Search Results (14,019)

Drought stress severely limits maize growth and productivity worldwide. In this study, we examined the effects of foliar-applied carbon nanoparticles (CNPs) on morphological and physiological traits in maize plants exposed to drought stress for 25 days. Two maize hybrids, one drought-tolerant (LG 36745 PRO4) and one drought-sensitive (AG 8088 PRO2), were fertilized with 0 or 1.0 mL L⁻¹ of a CNP-based nanofertilizer at the V₂ growth stage and exposed to three drought levels: 0 MPa (control), −0.4 MPa (moderate stress), and −0.8 MPa (severe stress). The experiment followed a 2 × 2 × 3 factorial design (hybrid × CNP treatment × drought level) with four replicates. Results indicated that drought stress adversely affected most morphological and physiological traits, particularly in the drought-sensitive hybrid. However, foliar CNP application significantly alleviated the adverse effects of drought in maize plants under moderate and severe stress, primarily by preserving plant water status, enhancing water use efficiency, carboxylation efficiency, photosynthetic rate, and initial growth in challenging environments. These findings will provide the basis for future research on management practices adopted to control drought and ensure the development of modern and sustainable agriculture. Full article

Accurate crop yield prediction is fundamental to sustainable agricultural management, enabling optimized resource allocation and informed decision-making. However, a critical gap exists in current prediction models: existing approaches overlook the temporal alignment between meteorological conditions and production management phases—defined as the intervals between consecutive agronomic operations (e.g., sowing, fertilization, thinning). This oversight results in suboptimal predictive performance, as conventional whole-season weather aggregation fails to capture phase-sensitive crop–weather interactions. While machine learning (e.g., XGBoost) and deep learning approaches (e.g., CNN, LSTM) have been applied to yield prediction, these models typically treat weather variables as temporally homogeneous inputs, inadequately modeling the correlation between historical yields and phase-specific meteorological patterns. To address this gap, this study proposes CNN-LSTM-AM, an innovative hybrid deep learning model that integrates convolutional neural networks (CNNs), long short-term memory (LSTM), and attention mechanisms (AMs), utilizing weather data explicitly aligned with production management phases as input. The CNN component extracts cross-phase weather patterns, the LSTM captures sequential dependencies across growth stages, and the attention mechanism dynamically weights phase importance based on meteorological conditions. The proposed model is validated using a real-world case study of Bok choy production from an agricultural cooperative in Yunlin County, Taiwan, encompassing 1714 production cycles over eight years (2011–2019). Experimental results demonstrate that CNN-LSTM-AM achieves an RMSE of 1448.24 kg/ha, MAPE of 3.60%, and R² of 0.98, outperforming five baseline models—CNN (RMSE = 2919.18), LSTM (RMSE = 2529.74), CNN-LSTM (RMSE = 1516.44), LSTM-AM (RMSE = 2284.64), and XGBoost (RMSE = 3452.47)—representing a notable reduction in prediction error (58% lower RMSE) compared to XGBoost. Furthermore, prediction accuracy improves progressively as harvest time approaches, and phase-specific weather encoding enhances accuracy by 16.5% compared to whole-season averaging. These findings underscore the critical importance of integrating agronomic domain knowledge into data-driven prediction frameworks. Full article

Against the backdrop of uneven educational development and structural constraints in rural Mainland China, teacher agency is critical for driving professional growth and instructional improvement. Rural educators face distinct challenges—limited resources, isolated work contexts, and systemic pressures—that shape their capacity to enact change. While scholarship has documented the roles of contextual resources and individual beliefs in shaping teacher agency, less is known about the mediating mechanisms linking job resources and self-efficacy to agency within China’s rural educational landscape. This study examines how perceived job resources (teaching resources, administrative support, colleague support, parental support) and teaching self-efficacy collectively shape rural teachers’ agency, to inform policy and practice for strengthening their professional capacity. Drawing on a quantitative survey of 625 rural teachers, we employ a two-stage analytical approach: first, descriptive statistics, t-tests, ANOVA, and Pearson correlations to map baseline variable relationships; second, Hayes’ PROCESS macro (Model 4) with bootstrapping to test the mediating role of teaching self-efficacy between job resources and teacher agency. Findings reveal the following: (1) Rural teachers report moderate agency (M = 3.53/5), indicating room for growth; (2) All four job resource dimensions significantly and positively predict agency (β = 0.099–0.163); (3) Teaching self-efficacy is a robust predictor of agency (β = 0.785–0.822, p < 0.001) after controlling for resources; (4) Self-efficacy partially mediates the links between each job resource and agency, with indirect effects ranging from 0.269 (teaching resources) to 0.451 (colleague support), highlighting its central role in translating contextual resources into agentic action. We conclude that fostering rural teacher agency requires a holistic approach addressing both external job resources and internal self-efficacy. Policymakers and administrators should prioritize investments in teaching resources, collaborative support structures, and professional development to build educators’ confidence and competence. Limitations include self-report bias, cross-sectional design constraints on causal inference, and limited generalizability. Future research should use longitudinal designs and broader samples to deepen understandings of agency in structurally constrained educational settings. Full article

Background and Objectives: Childhood obesity is associated with alterations in body composition that may impair muscular strength and functional capacity. While higher body mass is often accompanied by greater absolute strength, the independent effect of adiposity on muscle strength after accounting for lean mass remains insufficiently understood. This study aimed to evaluate the associations between adiposity and muscle strength in children and adolescents, while accounting for growth and maturation, and to examine differences according to weight status. Materials and Methods: This retrospective cross-sectional study included 84 children and adolescents aged 5–18 years. Anthropometric measurements were used to calculate body mass index (BMI), waist-to-hip ratio, and waist-to-height ratio, with weight status classified according to CDC BMI-for-age percentiles. Body composition was assessed using bioelectrical impedance analysis (Tanita). Pubertal stage was evaluated using Tanner classification. Muscle strength was assessed using dominant handgrip strength. Associations between adiposity-related parameters and muscle strength were analyzed using correlation and multivariable linear regression models adjusted for age, sex, pubertal stage, physical activity, and body composition. Results: Body mass index was positively correlated with absolute handgrip strength (r = 0.561, p < 0.001). Body fat percentage was negatively associated with relative handgrip strength (r = −0.381, p < 0.001). In multivariable regression analyses, body fat percentage remained an independent negative predictor of handgrip strength (β = −0.203, p = 0.0046), whereas fat-free mass and fat-free mass index were positive predictors in respective models (p < 0.001). Conclusions: Increased adiposity is associated with reduced muscle strength in children and adolescents when strength is evaluated relative to body size or adjusted for lean mass. These findings support the concept of impaired muscle performance in pediatric populations with excess adiposity and highlight the importance of integrating body composition and functional assessments in clinical evaluation. Full article

Cyclin-dependent kinases 4 and 6 (CDK4/6) play a central role in the regulation of cell cycle progression and represent important therapeutic targets in hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2−) breast cancer. The introduction of selective CDK4/6 inhibitors, including palbociclib, ribociclib, and abemaciclib, in combination with endocrine therapy, has significantly improved clinical outcomes and has become a standard treatment strategy in both metastatic and high-risk early-stage disease. Nevertheless, treatment resistance and disease progression remain major clinical challenges. A deeper understanding of the structural characteristics of CDK4/6 and the molecular basis of inhibitor binding is therefore essential for improving therapeutic strategies and guiding the development of new targeted agents. This review provides an integrated overview of the structural features of CDK4/6 and their role in cell cycle regulation, summarizes the clinical development and major clinical trials of currently approved CDK4/6 inhibitors, and discusses recent computational studies investigating inhibitor binding and conformational dynamics. Particular attention is given to the application of in silico approaches, including molecular docking, molecular dynamics simulations, and binding free-energy calculations, which provide insights into mechanisms of therapy resistance and potential strategies to overcome them and support the identification and optimization of novel CDK4/6-targeted therapeutic candidates. By integrating structural, clinical, and computational perspectives, this review highlights current knowledge and emerging directions in CDK4/6 research that may advance the development of more personalized therapies for HR+/HER2− breast cancer, while accounting for both intrinsic and de novo resistance mechanisms. Full article

To clarify cultivar differences in growth performance, yield formation, and bioactive characteristics at the sprout and fresh seed stages, twelve pea cultivars were evaluated. Growth traits, yield formation, and changes in phenolic compounds and antioxidant activity during sprouting were assessed, and the nutritional quality and mineral element composition of fresh seeds were also determined. The results showed that cultivars 24-164 and 24-510 exhibited low germination rates and severe cotyledon decay, making them unsuitable for sprout production. Significant differences were observed among the remaining cultivars in growth traits, edible ratio, and yield efficiency, with cultivars 24-724 and 24-486 showing superior processing efficiency and utilization value. During sprouting, total phenolic and total flavonoid contents, as well as 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radical scavenging activity and ferric reducing antioxidant power (FRAP), were significantly influenced by both cultivar and light exposure stage. Root length and root diameter were significantly and positively correlated with phenolic accumulation and antioxidant activity. Analysis of fresh seed quality revealed marked inter-cultivar variation in nutritional and health-related traits. Cultivar 24-486 exhibited the highest values for phenolic content, antioxidant capacity, vitamin C, vitamin E, and Fe and Se accumulation, whereas cultivar 24-013 showed advantages in calcium and potassium contents. These results identify cultivars 24-724 and 24-486 as promising candidates for sprout production and highlight cultivar 24-486 as a dual-purpose genotype for both sprout and fresh seed utilization. Full article

Using 29,278 firm-year observations of Chinese A-share listed firms from 2012 to 2023, this study examines whether data assetisation improves corporate investment efficiency and whether bank fintech conditions shape this relationship. Data assetisation refers to the process through which firms transform data resources into economically valuable, governable, and deployable assets. We construct a text-based proxy from annual reports using a Word2Vec-expanded lexicon and further distinguish between own-use and transactional data assets. The study finds: (1) Data assetisation significantly enhances corporate investment efficiency, with self-use data assets demonstrating a stronger driving effect. (2) Mechanism analysis reveals that data assetisation alleviates underinvestment by easing financing constraints and leveraging the “talent effect”. Concurrently, it mitigates overinvestment by reducing agency problems and accelerating digital transformation, thereby enhancing investment efficiency. (3) Heterogeneity tests indicate that the positive impact of data assetisation on investment efficiency is more pronounced among growth-stage enterprises, technology-intensive firms, and companies operating in regions with high bank liquidity. (4) Banking fintech positively moderates the enhancement of corporate investment efficiency through data assetisation, with a more pronounced effect on alleviating underinvestment. However, it may also exacerbate overinvestment. This study contributes to sustainable economic development by improving resource allocation efficiency, reducing capital misallocation, and supporting high-quality, low-waste, and sustainable growth of the real economy. Consequently, enterprises should vigorously develop data assetisation, applying different types of data assets to specific use cases to unlock data dividends. This approach supports the scientific development of corporate investment decisions and enhances investment efficiency, laying a micro-level foundation for sustainable socio-economic development. Full article

The coordinated development of achenes and receptacles in strawberry is critical for seed dispersal and fruit quality, yet the underlying molecular mechanisms remain poorly characterized. Utilizing RNA-seq analysis during the ripening transition stage, we identified pronounced transcriptomic divergence between achenes and receptacles, with receptacles exhibiting more dynamic gene expression shifts. Intriguingly, a substantial subset of differentially expressed genes (DEGs) displayed antagonistic expression patterns between these tissues, including the cytokinin degradation gene cytokinin oxidase/dehydrogenase 1 (FvCKX1), which was highly expressed in both tissues but with opposing temporal trends. Functional interrogation via transient silencing and overexpression revealed a tissue-specific regulatory role for FvCKX1. RNA interference (RNAi) suppression of FvCKX1 significantly enhanced receptacle expansion but delayed achene maturation, whereas overexpression inhibited receptacle growth while accelerating achene ripening. Abscisic acid (ABA), which positively regulates fruit enlargement, was elevated in FvCKX1 RNAi receptacles and notably reduced in overexpression fruits, indicating that FvCKX1 might negatively modulate ABA synthesis during strawberry fruit development. Our results demonstrate that FvCKX1 may function as a key regulator mediating the coordinated development between achenes and receptacles in strawberry. Full article

Remote-sensing inversion of water-quality parameters is a critical interdisciplinary field, integrating remote-sensing technology, environmental science, and water resources management, providing key technical support for precise water resources monitoring and ecological governance. To address the lack of comprehensive systematic reviews in this field, this study conducted a bibliometric-based narrative review, selecting 2812 valid English studies published during 1980–2026 from the Web of Science Core Collection (WOSCC) and performing in-depth knowledge mapping analysis via CiteSpace software. The results showed that global research in this field has gone through three stages: initial exploration (1980–2000), slow growth (2001–2015), and rapid explosion (2016–2026). China ranks first in publication volume worldwide, with a collaborative research pattern dominated by core institutions, including the Chinese Academy of Sciences, Wuhan University, and the National Aeronautics and Space Administration (NASA). The core research hotspots focus on multi-source data fusion, AI-driven inversion-model optimization, and the research shift from coastal to inland water bodies. Current research faces three key challenges: poor adaptability of multi-source data-fusion technologies to water-quality monitoring, inadequate integration of geospatial and thematic factors in inversion models, and an insufficient systematic approach of inland-water-body research. Accordingly, future research should focus on advancing remote-sensing data-fusion methods, further optimizing water-quality inversion models, and strengthening inland-water-body studies. This study clarifies the field’s development context and research characteristics, providing valuable references for subsequent academic exploration and practical applications in water resources management. Full article

Substantial tracts of fallow farmland remain unutilized across southwestern China throughout winter and spring. To explore a high-yield planting pattern for utilizing such fallow land, a cereal–legume intercropping experiment was conducted in Chengdu in 2021–2022 and in 2022–2023. This involved five different intercropping ratios of oat (Avena sativa) and common vetch (Vicia sativa) including 100:0, 75:25, 50:50, 25:75, and 0:100 based on seed number per unit area. The relative density, LER (land equivalent ratio), hay yield, nutritional composition and in vitro fermentation characteristics were assessed. The study revealed that the combination of oat and common vetch led to a significant enhancement in the production performance over the monocultures. At the flowering stage, the most balanced interspecific competition was observed at a ratio of 50:50. The ratio of 50:50 had the higher LER in the mixture—from 1.018 to 1.873—, which was significantly higher than the other two intercropping ratios in 2021–2022. At the flowing development stage in 2021–2022, the harvesting of mixed crops at the 50:50 ratio resulted in a significant higher crude protein yield, 1454.7 kg/hm², than the other intercropping ratios. As the growth stage continued, the mixture hay neutral detergent fiber and acid detergent fiber contents increased, while the relative feed value and crude fat content decreased. The soluble sugar content increased with the prolongation of the growth stage and peaked at the jointing stage, and decreased with the decrease in the proportion of oat in the mixture. Additionally, the gas production showed an overall decreasing trend with the increase in the proportion of common vetch. The dry matter degradation rate in the mixture hay was overall higher than that of the monocultures, and the NH₃-N content showed an overall trend of increasing with the decrease with the intercropping ratio of oat. Consequently, the 50:50 ratio may be recommended as an oat-common vetch intercropping ratio suitable for utilizing fallow fields in southwestern China from October to April to produce high-quality forage. Full article

Nitrogen (N) and phosphorus (P) are essential nutrients that play critical roles in plant physiological processes and the accumulation of N and P in broccoli head was significantly correlated with yield. Therefore, there is a need for a rapid, non-destructive diagnosis of crop status by detecting deficiencies in essential nutrients. This study evaluated the effects of N and P deficiency on field grown broccoli (Brassica oleracea L. var. italica Plenk) using a plant-induced electrical signal (PIES) sensor, in which needle electrodes are inserted into the stem to measure electrical conductivity reflecting plant water and ion status. Four treatments were established, including the control (N100P100) with sufficient N and P supply, N deficiency (N0P100), P deficiency (N100P0), and combined N–P deficiency (N0P0). For sufficient supply, urea and fused phosphate (FP) were applied at rates of 122 kg N ha⁻¹ and 71 kg P ha⁻¹, respectively. Soil, stem, and leaf nutrient contents, growth parameters, and stress related indicators were analyzed and their relationship with PIES values were evaluated. PIES was highest in control (N100P100) and lowest under N–P deficiency (N0P0). Higher PIES values were observed during the vegetative stage, whereas values declined during the reproductive stage, reflecting changes in physiological activity. Growth parameters such as shoot and root weight and stem diameter were generally superior in the control (N100P100) treatment, while leaf calcium (Ca), magnesium (Mg), and potassium (K) concentrations showed no significant differences among treatments. Total N content in leaves was higher in N fertilized treatments (control and P deficiency). Photosynthesis-related parameters, including soil plant analysis development (SPAD), Fv/Fm, and chlorophyll content, were lowest under N–P deficiency, which was reflected in the PIES. Principal component analysis (PCA) showed that the PIES was closely associated with growth and photosynthetic parameters and clearly distinguished N sufficient treatments (control and P deficiency) from N deficient treatments (N0P100, N0P0). Overall, these findings suggest that PIES monitoring can serve as a sensitive physiological indicator of nutrient stress and may be applied as an early diagnostic tool before visible growth inhibition occurs in broccoli cultivation. Full article

Chrysaora pacifica, a scyphozoan jellyfish widely distributed in East Asian waters, has recently shown signs of range expansion along the coasts of Korea, Japan, and China. However, ecological information on its early planktonic stage, the ephyra, remains limited. In this study, we experimentally investigated the effects of seawater temperature on the growth, feeding, and survival of C. pacifica ephyrae under controlled laboratory conditions. Five temperature treatments (12, 16, 20, 24, and 28 °C) were selected based on the species’ natural occurrence period. The results showed that ephyrae exhibited stable growth and feeding at 20–24 °C, with a high survival rate of approximately 90%, indicating that this range represents the optimal thermal condition for the ephyra stage. At 28 °C, growth and feeding were highest among all treatments; however, survival declined sharply to 22.5%, suggesting that elevated temperature may impose physiological stress. In contrast, at 12 °C, both growth and feeding activity were markedly reduced, and survival decreased to 32.5%. These findings demonstrate that temperature is a key environmental factor influencing the physiological performance and survival of C. pacifica ephyrae. This study provides essential baseline data for understanding the early life-stage ecology of this species and contributes to improving predictions of jellyfish population dynamics and potential distribution shifts in East Asian marine ecosystems under future environmental change. Full article

The rapid growth of civilian unmanned aircraft systems (UAS) for various applications, such as logistics, inspection and surveillance has enabled increasingly complex UAS operations in shared airspace and in close proximity to third parties. European regulations for civilian UAS provide a comprehensive framework for operational approval, based on operational rules, risk-based approval processes, and airspace management concepts. While regulatory frameworks and current international standards provide detailed guidance for operational authorization for UAS, they do not prescribe how UAS should be developed and verified at a system and software level to support safety assurance in a structured and traceable manner. This paper addresses this gap by proposing a method for extracting system-level and software-level safety requirements from regulatory artifacts. The method interprets regulatory safety intent–expressed through operational constraints, mitigation measures, and robustness expectations–and translates it into development-relevant safety requirements under explicit operational assumptions. Building on these requirements, the paper introduces a software-centered system lifecycle for UAS development. The proposed lifecycle integrates regulatory safety intent, risk-proportionate assurance, and staged verification. Finally, through a cross-domain analysis, the paper positions the proposed approach relative to established practices from the automotive and the avionics domains, aiming to identify transferable and necessary adaptations for the development of unmanned aircraft systems. Full article

This study aims to explore the effects of micro-polluted river water on nitrogen and microbial communities of paddy field soil under different irrigation modes. The experiment was conducted in a water-saving park in Nanjing. By establishing three water quality conditions—clean water, micro-polluted river water, and alternating irrigation—and two moisture conditions—flood irrigation and controlled irrigation—this study investigates the effects of different irrigation patterns on soil nitrogen and microbial communities. The results indicate that, under flood irrigation, the input of micro-polluted river water can effectively alleviate NH₄⁺-N loss during the heading stages of rice growth by 49.3%. Moisture conditions are the primary factor influencing microbial community structure. Although the input of micro-polluted river water reduces community stability, rotation irrigation can increase microbial abundance and enhance network complexity, thereby enhancing the system’s resilience. Redundancy analysis shows that soil moisture, pH, and ion content are the key environmental factors driving microbial distribution. The clean and polluted water rotation irrigation model performs best in maintaining soil nitrogen and microbial health. Rotation irrigation promotes the enrichment of key functional groups, such as Actinobacteria, effectively increasing rice yield. This study provides a theoretical basis for promoting sustainable agricultural production through water resource management. Full article

NAC (NAM, ATAF1/2 and CUC2) transcription factors constitute one of the largest plant-specific transcription factor families and play pivotal roles in plant growth, development, and responses to environmental stresses. Systematic characterization of NAC genes is essential for understanding regulatory networks underlying key agronomic and adaptive traits. As a conservation-priority woody species with distinctive biological and horticultural value, Sinojackia xylocarpa Hu lacks comprehensive knowledge of its NAC repertoire, and elucidating its NAC family will facilitate functional studies related to development and environmental adaptation. Based on whole-genome data of S. xylocarpa, we conducted a systematic survey and characterization of the NAC transcription factor family. In total, 115 SxyNAC genes encoding the conserved NAC domain were identified, and their loci were unevenly distributed across 12 chromosomes. Analyses of gene-duplication modes and collinearity indicated that whole-genome/segmental duplication events were the major driving force for the expansion of this family. Phylogenetic relationships, gene structures, and conserved motifs classified the SxyNAC members into 15 subfamilies, revealing a highly conserved N-terminal NAC domain and a markedly diversified C-terminal regulatory region with pronounced member- and lineage-specific differences. Promoter cis-element prediction showed extensive enrichment of light-responsive, phytohormone-responsive, and stress-related elements, suggesting that SxyNAC genes may participate in coordinated regulation of multiple environmental cues and endogenous hormone pathways. Transcriptome data from six fruit developmental stages, together with qRT-PCR validation of ten representative genes, demonstrated diverse temporal and tissue-specific expression patterns during fruit development and close associations with fruit growth regulation. Overall, our findings establish a framework for exploring the evolutionary trajectories and functional diversification of NAC genes in S. xylocarpa, and they offer a valuable resource for NAC-family research and conservation-focused functional genomics in other rare or threatened plant species. Full article