Search Results (2,054)

Autonomous monitoring is essential for precision agriculture in greenhouses, yet deploying unmanned aerial vehicles (UAVs) in confined, GPS-denied environments remains limited by payload, power, and cost constraints. This study developed and validated an autonomous UAV system for reliable, low-cost operation in such conditions. The proposed system employs a dual-link edge-computing architecture: a lightweight onboard controller handles flight control and sensor acquisition, while visual simultaneous localization and mapping (V-SLAM) is offloaded to an edge computer via the FPV video link. Phenotyping (flower detection and tracking/counting) is performed offline from the side-view RGB stream and does not participate in the flight control loop. Using muskmelon (Cucumis melo L.) flower development as a case study, the UAV autonomously executed daily missions for 27 days in a commercial greenhouse, performing flower detection and tracking to monitor phenological dynamics. Localization and control accuracy were evaluated against a validated UWB reference system, achieving 5.4~8.0 cm 2D RMSE for trajectory tracking and 12.7 cm translation RMSE for greenhouse mapping. This work demonstrates a practical architecture for autonomous monitoring in GPS-denied agricultural environments, with operational boundaries characterized through the sustained field deployment. The system’s design principles may extend to other indoor or communication-limited scenarios requiring lightweight, intelligent robotic operation. Full article

In response to problems inherent in conventional hydraulic engineering education including compartmentalized courses, fragmented knowledge delivery, overlapping and omitted content, and insufficient development of students’ integrated practical competencies this study develops an instructional model for a coordinated curriculum group based on the OBE-BOPPPS teaching theory. The curriculum cluster model aims to integrate interdisciplinary course content, restructure curriculum structure hierarchy, eliminate disciplinary barriers, and establish clear stratified and interrelated knowledge relationships. The model centers on competency development, constructing a three-dimensional “agent–objective” system that connects “teacher–student–curriculum” with “knowledge–competency–literacy.” It further establishes a multi-indicator evaluation system encompassing teachers, students, and courses. The comprehensive evaluation employing Principal Component Analysis, Entropy Weight Method, and CRITIC method demonstrates that the curriculum group teaching model significantly outperforms traditional course-based instruction in transcending disciplinary boundaries, enhancing knowledge systematicity, improving teaching precision, and strengthening knowledge acquisition as well as students’ comprehensive competencies. This approach achieves dynamic optimization and precision feedback in the teaching process, effectively facilitating the systematic transfer of knowledge and the holistic development of students’ innovative practical abilities. It thereby provides a scientific pathway and empirical support for the reform of hydraulic engineering education and the cultivation of high-quality talent. Full article

Tripartite interaction among arbuscular mycorrhizal fungi (AMF), small grain cereals—including wheat, barley, oats, and rye—and pathogenic organisms constitute a highly complex ecological system with major implications for plant health, productivity and resilience. AMF colonization increases nutrient acquisition, particularly phosphorus and nitrogen, while concurrently priming host defense mechanisms that increase resistance to a broad spectrum of pathogens. These benefits, however, are strongly context-dependent and modulated by AMF species composition, host genotype, soil characteristics, and environmental conditions. AMF activate resistance pathways and modulate the rhizosphere microbiome, underscoring their central role in shaping plant–pathogen dynamics. Importantly, the relevance of these interactions extend beyond crop protection and yield stability to encompass food security and sustainability goals aligned with the One Health framework, which recognizes the interconnectedness of plant, environmental, and human health. Field implementation of AMF-based strategies has the potential to reduce reliance on chemical fertilizers and pesticides, thereby promoting sustainable cereal production, restoring soil biodiversity, and enhancing ecosystem services, with downstream benefits for human nutrition and environmental safety. This review integrates current knowledge on AMF–cereal–pathogen interactions, synthesizing mechanistic advances and applied perspectives while identifying critical knowledge gaps that must be addressed to effectively deploy AMF in resilient and sustainable agroecosystems within a One Health context. Full article

Background: Pumping in Laser-class sailing is a dynamic propulsion technique used in marginal wind conditions and characterized by repetitive, coordinated oscillations of the sailor–sail system. Despite its practical relevance, its biomechanical and ergonomic demands remain insufficiently characterized. Methods: A mixed-methods framework was applied combining questionnaire data, kinematic analysis, ergonomic assessment, and musculoskeletal modelling. Thirty-six competitive Laser sailors completed a Borg CR-10-based questionnaire on perceived discomfort/fatigue across body regions at predefined time points (during pumping, immediately after training, and the following day). A controlled land-based multi-angle video acquisition was used to reconstruct a standardized pumping posture and parameterize a digital human model in DELMIA^® for postural/kinematic analysis. Ergonomic risk was assessed using REBA, and muscle activity was estimated using the AnyBody^® Modeling System (simulation-derived normalized muscle activity across 129 muscles). Results: the simulation identified high neuromuscular demand in the trunk and shoulder complex, with several deep trunk stabilizers and the left latissimus dorsi reaching 100% modeled normalized muscle activity. Marked lateral asymmetry was observed, with right-sided trunk dominance and left-sided shoulder dominance. Kinematic analysis showed substantial joint excursions, with large lumbar motion amplitudes, while REBA yielded a score of 11 (Very-High Risk). Questionnaire data indicated a high prevalence of pumping-related musculoskeletal discomfort (72.2%), most frequently involving the lower back, shoulders, and knees. A dissociation was observed between modeled muscle activity and perceived fatigue, with the lower limbs rated as most fatigued despite lower modeled activation than the trunk. Conclusions: Findings identify the deep trunk stabilizers, latissimus dorsi, and lower extremities as key regions involved in pumping, with marked lateral asymmetry and high ergonomic risk. They support targeted training, injury-prevention, and ergonomic strategies to improve performance and reduce injury risk in competitive sailing. Full article

Cultural heritage buildings constitute an irreplaceable record of historical, social, and architectural identity, and their preservation is essential for cultural continuity and sustainable development. However, their conservation is inherently challenging due to material aging, complex construction techniques, limited documentation, and strict intervention constraints that restrict invasive monitoring or retrofitting solutions. Environmental degradation and microclimatic effects further accelerate deterioration, often in ways that are difficult to quantify or predict. This paper presents RADAR, a non-invasive, data-driven framework for assessing environmental and structural risk in cultural heritage buildings. The proposed approach integrates high-resolution geometric acquisition, computational fluid dynamics (CFD) modeling, and environmental monitoring to analyze airflow patterns, temperature distribution, and moisture-related decay mechanisms. By combining measured data with numerical simulations, RADAR enables the identification of high-risk zones and deterioration drivers without altering the building fabric. The framework is demonstrated through a real-world case study, illustrating its applicability as a decision-support tool for preventive conservation and heritage management. Full article

This study presents an integrated experimental and modeling framework to investigate human–robot collision dynamics involving a collaborative manipulator (KUKA LBR iiwa 14 R820). A dedicated impact test prototype was developed to reproduce controlled contact scenarios between the robot and human body analogues under various dynamic conditions. The experimental setup enables the acquisition of synchronized force, velocities, and displacement signals during contact events. These data are used to calibrate and validate a set of contact models, ranging from classical formulations such as Hertz and Hunt–Crossley to more recent supervised machine learning models. The proposed methodology allows a quantitative assessment of model accuracy and physical consistency in replicating real collision phenomena. Furthermore, the effective mass of the robot along its kinematic chain is estimated to compute impact energy and predict the interaction severity according to ISO 10218-1/2:2025 safety limits. The results highlight the trade-off between model complexity and predictive capability, offering alternative guidelines for collision severity evaluation in collaborative robotics applications. Full article

Music popularity prediction is a fundamental problem in music information retrieval, with important implications for digital content dissemination and creative decision-making on streaming platforms. In this study, music popularity prediction is formulated as a supervised regression problem, and six widely-used tree ensemble models (Random Forest, XGBoost, CatBoost, LightGBM, Extra Trees, and Decision Tree) are systematically evaluated using large-scale Spotify data. Among these models, Random Forest achieves the best predictive performance on this dataset (RMSE = 6.79, MAE = 5.10, and $R^2$ = 0.6658), followed by Extra Trees ($R^2$ = 0.6378) and Decision Tree ($R^2$ = 0.6328). Bayesian hyperparameter optimization based on a Tree-structured Parzen Estimator with an Expected Improvement acquisition function is conducted over 50 trials with 5-fold cross-validation to ensure robust model selection. Shapley value decomposition via SHAP analysis reveals that temporal recency dominates feature importance, far surpassing traditional musical attributes, while acoustic intensity (loudness) exhibits a U-shaped contribution pattern with optimal values at moderate intensity levels. Further SHAP dependence analysis uncovers non-linear relationships, indicating substantial popularity advantages for recent releases and optimal loudness levels around $-5$ to 0 dB. These findings suggest that streaming popularity is primarily governed by temporal exposure dynamics and production-related characteristics rather than intrinsic musical structure, offering both theoretical insights for music information retrieval research and suggestive empirical patterns that may inform future investigations into digital music ecosystems. Full article

Background/Objectives: Magnetite nanoparticles represent promising candidates for a broad spectrum of biomedical applications, ranging from in vitro diagnostic assays to in vivo imaging, hyperthermia, and targeted drug and gene delivery, with some nanoagents already approved for clinical use. A critical determinant of their functionality is the nanoparticle coating, which facilitates beneficial interactions within biological systems. In the context of tumor-targeted therapeutic delivery, key design parameters—particularly surface coatings—can be optimized to enhance treatment efficacy by modulating blood circulation kinetics, biodistribution, and other critical properties. However, current preclinical screening methods primarily rely on cell culture models to identify potential nanocarriers, yet these systems often poorly correlate with actual in vivo performance. This discrepancy highlights the necessity of incorporating more biologically relevant testing platforms, such as high-throughput in vivo assays. Methods: In this work, we employed an original magnetic particle quantification (MPQ) technology to systematically evaluate the blood circulation kinetics and biodistribution patterns for magnetite nanoparticles with 17 different coatings across multiple organs and tissues, including the liver, spleen, lungs, kidneys, heart, tumor, brain, peripheral blood, muscle, and bone. This methodology offers high sensitivity, user-friendly operation, and provides quantitative measurements across a broad dynamic range of nanoparticle concentrations. These advantages enabled high-throughput acquisition of precise blood circulation and biodistribution data. In addition, histological analysis was conducted to evaluate nanoparticle penetration depth within tumor tissue. Results: Here we conducted a comprehensive study of the effect of 17 different polymer-, lectin-, and small molecule-based coatings on the behavior of magnetite nanoparticles in vivo. For each type of obtained nanoparticles, we implemented passive targeting as well as magnetic targeting, the latter using an external magnetic field localized in the tumor area. Conclusions: The collected dataset provides critical insights into how surface modifications influence nanoparticle performance in complex biological systems, offering valuable guidance for optimizing therapeutic nanocarrier design. Full article

Different forest ecosystems affect the acquisition and loss of SOC by changing the niche differentiation of above-ground and under-ground, resulting in changes in the utilization efficiency of water and nutrient elements. The impact of different types of forests on carbon storage in forest soils has received significant attention in recent decades, as these ecosystems are critical for mitigating the effects of global climate change. There are significant differences in environmental factors among different types of forests, such as carbon source type, topographic characteristics, soil texture, microbial community status, climate and hydrological conditions. At present, the research on the effects of environmental factors such as climate, hydrological conditions or soil quality on SOC has been well carried out. Nevertheless, the distribution pattern of microbial carbon and particulate organic carbon in subtropical forest ecosystems and their contribution to SOC still need much of scientific research. Forest types have a significant impact on the content and distribution characteristics of MNC and particulate organic carbon fractions, but there is heterogeneity in different forests. Importantly, the random forest analysis showed that MNC and MAOC were the main factors affecting SOC compared with other variables, which indicated MNC and MAOC have higher relative importance to SOC (p < 0.05). Specifically, our research found that the total MNC and BNC content in natural forests and broad-leaved forests were significantly higher than that in coniferous forests (p < 0.05), while the FNC content and FNC/BNC in coniferous forests were significantly higher than that in the other two forests (p < 0.05). In addition, the MAOC content of natural forests was higher than others, which indicated the stability of natural forest is higher than other forests. However, CPOC, FPOC content, and POC/MAOC in coniferous forests were significantly higher than in broad-leaf forests and natural forests. Biotic and abiotic factors profoundly affect the dynamic changes in SOC accumulation and stability. Different environmental factors lead to more MNC and MAOC in forest types with faster decomposition rates. These findings have instructive implications for understanding the contributions of different forest types on SOC stability and accumulation mechanisms in forest soils. Full article

Phosphorus (P) is an essential macronutrient for plant growth and a major limiting factor for crop productivity, especially in tropical soils characterized by low P availability and high fixation capacity. The strong dependence of modern agriculture on non-renewable phosphate fertilizers, combined with their low use efficiency, raises economic and environmental concerns and reinforces the need to improve phosphorus use efficiency (PUE) in maize. PUE is a complex trait governed by integrated morphophysiological, biochemical, and molecular mechanisms related to phosphorus acquisition, internal remobilization, metabolic reprogramming, and root system plasticity. Recent advances using omics-based approaches have substantially expanded the understanding of these mechanisms, revealing coordinated regulation of carbon and energy metabolism, phosphatase activity, redox balance, and root meristem dynamics under P-limiting conditions. In parallel, increasing evidence demonstrates the important role of phosphate-solubilizing and plant growth-promoting bacteria in enhancing P availability through organic acid secretion, enzymatic mineralization of organic P forms, and modulation of root architecture. However, despite these advances, the genetic basis of plant responsiveness to beneficial bacteria and the interaction between host genotype and microbial activity remain poorly explored. This review integrates current knowledge on phosphorus dynamics in the soil–plant system, the genetic control of PUE in maize, and the contribution of beneficial bacteria, highlighting the importance of combining classical breeding, molecular approaches, and microbial strategies to accelerate the development of maize cultivars with improved phosphorus efficiency and reduced fertilizer dependency. Full article

The biospeckle laser (BSL) technique is recognized as a sensitive method for detecting biological activity and has been successfully applied for seed vigor testing. Given these achievements, whether the integration of BSL into automated systems can provide complementary information on the seed imbibition process remains limited. Addressing this gap represents a significant challenge with strong potential for technological innovation. This study presents an automated laser-optical system designed to monitor the imbibition process of multiple seeds over time using a mechanized carousel. The developed apparatus integrates all necessary components for the illumination and image acquisition of eight seeds across programmable time intervals, controlled by an industrial-grade programmable controller. Validation using maize seeds (Zea mays L.) over a 36-h period confirmed the system’s reliability. BSL indices enabled the characterization of internal biological activity throughout imbibition, revealing dynamic processes that remained undetected in previous discrete-time analyses. These results highlight the potential of the proposed system for more comprehensive and continuous seed monitoring. The successful automated laser-optical system with relative humidity control opens great potential in seeds research and daily industrial analysis. The test of the proposed system in other seeds is the next challenge, regarding the thick and colored coats. The design of larger carousels is a possible step forward, which will demand studies of the limits linked to the illumination and image acquisition time performed in each seed. Full article

Cardiovascular disease has become the leading cause of death worldwide, underscoring the urgent need for widespread cardiac monitoring, while the Electrocardiogram (ECG) remains the diagnostic gold standard, the complexity of its acquisition limits its long-term feasibility. In contrast, Photoplethysmography (PPG), ubiquitous in wearable devices, is increasingly adopted due to its accessibility. However, synthesizing ECG from PPG poses an intrinsically ill-posed inverse problem. Existing purely data-driven paradigms often neglect underlying biophysical mechanisms, resulting in a lack of physical constraints and interpretability, which renders them prone to generating non-physiological hallucinations. To address this, we propose PhysDiff-LBM, a novel physics-aware framework that incorporates Lattice Boltzmann hemodynamic constraints into a conditional diffusion model. Employing a dual-stream architecture, our framework captures high-frequency morphological details via a cross-attention-guided diffusion model with region-wise adaptability. Synergistically, we physically regularize the ECG synthesis by leveraging the mesoscopic streaming and collision operators of LBM. By forcing the synthesized waveform gradients to evolve consistently with hemodynamic momentum, this mechanism constrains the model to strictly adhere to the fluid dynamic conservation laws governing pulse wave propagation. Experimental results demonstrate that our method achieves superior signal fidelity and exhibits significant advantages in downstream clinical applications. Full article

Carbapenem-resistant Klebsiella pneumoniae (CRKP) sequence type 11 (ST11) is widely reported in Asia and represents an important clinical concern. Although antimicrobial resistance in ST11 isolates has been extensively investigated, less is known about the phenotypic characteristics and host-associated transcriptional responses of individual clinical isolates. In this study, we performed an in-depth characterization of a clinical ST11 CRKP isolate, NJGLYY4165. Phenotypic assays were used to evaluate bacterial growth, biofilm formation, serum resistance, inflammatory responses, and virulence in a Galleria mellonella infection model. Whole-genome sequencing and bacterial transcriptomic profiling were conducted to examine gene expression changes at 4 h during interaction with human intestinal epithelial cells and macrophages. NJGLYY4165 exhibited increased survival following exposure to normal human serum in vitro but displayed reduced lethality in the Galleria mellonella infection model compared with selected reference strains. Infection of host cells induced marked inflammatory responses. Transcriptomic analysis revealed extensive gene expression remodeling at the examined time point during host interaction, including upregulation of central metabolic pathways and iron acquisition systems, particularly under macrophage-associated conditions. This study provides a detailed phenotypic and single-time-point transcriptomic description of host-associated responses in a clinical ST11 CRKP isolate. The observed metabolic and iron acquisition responses may contribute to adaptation under host-associated conditions; however, because comparative analyses with non-ST11 or non-epidemic strains were not included, it remains unclear whether these features are isolate-specific, ST11-associated, or represent general adaptive responses of K. pneumoniae. Further comparative and time-course studies across diverse clinical isolates will be required to clarify temporal dynamics and broader epidemiological relevance. Full article

Professors, students, and researchers from universities around the world use software distributed under licenses for numerical simulation purposes, which requires a computer with considerable hardware capabilities. This implies a high cost of simulations in engineering applications that require dynamic modeling using numerical methods, particularly in robotics and nonlinear control. This article compares and analyzes the performance of a frugal simulation scheme based on the use of low-cost, free, and open-source technology, specifically a low-power, single-board minicomputer (Raspberry Pi) in conjunction with GNU-Octave software. The benchmark is a numerical simulation of trajectory tracking control in the joint space of a Selective Conformal Assembly Robot Arm (SCARA). To perform this task, a system of coupled nonlinear differential equations is solved in matrix form using a numerical method known as an ODE solver. This solution includes the control law and the dynamic system model derived from Euler–Lagrange formalism. The time complexity and accuracy are analyzed to compare the performance of the frugal simulation tool with that of a conventional simulation setup consisting of a personal computer and MATLAB^TM running the same simulation code. The analysis shows minimal deviations in the numerical solutions and reasonable time complexity. Moreover, the frugality score of this approach and the low acquisition cost of the simulation tool enable the creation of simulation laboratories at universities with limited budgets for education and research. Full article

Background: Bucket-wheel excavators are critical assets in surface mining operations, where structural modifications to increase productivity must be validated through rigorous stress analysis to ensure operational safety. Following modification of an ERc 1400-30/7 excavator’s bucket wheel from 18 to 20 buckets, increased operational loads necessitated experimental verification of structural integrity. Methods: A custom 10-channel strain-gauge data acquisition system with 0–10 kHz bandwidth measured stresses in cable anchoring lugs and H-type diagonal members under operational conditions at the Jilț lignite mine, Romania. Measurements were performed during both left and right bucket-wheel rotation. Finite element analysis validated experimental results. Results: Maximum equivalent stresses of 210.0 MPa and 167.1 MPa were measured in the left and right anchoring lugs, respectively, during left bucket-wheel rotation, representing 59% and 47% of material yield strength with safety factors of 1.69 and 2.12. Significant load asymmetry was observed, with left rotation inducing 220–284% higher stresses than right rotation. FEA validation showed <15% agreement with measurements. Dynamic stress amplification of 15–32% above quasi-static values was attributed to bucket–soil interaction and structural vibration. Conclusions: Despite increased operational loads, measured stresses remain below yield strength, confirming structural adequacy. Both anchoring lugs require prioritized monitoring due to elevated stress levels and load asymmetry. The validated methodology provides a framework for post-modification verification of large mining equipment. Full article