Search Results (309)

Modern sequencing technologies have transformed the identification of medicinal plant species and varieties, overcoming the limitations of traditional approaches. To address the challenge of discriminating Toona sinensis varieties, we sequenced and compared 15 complete chloroplast genomes from five varieties in northern China. Although these genomes exhibited a highly conserved structure, we identified eight variety-specific simple sequence repeats (SSRs), two unique tandem repeats, and several hypervariable regions with elevated nucleotide diversity. Phylogenetic analysis demonstrated that whole chloroplast genomes provided the highest resolution for variety identification, outperforming conventional barcodes. Furthermore, we developed 13 specific primer pairs targeting variable regions, and PCR validation confirmed their reliable amplification across varieties. In addition, sequence-level validation by Sanger sequencing of representative SSR and tandem repeat markers revealed stable, variety-specific repeat copy number differences. These results demonstrate that the identified chloroplast markers can effectively discriminate closely related T. sinensis varieties. This study confirms that despite overall conservation, the T. sinensis plastome contains sufficient variation for reliable identification, providing a robust framework for future germplasm conservation and molecular breeding. Full article

Historical landslide inventory serves as a critical tool for analyzing landslide activity patterns and evaluating the long-term geological impacts of triggering events, including earthquakes, extreme weather events, and large-scale infrastructure projects. Although various methods—including visual interpretation, heuristic approaches, machine learning, and deep learning models—have been employed for landslide detection, efficient techniques for historical landslide mapping remain understudied. As a result, comprehensive historical landslide inventories continue to be scarce worldwide. In this study, we developed an advanced landslide detection model using a Swin Transformer architecture integrated with a Pyramid Segmentation Attention mechanism. Subsequently, we applied a network fine-tuning method to achieve cross-domain adaptation, enabling the reconstruction of a decadal-scale landslide inventory across the Wenchuan earthquake-affected region efficiently. Experimental results from the Wenchuan earthquake area demonstrate the proposed approach’s superior temporal transfer mapping performance compared to state-of-the-art models. The proposed historical map also exhibits high accuracy and completeness, offering significant value for analyzing landslide spatiotemporal activity and long-term regional stability. Findings reveal that landslides stabilized overall between 2008 and 2021, with key influences including altitude, slope, and aspect. The results lay the groundwork for regional stability analysis and eco-environment recovery, enabling informed decisions in urban planning and infrastructure investments. Full article

Building a sustainable and resilient humanitarian logistics system is essential for reducing disaster losses and supporting long-term socio-economic recovery. Following a major disaster, rapidly organizing casualty evacuation while maintaining system robustness is a fundamental component of sustainable emergency management. This study develops a two-stage robust optimization model for designing a sustainable humanitarian logistics network that simultaneously accounts for two critical post-disaster uncertainties: (i) interruption risks at temporary medical points and (ii) uncertain casualty demand. By explicitly differentiating deprivation costs between mild and serious injuries, the model quantifies human suffering in monetary terms, thereby integrating social and economic sustainability considerations into the optimization framework. A customized column-and-constraint generation (C&CG) algorithm with proven finite convergence is proposed to ensure tractability and practical applicability. Using the 2008 Wenchuan earthquake as a real-world case study, involving 10 affected areas and 10 candidate temporary medical points, the results demonstrate that the proposed approach yields evacuation plans that remain feasible under all tested worst-case realizations, substantially reducing deprivation costs compared with existing benchmarks. The findings highlight that strategically increasing the capacity of key temporary medical nodes enhances the sustainability and resilience of the emergency medical system, offering evidence-based insights for designing sustainable and robust disaster-response strategies. Full article

Accurate daily runoff forecasting is essential for flood control and water resource management, yet existing models struggle with the seasonal non-stationarity and inter-basin variability of runoff sequences. This paper proposes a Season-Aware Ensemble Forecasting (SAEF) method that integrates SVM, LSSVM, LSTM, and BiLSTM models to leverage their complementary strengths in capturing nonlinear and non-stationary hydrological dynamics. SAEF employs a seasonal segmentation mechanism to divide annual runoff data into four seasons (spring, summer, autumn, winter), enhancing model responsiveness to seasonal hydrological drivers. An Improved Arctic Puffin Optimization (IAPO) algorithm optimizes the model weights, improving prediction accuracy. Beyond numerical gains, the framework also reflects seasonal runoff generation processes—such as rapid rainfall–runoff in wet seasons and baseflow contributions in dry periods—providing a physically interpretable perspective on runoff dynamics. The effectiveness of SAEF was validated through case studies in the Dongjiang Hydrological Station (China), the Elbe River (Germany), and the Quinebaug River basin (USA), using four performance metrics (MAE, RMSE, NSEC, KGE). Results indicate that SAEF achieves average Nash–Sutcliffe Efficiency Coefficient (NSEC) and Kling–Gupta efficiency (KGE) coefficients of over 0.92, and 0.90, respectively, significantly outperforming individual models (SVM, LSSVM, LSTM, BiLSTM) with RMSE reductions of up to 58.54%, 55.62%, 51.99%, and 48.14%. Overall, SAEF not only strengthens predictive accuracy across diverse climates but also advances hydrological understanding by linking data-driven ensembles with seasonal process mechanisms, thereby contributing a robust and interpretable tool for runoff forecasting. Full article

For runoff-generated debris flow continuum mechanics-based early warning models, the computational unit must satisfy the homogeneity assumption of continuum mechanics. Although traditional grid cells meet the homogeneity assumption as computational units, they segment channel geomorphological functional reaches, weaken the clustered mobilization of sediment sources, and constrain efficiency due to grid-by-grid calculations. To address these limitations, we construct a Froude number ($Fr$) calculation model constrained by key factors such as the channel cross-sectional geometry and topographic parameters. The absolute deviation of $Fr$ is used as a criterion for homogeneity within the computational unit. By combining critical shear stress theory and velocity perturbation, physical thresholds for the criteria are derived. A physical model-based method for automatically delineating homogeneous channel units (${CU}_j$) is proposed, ensuring that the geometric features and hydrodynamic parameters within ${CU}_j$ are homogeneous, while ensuring heterogeneity between adjacent ${CU}_j$. Comprehensive multi-scale validation in Yeniu Gully, a typical debris flow catchment in Wenchuan County, demonstrates that parameters such as longitudinal gradient, cross-sectional area, flow depth, and shear stress remain relatively homogeneous within each ${CU}_j$ but differ significantly between adjacent ${CU}_j$. Furthermore, the proposed method can stably characterize key channel geomorphological functional units, such as bends, confluences, abrupt width changes, longitudinal gradient changes, erosion segments, and deposition segments. Sensitivity analysis demonstrates that the method satisfies both robustness and universality under various conditions of rainfall intensity, runoff coefficient, and Manning’s roughness coefficient. Even under the most unfavorable extreme conditions, the accuracy of ${CU}_j$ delineation exceeds 88.64%, indicating high reliability and suitability for deployment in various debris flow catchments. The proposed framework for defining ${CU}_j$ resolves the conflict in traditional computational units between the “continuum model homogeneity requirement” and “geomorphological functional unit continuity,” providing a more rational and efficient computational environment for runoff-generated debris flow continuum mechanics-based early warning models. Full article

This study examines the roles, policy alignment, and challenges of civil society organizations (CSOs) in China’s disaster risk reduction (DRR) efforts post-2008 Wenchuan Earthquake. Using qualitative analysis of national policies, international frameworks, and academic literature, it traces the evolution of Chinese CSOs from peripheral actors to state-integrated partners in disaster risk governance. Findings reveal that China’s top-down system has progressively institutionalized CSOs through Five-Year Plans, enabling their participation in emergency response and community resilience by using technological innovation. However, their contributions remain skewed toward short-term relief, with limited engagement in risk reduction or global humanitarian initiatives. Challenges include fragmented government–CSO collaboration and reliance on informal networks. While CSOs demonstrate growing technical proficiency, systemic barriers—such as funding gaps, weak institutionalized partnerships, and ideological divergences—hinder sustainability. Recommendations emphasize capacity building in risk education, policy literacy, and technology adoption, alongside reforms to formalize cross-sector collaboration and expand international engagement. By addressing these gaps, Chinese CSOs could transition from crisis responders to proactive agents of sustainable resilience, aligning local actions with global DRR agendas. This research offers critical insights for policymakers and practitioners seeking to optimize CSOs’ role in national and local risk governance and invest in their development. Full article

Pedestrian trajectory prediction from a vehicle-mounted perspective is essential for autonomous driving in complex urban environments yet remains challenging due to ego-motion jitter, frequent occlusions, and scene variability. Existing approaches, largely developed for static surveillance views, struggle to cope with continuously shifting viewpoints. To address these issues, we propose V-PTP-IC, an end-to-end framework that stabilizes motion, models inter-agent interactions, and fuses multi-modal cues for trajectory prediction. The system integrates Simple Online and Realtime Tracking (SORT)-based tracklet augmentation, Scale-Invariant Feature Transform (SIFT)-assisted ego-motion compensation, graph-based interaction reasoning, and multi-head attention fusion, followed by Long Short-Term Memory (LSTM) decoding. Experiments on the JAAD and PIE datasets demonstrate that V-PTP-IC substantially outperforms existing baselines, reducing ADE by 27.23% and 25.73% and FDE by 33.88% and 32.85%, respectively. This advances dynamic scene understanding for safer autonomous systems. Full article

Spatial pattern analysis is essential for understanding forest structure and successional dynamics. Focusing on natural secondary forests in the subalpine region of western Sichuan, China, we established two 1-hectare permanent plots to investigate the spatial distribution of dominant tree species and assess the soil’s water-holding properties, aiming to clarify the relationship between species spatial patterns and edaphic conditions. The pioneer species Betula albosinensis exhibited a unimodal diameter distribution with scarce seedling presence, indicating limited regeneration. In contrast, Abies fargesii var. faxoniana showed a typical inverse J-shaped diameter distribution, suggesting stable population recruitment. At fine spatial scales, dominant species generally exhibited aggregated distributions, with A. fargesii var. faxoniana seedlings showing the strongest clumping; however, as the spatial scale increased, distributions tended toward randomness, likely due to self-thinning and density-dependent interactions. Bivariate spatial association analysis revealed that B. albosinensis was positively associated with A. fargesii var. faxoniana and Picea asperata at small scales, suggesting a potential facilitative effect of B. albosinensis on Pinaceae species. Moreover, capillary water-holding capacity was significantly higher in areas with greater conifer dominance, underscoring the strong environmental filtering effect of microhabitat moisture on community spatial structure. Collectively, our results suggest an ongoing mid- to late-successional shift from pioneer broadleaved to shade-tolerant conifer dominance, with concurrent changes in species composition and soil conditions. This study provides empirical insight into spatial successional processes and highlights their ecological implications for hydrological regulation in subalpine secondary forests. Full article

Morphological plasticity (MP) is an essential strategy for plants in nutrient acquisition, disturbance alleviation, and community coexistence during environmental and climatic changes. However, to date, there has been little research concerning the MP for alpine–subalpine forests on the Qinghai–Tibet plateau. These forests are representative of the ectomycorrhizal (ECM) type, and morphological traits of these ECM roots, such as root tip lengths, diameters, and their adherent hyphal lengths and exploration types, have rarely been studied in the context of nutrient and environmental gradients. In this study, we examined the morphological traits of ECM roots for faxon fir (Abies fargesii var. faxoniana), which dominated in subalpine forests across nine elevations on the Eastern Qinghai–Tibet plateau. By quantifying ca. 90,000 root tips, the hyphal lengths of ectomycorrhizal extraradical mycelium (EEM, i.e., short- and long-distance exploration types) reached up to 1.1 × 10⁶ cm/m³ in soil, which decreased significantly due to gradually increasing altitude. In contrast, the variability of ECM root traits (diameter, length, and superficial area) was highly conserved along the altitudinal gradients, yet the root tip lengths were positively associated with soil protease enzyme activity. The increase in diameter and length of ECM root tips was climate-independent yet significantly associated with increasing root N concentration. In the studied forests, a long-distance exploration type of ECM hyphae was controlled by precipitation (p < 0.05), whereas the short-distance one was controlled by precipitation and temperature simultaneously. The EEM lengths of short- and long-distance exploration types were associated with high C concentration and low N concentration in host tree root tissues. Our findings demonstrated that MP expression in nutrient-foraging strategies for the dominant coniferous trees facilitates the adaptation to changing environments by specialized hyphal structures. In conclusion, ECM root tips and hyphal structures are two dimensions of functional traits linked to root N concentration in opposite ways, and their MP collectively ensures the temporal stability and resistance of subalpine forests on the Qinghai–Tibet plateau. These results provide new insights into ECM morphological traits and their adaptation in changing environments, which is valuable for understanding responses of subalpine forests to climate change. Full article

When a highway overlies a goaf, the cracking and subsidence of the highway subgrade seriously threaten the safe operation and maintenance of highways, including passenger safety. In this study, subgrade subsidence in the operation period of the G0611 Zhangye–Wenchuan Expressway from Biandukou to Menyuan was analyzed. First, the main factors influencing this kind of subsidence were analyzed using theoretical analysis, field investigation, and field detection. Then, an index system for these factors was constructed, composed of one target-layer, five criterion-layer, and seventeen indicator-layer indexes. The ANP and CRITIC methods were used to calculate the subjective and objective weights of each influencing factor index. The combined weights were obtained based on game theory, and the contribution degree of each index was determined. The primary and secondary relationships of the influencing factors of subgrade subsidence were inferred. The research results indicate that the foundation of the analyzed expressway section contains goaf areas, with poor filling performance, failure to fill in layers according to regulations, and poor drainage being the main reasons for subgrade subsidence. Based on the contribution degree of the indicator-layer influencing factors, high-energy-level dynamic compaction can be used to ram goafs so as to ensure the operational safety of the expressway. Full article

Three-dimensionally ordered macroporous (3DOM) La₂O₃-supported Ni catalysts exhibit outstanding performance for methane dry reforming (DRM). The 5Ni/La₂O₃-3DOM catalyst achieves 79% CH₄ and 84% CO₂ conversions at 800 °C under the reaction conditions of atmospheric pressure, CH₄:CO₂ molar ratio of 1:1, and gas hourly space velocity (GHSV) = 36,000 mL·gcat⁻¹·h⁻¹, outperforming its counterparts (5Ni/La₂O₃-PP prepared by means of co-precipitation and 5Ni/La₂O₃-GNC prepared by means of glycine–nitrate combustion) by 15–20%. Long-term stability tests at 700 °C (same CH₄:CO₂ ratio and GHSV as above) show that the 5Ni/La₂O₃-3DOM catalyst maintains CH₄ and CO₂ conversions at approximately 80% and 85%, respectively, with zero deactivation over 50 h. Meanwhile, its carbon deposition rate plummets to 1.1 mg·g⁻¹·h⁻¹, which is 75% lower than that of the precipitation-derived 5Ni/La₂O₃-PP catalyst. This excellent performance stems from the synergy of nano-confined Ni particles (11.2 nm in crystallite size after reduction) and abundant surface oxygen species (38 μmol·g⁻¹), establishing 3DOM La₂O₃ as a superior anti-coking support platform for scalable H₂ production via DRM. Full article

To address the overvoltage problem in distribution networks with large-scale photovoltaic (PV) integration, this paper proposes an interactive game-based voltage optimization control strategy based on microgrid cluster partitioning. A multi-agent control architecture is constructed, including a dynamic partitioning layer, a parallel independent optimization layer, and an interactive game optimization layer. In the dynamic partitioning layer, microgrid clusters are formed considering coupling degree, voltage regulation capability, and cluster scale. In the parallel optimization layer, a network reconfiguration-based control model is established for utility-owned microgrids, and a PV active/reactive power regulation model is developed for PV microgrids, enabling independent cluster-level control. In the game optimization layer, a non-cooperative game model is formulated to coordinate voltage regulation among clusters. The effectiveness of the proposed method is demonstrated on an actual 10 kV feeder system. Full article

Expansion microscopy (ExM) enables conventional light microscopes to achieve nanoscale resolution by physically enlarging biological specimens. While ExM has been widely applied in neurobiology, it has not been adapted for the enteric nervous system (ENS). Here, we provide a detailed and reproducible protocol for applying ExM to mouse colonic ENS tissue. The procedure includes preparation of the external muscle layers with the myenteric plexus, histochemical staining for NADPH-diaphorase, immunostaining for glial fibrillary acidic protein (GFAP), anchoring of biomolecules, gelation, proteinase K digestion, and isotropic expansion in a swellable polymer matrix. Step-by-step instructions, required reagents, and critical parameters are described to ensure robustness and reproducibility. Using this protocol, tissues expand 3–5-fold, allowing neuronal somata, fibers, and glial cell processes to be clearly visualized by standard brightfield or fluorescence microscopy. The tissue architecture is preserved, with distortion in the X–Y plane of about 7%. This protocol provides a reliable framework for high-resolution structural analysis of the ENS and can be readily adapted to other peripheral tissues. Full article

A novel multi-degree-of-freedom bionic Soft Pneumatic Actuator (SPA) inspired by the shoulder joint of a sea turtle is proposed. The SPA is mainly composed of a combination of oblique chamber actuator units capable of omnidirectional bending and bi-directional twisting, which can restore the multi-modal motions of a sea turtle’s flipper limb in three-dimensional space. To address the nonlinear behavior of the complex structure of SPA, traditional modeling is difficult. The attitude information of each axis of the actuator is extracted in real time using a high-precision Inertial Measurement Unit (IMU), and the attitude outputs of the SPA are modeled using six machine learning methods. The results show that the XGBoost model performs best in attitude modeling. Its R² can reach 0.974, and the average absolute errors of angles in Roll, Pitch, and Yaw axes are 1.315°, 1.543°, and 1.048°, respectively. The multi-axis attitude of the SPA can be predicted with high accuracy in real time. The studies on deformation capability, actuation output performance, and underwater validation experiments demonstrate that the SPA meets the bionic sea turtle shoulder joint requirements. This study provides a new theoretical foundation and technical path for the development, control, and bionic application of complex multi-degree-of-freedom SPA systems. Full article

Pseudostellaria heterophylla, a dual-purpose medicinal and edible herb, has shown significant pharmacological potential, particularly through its immunomodulatory and antitumor activities. This review provides insights into the phytohormone regulatory mechanisms and active-component biosynthesis, highlighting key metabolic pathways and yield-optimization strategies. The interactions between hormones and genes in root morphology and metabolite accumulation are discussed, offering new perspectives for molecular breeding. Additionally, a multidisciplinary framework is proposed to address cultivation challenges and quality enhancement, laying the groundwork for sustainable utilization of this valuable medicinal plant. Full article