Search Results (110)

Background: This study examined the effects of high-intensity interval training with change of direction (HIITcod) and small-sided games (SSGs) on components of physical fitness in school-aged children. The aim was to provide practical insights for optimizing exercise interventions in constrained indoor environments. Methods: A randomized controlled trial was conducted during regular physical education (PE) classes in a school’s indoor sports hall. Fifty healthy boys (mean ± SD = 12.6 ± 0.6 years) were randomly assigned to a HIITcod group (n = 25) or an SSG group (n = 25). The intervention lasted eight weeks and consisted of structured training sessions designed to progressively increase intensity and training load in a child-friendly and safe environment. Individual maximal heart rate (HRmax) was determined using the 20 m shuttle run test prior to the intervention. Heart rate monitors were worn throughout all sessions to ensure exercise intensity consistently exceeded 75% of HRmax, with real-time monitoring used to adjust effort when necessary. Physical fitness outcomes, including the shuttle run test (SRT), handgrip strength (HG), 20 m sprint, standing broad jump (SBJ), Illinois agility test, and T-test, were assessed pre- and post-intervention. Results: Both groups demonstrated significant improvements over time in the SRT, SBJ, Illinois agility test, and T-test (p < 0.05). No significant group × time interactions were detected (all p > 0.05). Handgrip strength increased significantly in the HIITcod group (35.03 ± 7.19 kg to 36.80 ± 6.68 kg, p = 0.001, d = 0.25) and showed a non-significant trend in the SSG group (38.28 ± 9.09 kg to 39.23 ± 9.12 kg, p = 0.056). No significant changes were observed in 20 m sprint performance. Conclusions: Based on the study results, both HIITcod and SSGs were associated with improvements in multiple components of physical fitness in school-aged boys. These findings suggest that both training modalities may be viable options for implementation during physical education classes, particularly in limited indoor settings. The observed positive changes in fitness could indicate their potential to positively impact children’s fitness in a structured and engaging manner. Full article

Industrial wastewater pollution has reached acute levels in the environment; consequently, scientists are developing new sustainable treatment methods. Lignocellulosic biomass (LB) stands as a promising raw material because it originates from agricultural waste, forestry residues, and energy crop production. This review examines the application of nanomaterials derived from lignocellulosic resources in wastewater management, highlighting their distinctive physical and chemical properties, including a large surface area, adjustable porosity structure, and multifunctional group capability. The collection of nanomaterials incorporating cellulose nanocrystals (CNCs) with lignin nanoparticles, as well as biochar and carbon-based nanostructures, demonstrates high effectiveness in extracting heavy metals, dyes, and organic pollutants through adsorption, membrane filtration, and catalysis mechanisms. Nanomaterials have benefited from recent analytical breakthroughs that improve both their manufacturing potential and eco-friendly character through hybrid catalysis methods and functionalization procedures. This review demonstrates the ability of nanomaterials to simultaneously turn waste into valuable product while cleaning up the environment through their connection to circular bioeconomic principles and the United Nations Sustainable Development Goals (SDGs). This review addresses hurdles related to feedstock variability, production costs, and lifecycle impacts, demonstrating the capability of lignocellulosic nanomaterials to transform wastewater treatment operations while sustaining global sustainability. Full article

The vortex-induced vibration (VIV) dynamics of commercial-scale deep-sea mining risers with complex component arrangements (pumps, buffer stations, buoyancy modules) remain insufficiently explored, especially for 6000 m systems with nonlinear tension. This study investigates VIV control strategy by adjusting tension for a nonlinear riser system using the Iwan-Blevins wake oscillator model integrated with Morison equation-based analysis. An analytical model incorporating four typical current profiles was established to quantify the dynamic response under different flow velocities, internal flow density, and structural parameters. Increased buffer station mass effectively suppressed drift distance (over 35% reduction under specific conditions) by regulating axial tension. Dynamic comparisons demonstrated distinct VIV energy distribution patterns under different current conditions. Spectral analysis revealed that the vibration follows Strouhal vortex shedding lock-in principles. Spatial modal differentiation was observed due to nonlinear variations in velocity profiles, pipe diameters, and axial tension, accompanied by multi-frequency resonance, coexistence of standing and traveling waves, and broadband resonance with amplitude surges under critical velocities (1.75 m/s in Current-B). This study proposes to control the VIV amplitude by adjusting internal flow density and buffer mass, which is proved effective for reducing vibrations in upper (0–2000 m) risers. It validates vibration amplitude and frequency control through current velocity, buffer mass and slurry density regulation in a nonlinear riser system. Full article

Thermoplastic polyurethane (TPU) electrospun fiber membranes possess unique micro-nano structures and excellent properties. Adjusting their wettability enables the directional transportation of lubricants. A conventional method for adjusting porosity and wettability involves inducing membrane shrinkage using absolute ethanol and heat treatment. However, the shrinkage response and the corresponding changes in the tensile properties of TPU fiber membranes after induction remain unclear, limiting their applications. Thus, in this study, after being peeled off, the samples were first left to stand at room temperature (RT) for 24 h to release residual stress and stabilize their dimensions, and then treated with dehydrated ethanol at RT and high temperature, respectively, with their shrinkage behaviors observed and recorded. The results showed that TPU nanofiber membranes shrank significantly in absolute ethanol, and the degree of shrinkage was temperature-dependent. The shrinkage rates were 2% and 4% in dehydrated ethanol at room temperature and high temperature, respectively, and heating increased the shrinkage effect by 200%. These findings prove that absolute ethanol causes TPU fibers to shrink, and high temperatures further promote shrinkage. However, although the strong synergistic effect of heat and solvent accelerates shrinkage, it may induce internal structural defects, resulting in the deterioration of mechanical properties. The contraction response induced by anhydrous ethanol stimulation can be used to directionally adjust the local density and modulus of TPU nanofiber membranes, thereby changing the wettability. This approach provides new opportunities for applications in areas such as medium transportation and interface friction reduction in lubrication systems. Full article

Metasurfaces have drawn extensive research attention for their unique optical properties and vast application potential. Among the various resonant modes induced in metasurfaces, BIC and electric anapole modes stand out as particularly interesting due to their distinctive physical characteristics. In this work, we designed and investigated novel dimeric dumbbell-shaped metasurfaces incorporating two independently tunable asymmetric parameters. This structural innovation enables the simultaneous excitation of both electric anapole and QBIC modes under normally incident MIR illumination. More importantly, by adjusting these two asymmetric parameters, one can independently tune the resonance peaks of the two modes, thereby overcoming the performance limits of conventional single-peak modulation. This metasurface design demonstrates outstanding performance for dielectric environment-sensing applications. We conducted a comprehensive investigation of the sensing sensitivity for dumbbell-shaped metasurfaces of various geometries. Our simulation results show that the circular-shaped configuration achieved high sensitivity, reaching 20,930 GHz/RIU. This work offers a novel design paradigm for multi-mode control and functionalization of metasurface structures. Full article

Canada’s vast forests play a substantial role in the global carbon balance but require laborious and expensive forest inventory campaigns to monitor changes in aboveground biomass (AGB). Light detection and ranging (LiDAR) or reflectance observations onboard airborne or unoccupied aerial vehicles (UAVs) may address scalability limitations associated with traditional forest inventory but require simple forest structures or large sets of manually delineated crowns. Here, we introduce a deep learning approach for crown delineation and AGB estimation reproducible for complex forest structures without relying on hand annotations for training. Firstly, we detect treetops and delineate crowns with a LiDAR point cloud using marker-controlled watershed segmentation (MCWS). Then we train a deep learning model on annotations derived from MCWS to make crown predictions on UAV red, blue, and green (RGB) tiles. Finally, we estimate AGB metrics from tree height- and crown diameter-based allometric equations, all derived from UAV data. We validate our approach using 14 ha mixed forest stands with various experimental tree densities in Southern Ontario, Canada. Our results show that using an unsupervised LiDAR-only algorithm for tree crown delineation alongside a self-supervised RGB deep learning model trained on LiDAR-derived annotations leads to an 18% improvement in AGB estimation accuracy. In unharvested stands, the self-supervised RGB model performs well for height (adjusted R², R_a² = 0.79) and AGB (R_a² = 0.80) estimation. In thinned stands, the performance of both unsupervised and self-supervised methods varied with stand density, crown clumping, canopy height variation, and species diversity. These findings suggest that MCWS can be supplemented with self-supervised deep learning to directly estimate biomass components in complex forest structures as well as atypical forest conditions where stand density and spatial patterns are manipulated. Full article

In reversible data hiding, prediction error generation plays a crucial role, with pixel value ordering (PVO) standing out as a prediction method that achieves high fidelity. However, conventional PVO approaches select predicted pixels and their predictions independently, failing to fully exploit the inherent redundancy in ordered pixel sequences. This paper proposes a novel PVO-based prediction method that leverages the continuity and spatial correlation of ordering pixels. We first introduce a new prediction technique that exploits the redundancy of consecutive pixels. Our approach selects the most appropriate prediction method from preset prediction errors, considering both pixel position and value characteristics. Furthermore, we implement an adaptive strategy that dynamically selects multiple iteration parameters based on pixel content to obtain more expandable prediction errors and adjusts the modification of prediction errors accordingly. Unlike traditional fixed-parameter methods, our approach better utilizes the inherent structure and redundancy of image pixels, thereby improving data embedding efficiency while minimizing image distortion. We enhance performance by combining pairwise prediction-error expansion with content-based prediction error analysis. Experimental results demonstrate that the proposed scheme outperforms state-of-the-art solutions in terms of image fidelity while maintaining competitive embedding capacity, confirming the effectiveness of our method for efficient data embedding and image recovery. Full article

In the management of forests, the boundaries of individual units of land containing similar forest resources (e.g., stands) are delineated and used to guide the implementation of management activities. Traditionally, stand boundaries are drawn or digitized by hand; however, work recently has been conducted to automate the process using aerial imagery or airborne light detection and ranging (LiDAR) data as supporting resources. The work described here applies an object-based image analysis (OBIA) process to aerial imagery and to a landform index database. The size and shape of stands in the outcomes of these applications are then adjusted to conform to the desired product of land managers. These products are then intersected as they each contain information of value in the stand delineation process. The intersected database is then adjusted once again to conform to the desired product of land managers. Conformity of the size and shape of the resulting stand boundaries to a reference database drawn subjectively by hand was low to moderate. Specifically, the overall agreement for spatial and thematic (class names) accuracies was 43.0% and 56.8%, respectively. Nevertheless, the process of automating the stand delineation effort remains promising for achieving an efficient and non-subjective characterization of a structurally complex forested environment. Full article

The instability in rare-earth material supply and rising costs have driven research into rare-earth-free electric motors. Among various alternatives, wound rotor synchronous motors (WRSMs) stand out due to their adjustable excitation, enabling high torque at low speeds, and efficient field weakening at high speeds. Unlike permanent magnet synchronous motors (PMSMs), WRSMs offer greater operational flexibility and eliminate the risk of demagnetization. However, accurately modeling WRSMs remains challenging, especially when considering axial fringing flux and leakage components, which significantly affect motor performance. To address this challenge, this paper proposes a 3D nonlinear magnetic equivalent circuit (MEC) model that explicitly incorporates axial flux components and leakage paths in WRSMs with overhang rotor structures. Unlike conventional 2D MEC models, which fail to capture axial flux interactions, the proposed approach improves prediction accuracy while significantly reducing computational costs compared to full 3D finite element analysis (FEA). The model was validated through comparisons with 3D FEA simulations and experimental back-EMF measurements, demonstrating its accuracy and computational efficiency. The results confirm that the 3D nonlinear MEC model effectively captures axial flux paths and leakage components, making it a valuable tool for WRSM design and analysis. Future research will focus on further refining the model, incorporating hysteresis loss modeling, and developing hybrid MEC–FEA simulation techniques to enhance its applicability. Full article

Building materials, including polyvinyl chloride (PVC), play a key role in construction engineering, influencing the durability, esthetics, and functionality of structures. PVC stands out for its lightness, thermal insulation, and corrosion resistance. This makes it competitive with wood, aluminum, or steel, particularly in the manufacture of window joinery. One of the key technological processes in the processing of PVC profiles is welding, the quality of which depends on the precise control of parameters such as the temperature, time, and pressure regulating the speed of the welding heads. In modern welding machines, the use of servo drives guarantees the adequate precision and repeatability of the process, which allows better adjustment to technological requirements than in older machines. This study aimed to determine the effect of the heating head feed rate for selected milling depths on the quality and strength of window frame welds. A criterion in the assessment of the strength of the window frames was the result of failure load tests on the welds. In addition, the tests took into account the quality of the welds. The tests showed that the welding head feed rate of 0.25 mm/s generated the highest-quality welds, taking into account the continuity and symmetry of the weld and its highest failure load. When milling the composite to a depth of 1 mm, the average value of the failure load was 3637 N. Meanwhile, for speeds of 0.19 mm/s and 0.31 mm/s, it was 3157 N and 3033 N, respectively. For the 0.5 mm milling variant and without milling the composite, the average load values were significantly smaller. Full article

Background/Objectives: Low masticatory function has been proposed as a risk factor for sarcopenia. This study investigated its potential association with body composition and physical performance in community-dwelling older adults. Methods: Participants included adults aged ≥65 years (643 men; 797 women) who volunteered for a longitudinal cohort study. Masticatory function was objectively assessed using gummy jelly and subjectively evaluated via a structured questionnaire. The skeletal muscle mass, body mass index, waist circumference, handgrip strength, gait speed, and five-time chair-stand test were assessed. Results: Objectively measured masticatory function was classified as low (12.6%), moderate (38.0%), or high (49.4%). In men, masticatory function was significantly associated with skeletal muscle mass index (low, moderate, and high: 7.4, 7.7, and 7.7 kg/m²; p = 0.005), handgrip strength (31.8, 34.2, and 35.5 kg; p < 0.001), and gait speed (1.3, 1.4, and 1.4 m/s; p = 0.003). In women, low masticatory function was linked to a higher body mass index (22.9, 22.0, and 21.9 kg/m²; p = 0.028) and waist circumference (82.9, 80.8, and 80.4 cm; p = 0.041). Moreover, these significant associations persisted after adjusting for covariates. Discrepancies were observed between objective and subjective measures of masticatory function, with approximately 40% of participants showing low objective masticatory function, perceiving their chewing ability as normal. Subjective masticatory function exhibited no significant associations with anthropometric measures or sarcopenia components. Conclusions: In men, objectively measured low masticatory function was associated with reduced skeletal muscle mass and poor physical performance; in women, it was linked to higher body mass index. Full article

In recent years, polyurea (PUA) systems have drawn considerable attention in the coatings industry for their superior performance. Among these systems, polyaspartate ester-based polyurea (PAE-PUA) stands out for its excellent comprehensive properties, and the structure of the diamines used in polyaspartate ester (PAE) significantly influences key performance attributes, such as gel time, mechanical properties, and thermal stability. To investigate the influence of diamine structures on PAE-PUA properties, this study synthesized PAEs through ester exchange reactions involving diamines and monohydric alcohols with varied chain lengths and structural types (linear or cyclic). The effects of four diamines (D230, DMH, IPDA, PACM) and four monohydric alcohols (CA, DDA, OD, CHOL) on polyurea coating properties were systematically examined. The results demonstrated that adjusting the structural regularity of PAEs via ester exchange reactions effectively regulated their viscosity, maintaining it below 1500 mPa·s. These reactions also enabled simultaneous regulation of surface-drying time, mechanical properties, and thermal performance. Notably, introducing 1-octadecanol (OD) significantly improved surface-drying time and thermal stability, whereas cyclic structures in diamines or alcohols resulted in higher glass transition temperatures (T_g). Additionally, the mechanical properties and reaction rates of modified PAEs can be tailored to meet specific application requirements, offering an effective strategy for developing polyurea materials optimized for the coatings industry. Full article

The growing demand for wood products and ecosystem services in Chinese fir plantations has led to longer rotation ages and density control practices, raising concerns about their impact on soil fertility. This study assessed soil fertility of Chinese fir plantations in Fujian, Jiangxi, and Sichuan Provinces using the Nemerow index. The effects of stand age and initial planting density on soil fertility were analyzed using statistical models. In Fujian and Jiangxi, soil fertility was significantly higher at 11 and 30 years than at 5 and 25 years, while in Sichuan, it was higher at 25 and 30 years than at 5 and 11 years. In Fujian, soil fertility was higher at 6667 trees ha⁻² than at 1667 trees ha⁻². No significant differences were observed in Jiangxi, while in Sichuan, soil fertility at 6667 trees ha⁻² was significantly higher than at 5000 and 1667 trees ha⁻², and soil fertility at 10,000 trees ha⁻² exceeded that at 1667 trees ha⁻². Soil fertility typically increased with stand age, especially in Fujian and Sichuan. Soil fertility also increased with initial planting density, especially in Jiangxi and Sichuan. A structural equation model (SEM) explained 88% of the variance in soil fertility, with stand age directly affecting soil fertility and soil organic matter mediating the effects of stand age and planting density. These findings suggest that adjusting rotation age and planting density could help improve soil fertility, offering practical implications for sustainable forest management in Chinese fir plantations. Full article

The large-scale microwave plasma synthesis of graphene and nitrogen-doped graphene with tailored structural properties, crucial for their successful usage applications, has been demonstrated. The developed atmospheric pressure plasma method offers several advantages, including the continuous production of high-quality, free-standing graphene without the use of chemicals, solvents, catalysts, or additional heating. This non-toxic process eliminates the need for vacuum systems while achieving high temperatures. The method enables the precise control over graphene’s properties, such as the layer number, defects, sheet size, uniformity, and functionality, as well as the doping type and configuration, by adjusting the plasma parameters. Protocols for the synthesis of specific nanostructures with a controlled structural quality, production rate, and chemical composition have been established using methane and methylamine as precursors. The comprehensive physicochemical characterization of the graphene and nitrogen-doped graphene was carried out using scanning electron microscopy, high-resolution transmission electron microscopy, Raman spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. Full article

Fruits and vegetables play a crucial role in addressing food security challenges posed by the growing global population. Citrus fruits are among the most widely cultivated crops worldwide; however, their production is steadily declining due to climate change. Among the various biotic and abiotic stresses affecting citrus production, water scarcity caused by climate change stands out as a significant issue. Interestingly, the rhizosphere of citrus plants is home to beneficial fungi known as arbuscular mycorrhizal fungi (AMF). AMF have been shown to enhance the growth and development of host plants. They also improve the plants’ tolerance to various stresses and enhance soil structure. This study aimed to evaluate the response of two different citrus rootstocks—Rangpur lime and Carrizo citrange—when subjected to three mycorrhizal treatments, namely, AMF+ (inoculated with AMF), AMF- (treated with fungicide to eliminate AMF), and a control (naturally occurring AMF), under conditions of water deficit. The results indicated that the AMF+ treatment had a significant positive effect on both rootstock genotypes compared to the AMF- treatment. Physiological attributes such as photosynthesis, stomatal conductance, transpiration, non-photochemical quenching, and both dark and light quantum yield exhibited significantly smaller declines under water deficit conditions in AMF+ plants compared to those in the AMF- and control groups. Conversely, stress indicators—such as malondialdehyde (MDA) and hydrogen peroxide (H₂O₂)—increased significantly in the AMF- treatment compared to AMF+. Additionally, the increase in antioxidative enzymes (superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APx) and osmotic adjustment (proline (PRO)) was more pronounced in the AMF+ treatment in the leaves and roots of both citrus rootstocks. In conclusion, the findings suggest that the presence and application of AMF in citrus roots may enhance the plants’ ability to cope with water scarcity more effectively. Full article