Search Results (3,276)

With the expansion of muskmelon cultivation, manual pollination is increasingly inadequate for sustaining industry development. Therefore, the development of automatic pollination robots holds significant importance in improving pollination efficiency and reducing labor dependency. Accurate flower detection and localization is a key technology for enabling automated pollination robots. In this study, the YOLO-MDL model was developed as an enhancement of YOLOv7 to achieve real-time detection and localization of muskmelon flowers. This approach adds a Coordinate Attention (CA) module to focus on relevant channel information and a Contextual Transformer (CoT) module to leverage contextual relationships among input tokens, enhancing the model’s visual representation. The pollination robot converts the 2D coordinates into 3D coordinates using a depth camera and conducts experiments on real-time detection and localization of muskmelon flowers in a greenhouse. The YOLO-MDL model was deployed in ROS to control a robotic arm for automatic pollination, verifying the accuracy of flower detection and measurement localization errors. The results indicate that the YOLO-MDL model enhances AP and F1 scores by 3.3% and 1.8%, respectively, compared to the original model. It achieves AP and F1 scores of 91.2% and 85.1%, demonstrating a clear advantage in accuracy over other models. In the localization experiments, smaller errors were revealed in all three directions. The RMSE values were 0.36 mm for the X-axis, 1.26 mm for the Y-axis, and 3.87 mm for the Z-axis. The YOLO-MDL model proposed in this study demonstrates strong performance in detecting and localizing muskmelon flowers. Based on this model, the robot can execute more precise automatic pollination and provide technical support for the future deployment of automatic pollination robots in muskmelon cultivation. Full article

The abandoned goaf resulting from coal resource integration in China poses a significant threat to coal mine safety. The transient electromagnetic method (TEM) has emerged as a crucial technology for detecting goafs in coal mines due to its adaptable equipment and efficient implementation. In recent years, small-loop TEM has demonstrated high resolution and adaptability in challenging terrains with vegetation, such as coal mine ponding areas, karst regions, and reservoir seepage scenarios. By considering the sedimentary characteristics of coal seams and addressing the resistivity changes encountered in single-point inversion, a joint optimization inversion process incorporating lateral weighting factors and vertical roughness constraints has been developed to enhance the connectivity between adjacent survey points and improve the continuity of inversion outcomes. Through an OCCAM inversion approach, the regularization factor is dynamically determined by evaluating the norms of the data objective function and model objective function in each iteration, thereby reducing the reliance of inversion results on the initial model. Using the Xiaolong Coal Mine as a geological context, the impact of lateral and vertical weighting factors on the inversion outcomes of high- and low-resistivity structural models is examined through a control variable method. The analysis reveals that optimal inversion results are achieved with a combination of a lateral weighting factor of 0.5 and a vertical weighting factor of 0.1, ensuring both result continuity and accurate depiction of vertical and lateral electrical interfaces. The practical application of this approach validates its effectiveness, offering theoretical support and technical assurance for old goaf detection in coal mines, thereby holding significant engineering value. Full article

Inspection, maintenance, and repair (IMR) operations on underwater infrastructure remain costly and time-intensive because fully teleoperated remote operated vehicle s(ROVs) lack the range and dexterity necessary for precise cooperative underwater manipulation, and the alternative of using professional divers is ruled out due to the risk involved. This work presents and experimentally validates an autonomous, dual-I-AUV (Intervention–Autonomous Underwater Vehicle) system capable of assembling rigid pipeline segments through coordinated actions in a confined underwater workspace. The first I-AUV is a Girona 500 (4-DoF vehicle motion, pitch and roll stable) fitted with multiple payload cameras and a 6-DoF Reach Bravo 7 arm, giving the vehicle 10 total DoF. The second I-AUV is a BlueROV2 Heavy equipped with a Reach Alpha 5 arm, likewise yielding 10 DoF. The workflow comprises (i) detection and grasping of a coupler pipe section, (ii) synchronized teleoperation to an assembly start pose, and (iii) assembly using a kinematic controller that exploits the Girona 500’s full 10 DoF, while the BlueROV2 holds position and orientation to stabilize the workspace. Validation took place in a 12 m × 8 m × 5 m water tank. Results show that the paired I-AUVs can autonomously perform precision pipeline assembly in real water conditions, representing a significant step toward fully automated subsea construction and maintenance. Full article

Understanding the alterations to the shoot and root traits of rapeseed (Brassica napus) in response to salt stress is vital for improving its ability to thrive in saline-prone regions. This research aims to evaluate the responses of shoot and root traits of rapeseed at the vegetative stage under salt- and salicylic acid-induced stress in hydroponic culture. Five parents and ten F₃ segregants of rapeseed were subjected to three treatments: T1: control, T2: 8 dSm⁻¹ salt, and T3: 8 dSm⁻¹ salt + 0.1 mM salicylic acid at 21 days of age. Salinity stress significantly reduced the estimated root surface area by 54% compared to control, highlighting the plasticity of roots under stress. The simultaneous application of salt and SA did not alleviate the salinity stress, but rather reinforced the degree of stress and decreased the number of leaves, diameter of the main axis, chlorophyll content, and estimated root surface area by 18.5%, 15.4%, 38.8%, and 23%, respectively, compared to T2. The parental genotype M-245 followed by F₃ genotype M-232×M-223 accounted for the higher overall estimated root surface area. These results provide novel insights into the responses of root traits in rapeseed breeding lines under dual treatment, which hold promising implications for future rapeseed breeding efforts focused on sustainable rapeseed production. Full article

Microbial feed additives can effectively promote the healthy development of aquaculture, and Lactobacillus acidophilus can be utilized to mitigate disease risks and enhance productivity while minimizing antibiotic use. This article summarizes research on the application of L. acidophilus in aquaculture, focusing on growth and nutrient utilization, intestinal structure and microbial communities, disease prevention and control in aquatic organisms, and the regulation of water quality. This review holds significant implications for the development of compound feed additives and environmental regulators involving L. acidophilus, as well as for future aquatic food safety. Full article

Background: The role of collagen membrane fixation during guided bone regeneration (GBR) remains debatable, particularly in post-extraction sockets with buccal defects and concomitant immediate implant placement. This study evaluated whether or not fixation with titanium pins improved regenerative outcomes. Methods: Six adult Beagle dogs received bilateral extractions of the fourth mandibular premolars. An implant was immediately placed in both the distal alveoli, and standardized buccal bone defects (5 mm height, 3–2 mm width) were prepared. All defects were filled with a slowly resorbing equine xenograft and covered by a resorbable pericardium membrane. At the test sites, the membrane was apically fixed with pins, while no fixation was applied to the control sites. After 3 months of healing, histomorphometric analyses were performed. Results: The vertical bone gain of the buccal crest was 3.2 mm in the test sites (pin group) and 2.9 mm in the control sites (no-pin) (p > 0.754). No significant difference was found in terms of bone-to-implant contact (BIC). However, residual graft particles were located significantly more coronally in the pin group compared to the no-pin group (p = 0.021). Morphometric analyses revealed similar new bone formation within the groups, but with higher amounts of residual xenograft and soft tissue in the pin group. Conclusions: Membrane fixation did not significantly enhance vertical bone gain, and although the slightly higher regeneration in the pin group (3.2 mm vs. 2.9 mm) may hold clinical relevance in esthetically sensitive areas and osseointegration, it appeared to limit coronal migration of the grafting material. Full article

Research on reliability control for enhancing power systems under random loads holds significant and undeniable importance in maintaining system stability, performance, and safety. The primary challenge lies in determining the reliability index while optimizing system parameters. To effectively address this challenge, we developed a novel intelligent algorithm and conducted an optimal reliability assessment for a Negative Stiffness Device (NSD) seismic isolation structure incorporating fractional-order damping. This algorithm combines the Gaussian Radial Basis Function Neural Network (GRBFNN) with the Particle Swarm Optimization (PSO) algorithm. It takes the reliability function with unknown parameters as the objective function, while using the Backward Kolmogorov (BK) equation, which governs the reliability function and is accompanied by boundary and initial conditions, as the constraint condition. During the operation of this algorithm, the neural network is employed to solve the BK equation, thereby deriving the fitness function in each iteration of the PSO algorithm. Then the PSO algorithm is utilized to obtain the optimal parameters. The unique advantage of this algorithm is its ability to simultaneously achieve the optimization of implicit objectives and the solution of time-dependent BK equations.To evaluate the performance of the proposed algorithm, this study compared it with the algorithm combines the GRBFNN with Genetic Algorithm (GA-GRBFNN)across multiple dimensions, including performance and operational efficiency. The effectiveness of the proposed algorithm has been validated through numerical comparisons and Monte Carlo simulations. The control strategy presented in this paper provides a solid theoretical foundation for improving the reliability performance of mechanical engineering systems and demonstrates significant potential for practical applications. Full article

Background/Objectives: Nutraceuticals containing milk fat globule membranes (MFGMs) and extracellular vesicles (EVs) are purported to abate age-related metabolic dysfunction due to their richness in milk sphingolipids. As such, nutraceuticals offer a compelling strategy to improve metabolic health through dietary means, especially for elderly persons who are unable to adhere to common therapeutic interventions. To address this, we examined the effects of supplementing aged sedentary rats with an MFGM/EV-rich concentrate. Methods/Results: In a 25-week study, 89-week-old male rats received either a milk sphingolipid-rich MFGM/EV concentrate or a control supplement. Analysis of metabolic health using a battery of tests, including MS^ALL lipidomics of plasma, liver, and other peripheral tissues, revealed that MFGM/EV supplementation promotes accretion of unique sphingolipid signatures, ameliorates ceramide biomarkers predictive of cardiovascular death, and has a general lipid-lowering effect. At the functional level, we find that these health-promoting effects are linked to increased lipoprotein particle turnover, showcased by reduced levels of triglyceride-rich particles, as well as a metabolically healthier liver, assessed using whole-body lipidomic flux analysis. Conclusions: Altogether, our work unveils that MFGM/EV-containing food holds a potential for ameliorating age-related metabolic dysfunction in elderly individuals. Full article

I use Shakespeare to teach acting to students. A key to my work is impression management: what Shakespeare called reputation. I view the management of reputation as a route into Shakespearean character, which I present to students as a mask attuned to sacred values. The physical basis from which the actor can discover the mask is what Hamlet calls ‘smoothness’, which I explain with an acting exercise. We discover the force of sacred values by noticing the ubiquity of keywords in the text such as honor, virtue, reason, shame and faith. By holding characters to the fire of their sacred values, I shift the actor’s attention from an individualist idea of authentic representation towards a sense of character as a battleground of mind-shaping. The resulting performance work is scaled up to a more expansive and energized degree than the actor may be used to delivering in a social media-saturated environment in which what is often prioritized is a quasi-confessional self-revelation. The revelation of an inner life then emerges through a committed exploration of antithetical relations, a strategy basic both to mask work and to Shakespeare’s poetics. The actor finds their personal connection to the material by facing the contradiction between the objective standards of behavior demanded of the character and the character’s attempt to control their status, that is, how they are seen. The final value of the performance work is that the actor learns how to manage their reputation so that they come to appear like a giant who is seen from a distance. Full article

The detection of proteins plays a key role in disease diagnosis and drug development. For this, we numerically investigated a novel microfluidic motor actuated by an induced-charge electro-osmotic (ICEO) whirling flow. An alternating current–flow field effect transistor is engineered to modulate the profiles of ICEO streaming to stimulate and adjust the whirling flow in the circle microfluidic chamber. Based on this, we studied the distribution of an ICEO whirling flow in the detection chamber by tuning the fixed potential on the gate electrodes by the simulations. Then, we established a fluid–structure interaction model to explore the influence of blade structure parameters on the rotation performance of microfluidic motors. In addition, we investigated the rotation dependence of microfluidic motors on the potential drop between two driving electrodes and fixed potential on the gate electrodes. Next, we numerically explored the capability of these microfluidic motors for the detection of low-abundance proteins. Finally, we studied the regulating effect of potential drops between the driving electrodes on the detection performance of microfluidic motors by numerical simulations. Microfluidic motors actuated by an ICEO whirling flow hold good potential in environmental monitoring and disease diagnosis for the outstanding advantages of flexible controllability, a simple structure, and gentle work condition. Full article

The integration of digital twin technology with robotic automation holds significant promise for advancing sustainable horticulture in controlled environment agriculture. This article presents DigiHortiRobot, a novel AI-driven digital twin architecture tailored for hydroponic greenhouse systems. The proposed framework integrates real-time sensing, predictive modeling, task planning, and dual-arm robotic execution within a modular, IoT-enabled infrastructure. DigiHortiRobot is structured into three progressive implementation phases: (i) monitoring and data acquisition through a multimodal perception system; (ii) decision support and virtual simulation for scenario analysis and intervention planning; and (iii) autonomous execution with feedback-based model refinement. The Physical Layer encompasses crops, infrastructure, and a mobile dual-arm robot; the virtual layer incorporates semantic modeling and simulation environments; and the synchronization layer enables continuous bi-directional communication via a nine-tier IoT architecture inspired by FIWARE standards. A robot task assignment algorithm is introduced to support operational autonomy while maintaining human oversight. The system is designed to optimize horticultural workflows such as seeding and harvesting while allowing farmers to interact remotely through cloud-based interfaces. Compared to previous digital agriculture approaches, DigiHortiRobot enables closed-loop coordination among perception, simulation, and action, supporting real-time task adaptation in dynamic environments. Experimental validation in a hydroponic greenhouse confirmed robust performance in both seeding and harvesting operations, achieving over 90% accuracy in localizing target elements and successfully executing planned tasks. The platform thus provides a strong foundation for future research in predictive control, semantic environment modeling, and scalable deployment of autonomous systems for high-value crop production. Full article

Background/Objectives: Pumpkin seed pulp from processing plants offers high nutritional value due to its rich β-carotene content, making it a potential functional feed ingredient. This study investigated the effects of pumpkin seed pulp, which has already been administered as livestock feed, on key physiological parameters in cattle, including the concentration of β-carotene in the blood measured during routine health monitoring. Methods: Here, pumpkin waste cultivated in various fields was processed into cattle feed (pumpkin seed pulp flakes, PSPFs) by grinding and drying, and residual pesticide (heptachlor) and β-carotene contents were measured. A pilot feeding trial was conducted with 13 cattle (7 in the treatment group and 6 in the control group) and blood component analysis was performed, and findings were contextualized with a literature review. Results: Heptachlor concentrations varied depending on the cultivation site of raw pumpkins. Among the six lots produced using raw materials sourced from fields not contracted by the Air Water Group—a collective of companies in which Air Water Inc. holds more than 51% ownership—three exceeded the regulatory limits for animal feed established in Japan. PSPFs contained high levels of β-carotene, as expected. Blood tests before and after the feeding trial indicated absorption of β-carotene in the cattle. Maintaining high plasma β-carotene concentrations in cattle has been associated with improved immune function and reproductive performance. Conclusions: Our study demonstrates that PSPFs are a promising, environmentally friendly, and natural β-carotene-rich feed ingredient. Tracing the cultivation fields of raw pumpkins can help ensure feed safety. Full article

The lateral vibration of propulsion shafting is a critical factor affecting the acoustic stealth performance of underwater vehicles. As the main vibration isolation component in transmitting vibrational energy, the damping efficiency of the propulsion shafting support system (PSSS) holds particular significance. This study investigates the dynamic characteristics of the PSSS with the integral squeeze film damper (ISFD). A dynamic model of ISFD–PSSS is developed to systematically analyze the effects of shaft speed and external load on its dynamic behavior. Three test bearings (conventional, 1S, and 3S structure) are designed and manufactured to study the influence of damping structure layout scheme, damping fluid viscosity, unbalanced load, and shaft speed on the vibration reduction ability of ISFD–PSSS through axis orbit and vibration velocity. The results show that the damping effects of ISFD–PSSS are observed across all test conditions, presenting distinct nonlinear patterns. Suppression effectiveness is more pronounced in the vertical direction compared to the horizontal direction. The 3S structure bearing has better vibration reduction and structural stability than other schemes. The research results provide a reference for the vibration control method of rotating machinery. Full article

While personal thermal comfort is critical for well-being and productivity, it is often overlooked by traditional building management systems that rely on uniform settings. Modern data-driven approaches often fail to capture the complex interactions between various data streams. This pilot study introduces a high-accuracy, interpretable framework for thermal comfort classification, designed to identify the most significant predictors from a comprehensive suite of environmental, physiological, and anthropometric data in a controlled group of young adults. Initially, an XGBoost model using the full 24-feature dataset achieved the best performance at 91% accuracy. However, after using SHAP analysis to identify and select the most influential features, the performance of our ensemble models improved significantly; notably, a Random Forest model’s accuracy rose from 90% to 94%. Our analysis confirmed that for this homogeneous cohort, environmental parameters—specifically temperature, humidity, and CO₂—were the dominant predictors of thermal comfort. The primary strength of this methodology lies in its ability to create a transparent pipeline that objectively identifies the most critical comfort drivers for a given population, forming a crucial evidence base for model design. The analysis also revealed that the predictive value of heart rate variability (HRV) diminished when richer physiological data, such as diastolic blood pressure, were included. For final validation, the optimized Random Forest model, using only the top 10 features, was tested on a hold-out set of 100 samples, achieving a final accuracy of 95% and an F1-score of 0.939, with all misclassifications occurring only between adjacent comfort levels. These findings establish a validated methodology for creating effective, context-aware comfort models that can be embedded into intelligent building management systems. Such adaptive systems enable a shift from static climate control to dynamic, user-centric environments, laying the critical groundwork for future personalized systems while enhancing occupant well-being and offering significant energy savings. Full article

According to the World Health Organization, musculoskeletal injuries affect more than 1.71 billion people around the world. These injuries are a major public health issue and the leading cause of disability. There has been a recent interest in hydrogels as a potential biomaterial for musculoskeletal tissue regeneration. This is due to their high water content (70–99%), ECM-like structure, injectability, and controllable degradation rates. Recent preclinical studies indicate that they can enhance regeneration by modulating the release of bioactive compounds, growth factors, and stem cells. Composite hydrogels that combine natural and synthetic polymers, like chitosan and collagen, have compressive moduli that are advantageous for tendon–bone healing. Some of these hydrogels can even hold up to 0.8 MPa of tensile strength. In osteoarthritis models, functionalized systems such as microspheres responsive to matrix metalloproteinase-13 have demonstrated disease modulation and targeted drug delivery, while intelligent in situ hydrogels have exhibited a 43% increase in neovascularization and a 50% enhancement in myotube production. Hydrogel-based therapies have been shown to restore contractile force by as much as 80%, increase myofiber density by 65%, and boost ALP activity in bone defects by 2.1 times in volumetric muscle loss (VML) models. Adding TGF-β3 or MSCs to hydrogel systems improved GAG content by about 60%, collagen II expression by 35–50%, and O’Driscoll scores by 35–50% in cartilage regeneration. Full article