzhou West Street Historic Reserve, China. Using a multi-objective optimization framework integrating SWMM simulations, life-cycle cost (LCC) modeling, and resilience metrics, we found that the decentralized CGGI layouts reduced the total LCC by up to 29.6% and required 60.7% less green infrastructure (GI) area than centralized schemes. Under nine extreme rainfall scenarios, the GREI-only systems showed slightly higher technical resilience (Tech-R: max 99.6%) than CGGI (Tech-R: max 99.1%). However, the CGGI systems outperformed GREI in operational resilience (Oper-R), reducing overflow volume by up to 22.6% under 50% network failure. These findings demonstrate that decentralized CGGI provides a more resilient and cost-effective drainage solution, well-suited for heritage districts with spatial and cultural constraints. Full article

Improving green innovation quality is a critical component for speeding green transformation and generating high-quality growth. This study examines the link between the pilot zone for green finance reform and innovations (PZGFRI) policy and the quality of green innovation in Chinese A-share listed firms from 2010 to 2020. This study demonstrates that the PZGFRI may greatly enhance the quality of enterprises’ green innovation. Additionally, by promoting environmental investment and reducing financial barriers, we use the mediating effect model to confirm that the PZGFRI improves the enterprises’ quality of green innovation. Meanwhile, the heterogeneity analysis demonstrates that the PZGFRI is more successful in raising the green innovation quality in state-owned, large-sized, and heavily polluting businesses. Our study’s findings offer a strong theoretical basis for improving the PZGFRI and encouraging businesses to undergo high-quality transformation. Full article

With the rapid growth of elevator installations, conventional scheduled maintenance struggles to meet the dual demands of ensuring operational safety and cost control. This study proposes an innovative on-demand maintenance method that aligns with the Chinese policy directives on elevator maintenance reform. First, we conduct a historical fault cause analysis to identify the root causes of elevator entrapment incidents. Next, we establish an entrapment prediction model based on our historical data. Then, we design an elevator entrapment risk index report according to the prediction results. Finally, we formulate an on-demand maintenance plan that combines insights from the report with the conclusions of the cause analysis. Field implementation and comparative experiments demonstrate that the proposed on-demand maintenance method outperforms the scheduled one. The result shows significant reductions in accident and maintenance workload, justifying the practical value of this approach for the industry. Full article

This study develops an integrated environmental–economic assessment framework to evaluate the life cycle environmental impacts and economic costs of CO₂ geological storage and produced water treatment in saline formations in China. Using a case study of a saline aquifer carbon storage project in the Ordos Basin, eight full-chain carbon capture, utilization, and storage (CCUS) scenarios were analyzed. The results indicate that environmental and cost performance are primarily influenced by technology choices across carbon capture, transport, and storage stages. The scenario employing potassium carbonate-based capture, pipeline transport, and brine reinjection after a reverse osmosis treatment (S5) achieved the most balanced outcome. Breakeven analyses under three carbon price projection models revealed that carbon price trajectories critically affect project viability, with a steadily rising carbon price enabling earlier profitability. By decoupling CCUS from power systems and focusing on unit CO₂ removal, this study provides a transparent and transferable framework to support cross-sectoral deployment. The findings offer valuable insights for policymakers aiming to design effective CCUS support mechanisms under future carbon neutrality targets. Full article

In the era of digital intelligence, digital media landscapes increasingly influence cultural tourism consumption. Consumerism capitalizes on tourists’ superficial aesthetic commonalities, constructing a homogenized media imagination that leads to collective convergence in travel decisions, which obscures aspects of local culture, poses safety risks, and results in fleeting local tourism booms. In this study, semistructured interviews were conducted with 36 tourists, and NVivo12.0 was used for three-level node coding in a qualitative analysis to explore the digital media attributions of conformist travel behavior. The findings indicate that digital media landscapes exert a “digital persuasion” effect by reconstructing self-experience models, directing the individual gaze, and projecting idealized self-images. These mechanisms drive tourists to follow digital traffic trends and engage in imitative behaviors, ultimately shaping the phenomenon of “group roaming”, grounded in the psychological effect of herd behavior. Full article

Background: With China’s rapidly aging population, frailty has become a growing concern among older adults. Physical activity (PA) is known to mitigate frailty-related decline, yet few studies have examined these associations longitudinally. Methods: Using five waves (2011–2020) of CHARLS data, we analyzed Chinese adults aged 60+ to assess the association between frailty—measured by a frailty index (FI)—and PA across various types (light, moderate, vigorous, total, and leisure). A generalized linear mixed-effects model was used, adjusting for demographic, socioeconomic, and health-related factors. Results: All PA types were significantly associated with lower odds of concurrent frailty, including light (OR = 0.37), moderate (OR = 0.37), vigorous (OR = 0.40), total (OR = 0.23), and leisure PA (OR = 0.56). Lagged PA also predicted reduced frailty risk over time, except for light PA. Conclusion: Regular PA is linked to a lower risk of frailty among older Chinese adults. These findings underscore the importance of sustained PA as a strategy to promote healthy aging and inform public health interventions for this population. Full article

Fritillaria unibracteata is a rare and endangered medicinal plant in the Liliaceae family, whose bulbs have been used in traditional Chinese traditional medicine for over 2000 years. The mevalonate (MVA) pathway is involved in the growth, development, response to environmental stress, and active ingredient production of plants; however, the functional characterization of MVA-pathway genes in the Liliaceae family remains poorly documented. In this study, an Acetyl-CoA C-acetyltransferase gene (FuAACT) was first cloned from F. unibracteata. It exhibited structural features of the thiolase family and showed the highest sequence identity with the Dioscorea cayenensis homolog. The K_m, V_max, and K_cat of the recombinant FuAACT were determined to be 3.035 ± 0.215 μM, 0.128 ± 0.0058 μmol/(min·mg), and 1.275 ± 0.0575 min⁻¹, respectively. The optimal catalytic conditions for FuAACT were ascertained to be 30 °C and pH 8.9. It was stable below 50 °C. His361 was confirmed to be a key amino acid residue to enzymatic catalysis by site-directed mutagenesis. Subsequent subcellular localization experiments demonstrated that FuAACT was localized in chloroplasts and cytoplasm. FuAACT-overexpressing transgenic Arabidopsis thaliana plants showed higher drought tolerance than wild-type plants. This phenotypic difference was corroborated by significant differences in seed germination rate, lateral root number, plant height, and leaf number (p < 0.05). Furthermore, the FuAACT transgenic plants resulted in the formation of a more developed fibrous root system. These results indicated that the FuAACT gene revealed substantial biological activity in vitro and in vivo, hopefully providing the basis for its further research and application in liliaceous ornamental and medicinal plants. Full article

Strengthening climate resilience constitutes a foundational approach through which cities adapt to climate change and mitigate associated environmental risks. However, research on the influence of economic policy environments on climate resilience remains limited. Guided by institutional theory and dynamic capability theory, this study employs a panel dataset comprising 272 Chinese cities at the prefecture level and above, covering the period from 2009 to 2023. It constructs a composite index framework for evaluating the green business environment (GBE) and urban climate resilience (UCR) using the entropy weight method. Employing a two-way fixed-effect regression model, it examined the impact of GBE optimization on UCR empirically and also explored the underlying mechanisms. The results show that improvements in the GBE significantly enhance UCR, with green innovation (GI) in technology functioning as an intermediary mechanism within this relationship. Moreover, climate policy uncertainty (CPU) exerts a moderating effect along this transmission pathway: on the one hand, it amplifies the beneficial effect of the GBE on GI; on the other hand, it hampers the transformation of GI into improved GBEs. The former effect dominates, indicating that optimizing the GBE becomes particularly critical for enhancing UCR under high CPU. To eliminate potential endogenous issues, this paper adopts a two-stage regression model based on the instrumental variable method (2SLS). The above conclusion still holds after undergoing a series of robustness tests. This study reveals the mechanism by which a GBE enhances its growth through GI. By incorporating CPU as a heterogeneous factor, the findings suggest that governments should balance policy incentives with environmental regulations in climate resilience governance. Furthermore, maintaining awareness of the risks stemming from climate policy volatility is of critical importance. By providing a stable and supportive institutional environment, governments can foster steady progress in green innovation and comprehensively improve urban adaptive capacity to climate change. Full article

In the context of global climate governance and the green transition, digital infrastructure serves as a critical enabler of resource allocation in the digital economy, offering strategic value in tackling synergistic pollution and carbon reduction challenges. Using panel data from 280 prefecture-level cities, this study employs a multiperiod difference-in-differences (DID) approach, leveraging smart city pilot policies as a quasinatural experiment, to assess how digital infrastructure affects urban synergistic pollution-carbon mitigation (SPCM). The empirical results show that digital infrastructure increases the urban SPCM index by 1.5%, indicating statistically significant effects. Compared with energy and income effects, digital infrastructure can influence this synergistic effect through indirect channels such as the energy effect, economic agglomeration effect, and income effect, with the economic agglomeration effect accounting for a larger share of the total effect. Additionally, fixed-asset investment has a nonlinear moderating effect on this relationship, with diminishing marginal returns on emission reduction when investment exceeds a threshold. Heterogeneity tests reveal greater impacts in eastern, nonresource-based, and environmentally regulated cities. This study expands the theory of collaborative environmental governance from the perspective of new infrastructure, providing a theoretical foundation for establishing a long-term digital technology-driven mechanism for SPCM. Full article