Search Results (68)

The kinematic and dynamic characteristics of the grinding media during the wet grinding process are investigated using a coupled Discrete Element Method (DEM)–Computational Fluid Dynamics (CFD) approach. Firstly, a coupled DEM-CFD model of the vertical spiral agitator mill is established and validated with experimental torque measurements. Subsequently, a velocity analysis model is established using the vector decomposition method. The cylinder is then divided into multiple regions along its radial and axial directions. The effects of spiral agitator rotational speed, diameter, pitch, and media filling level are investigated with respect to the circumferential velocity, axial velocity, collision frequency, effective energy between media, and energy loss of the grinding media. The average effective energy between media is an innovative metric for evaluating the grinding effect. The results indicate that the peripheral region of the spiral agitator demonstrates superior kinematic and dynamic performance. The rotational speed of the spiral agitator exerts a highly significant influence on the kinematic and dynamic characteristics of the media. With a maximum rise of 0.2 m/s in circumferential velocity and a 16.7 J gain in total energy. The media filling level demonstrates a negligible influence on media kinematics, while it profoundly affects dynamic properties, evidenced by a substantial increase of 83.09 J in the total media–media energy. As the diameter increases, the peak media circumferential velocity shifts outward, and the total media–media energy rises by 5.4 J. The spiral agitator pitch has a minimal impact on both the kinematic and dynamic characteristics of the media. Full article

Feeding unmanned aerial vehicles (UAVs) in aquaculture face critical challenges due to time-varying mass, strong coupling, and environmental disturbances, which hinder the effectiveness of conventional control strategies. This paper proposes a robust dual-loop model predictive control (MPC) framework optimized by an adaptive niche radius genetic algorithm (ANRGA). The outer loop employs MPC for position regulation using virtual acceleration inputs, while the inner loop applies MPC for attitude stabilization with dynamic inertia adaptation. To overcome the limitations of manual weight tuning, ANRGA adaptively optimizes the weighting factors, preventing premature convergence and improving global search capability. System stability is theoretically ensured through Lyapunov analysis and the small-gain theorem, even under variable-mass dynamics. MATLAB simulations under representative trajectories—including spiral, figure-eight, and feeding cruise paths—demonstrate that the proposed ANRGA-MPC-MPC achieves position errors below 0.5 m, enhances response speed by approximately 58% compared with conventional MPC, and outperforms benchmark controllers in terms of accuracy, robustness, and convergence. These results confirm the feasibility of the proposed method for precise and energy-efficient UAV feeding operations, providing a promising control strategy for intelligent aquaculture applications. Full article

Air-to-ground visual target persistent tracking technology for swarm drones, as a crucial interdisciplinary research area integrating computer vision, autonomous systems, and swarm collaboration, has gained increasing prominence in anti-terrorism operations, disaster relief, and other emergency response applications. While recent advancements have predominantly concentrated on improving long-term visual tracking through image algorithmic optimizations, insufficient exploration has been conducted on developing system-level persistent tracking architectures, leading to a high target loss rate and limited tracking endurance in complex scenarios. This paper designs an asynchronous multi-task parallel architecture for drone-based long-term tracking in air-to-ground scenarios, and improves the persistent tracking capability from three levels. At the image algorithm level, a long-term tracking system is constructed by integrating existing object detection YOLOv10, multi-object tracking DeepSort, and single-object tracking ECO algorithms. By leveraging their complementary strengths, the system enhances the performance of the detection and multi-object tracking while mitigating model drift in single-object tracking. At the drone system level, ground target absolute localization and geolocation-based drone spiral tracking strategies are conducted to improve target reacquisition rates after tracking loss. At the swarm collaboration level, an autonomous task allocation algorithm and relay tracking handover protocol are proposed, further enhancing the long-term tracking capability of swarm drones while boosting their autonomy. Finally, a practical swarm drone system for persistent air-to-ground visual tracking is developed and validated through extensive flight experiments under diverse scenarios. Results demonstrate the feasibility and robustness of the proposed persistent tracking framework and its adaptability to wild real-world applications. Full article

This study centers on retirement planning achievement, examining its impact mechanism on older adults’ mental health and its boundary conditions. Drawing on self-determination theory (SDT) and conservation of resources (COR) theory, we tested a parallel mediation and a moderated mediation model using data from an online survey with 900 Chinese retirees aged 55–74. Structural equation modelling revealed that retirement planning achievement directly and positively predicted mental health, and indirectly through three pathways: greater active social participation, higher retirement enjoyment, and reduced retirement loss. Furthermore, retirement adjustment exhibited dual, and opposing, moderating effects on the direct path: low retirement loss, as a psychological resource, significantly amplified the positive impact of planning achievement (a resource gain spiral), whereas high retirement enjoyment attenuated its effect (a ceiling effect). Income-group analysis revealed that both the parallel mediation and moderated mediation models were fully supported in the average-income group, but effects were non-significant for the insufficient-income group and weakened in the sufficient-income group. These findings suggest that retirement planning achievement represents a key pathway to promoting mental health in later life, but its benefits are constrained by psychological resources and socioeconomic status. The “achievement dividend” is greatest among well-adjusted retirees in the average-income group, highlighting the heterogeneity in retirement adjustment and providing evidence for targeted, equitable ageing-support policies. Full article

This paper investigates and evaluates a compact, high-Q glass transformer with a 3D spiral structure that offers low loss and high area efficiency. Furthermore, we designed a CMOS power amplifier (PA) with an output-matching network implemented using an off-chip high-Q glass transformer to validate its operation. Two transformer types were developed: a five-port transformer with a center-tap and a four-port transformer without a center tap. The high-Q property of the transformer leads to low loss and tight coupling, as evidenced by an increase in maximum available gain (MAG). Compared with an integrated CMOS transformer, the high-Q transformer exhibits significantly lower loss while maintaining similar area and inductance, despite being an external component. A test PA comprising the CMOS PA and the off-chip transformer was evaluated with simulations and measurements, and it was also compared with a fully integrated PA at the simulation level to verify performance improvements. The proposed PA achieved a saturation power of 29.8 dBm, which was 1.7 dB higher than that of the fully integrated PA. The PAE also improved by 11 percentage points, from 32.1% to 43.1% in simulation. The results show substantial performance gains in simulation, while the total area increases only slightly. Measurements show the same trend as the simulations; with shorter bond-wire lengths, the measured results are expected to approach the simulated performance. These findings demonstrate the feasibility of an ultra-compact CMOS–off-chip hybrid PA that delivers high performance while maintaining a footprint comparable to that of a fully integrated PA, enabling applications in compact devices including mobile products. Full article

The traditional construction industry significantly contributes to global resource consumption and climate change. Conventional methods limit the development of complex and multifunctional architectural forms. In contrast, 3D concrete printing (3DCP), an additive manufacturing technique, enables the creation of intricate building envelopes that integrate architectural and energy-efficient functions. Bioinspired design, recognized for its sustainability, has gained traction in this context. This study investigates the thermal and energy performance of various bioinspired and regular 3DCP infill patterns compared to conventional concrete building envelopes in tropical climates. A three-stage methodology was employed. First, bioinspired patterns were identified and evaluated through a literature review. Next, prototype models were developed using Rhino and simulated in ANSYS to assess thermal performance. Finally, energy performance was analyzed using Ladybug and Honeybee tools. The results revealed that honeycomb, spiral, spiderweb, and weaving patterns achieved 35–40% higher thermal and energy efficiency than solid concrete, and about 10% more than the 3DCP sawtooth pattern. The findings highlight the potential of bioinspired spiral infill patterns to enhance the sustainability of 3DCP building envelopes. This opens new avenues for integrating biomimicry into 3DCP construction as a tool for performance optimization and environmental impact reduction. Full article

Being ionized nebulae where star formation events take place, H ii regions are not only natural laboratories for studying physical processes of star formation and photoionization but also signatures reflecting evolution of their internal stellar populations and hosting galaxies. In this paper, we present a comprehensive analysis of spectral emission-line data for H ii regions in the nearby spiral galaxy NGC 2403, aimed at gaining deep insight into underlying properties and evolution for the H ii regions and the galaxy. The spectroscopic data are obtained through observations with the 2.16 m telescope at National Astronomical Observatories of China and a collection of published data in the literature. Photoionization modeling is combined in the analysis for diagnosing the spectral features and interpreting the observational data with certain physical mechanisms. Results of this work not only involve estimates of a set of parameters such as metallicity, the ionization parameter, etc., and evolution stages for the H ii regions in NGC 2403 but also reveal distinct characteristics of different spectral features and their sensitivities to specific parameters, which provides an instructive implication for proper usages of emission-line diagnostics for H ii regions or galaxies nearby and far away. Full article

The apple snail Pila globosa is a widely distributed mollusc in tropical freshwater ecosystems, where it plays a crucial ecological role. This study examined the morphometric features, condition indices, and reproductive traits of P. globosa to gain insights into its population structure in the Ratargul Freshwater Swamp Forest, Bangladesh. Water quality parameters were recorded, and various morphometric measurements were analysed, including their correlations and seasonal variations. The mean values for shell length, shell weight, shell width, spiral length, base length, aperture length, aperture width, and soft tissue wet weight were 4.64 ± 0.97 cm, 38.29 ± 15.27 g, 3.56 ± 0.74 cm, 2.32 ± 0.51 cm, 3.33 ± 0.74 cm, 3.46 ± 0.64 cm, 2.01 ± 0.45 cm, and 18.05 ± 11.39 g, respectively. Linear regression analyses revealed strong correlations among length–length and length–weight parameters, indicating consistent growth patterns. Monthly frequency distributions showed distinct variations in shell size and form. The sex ratio was 1:1.23 (male–female), not significantly different from parity. Histological analysis during the rainy season revealed reproductive activity, including mature ova, previtellogenic and vitellogenic oocytes, and spermatogonia and spermatids. These findings enhance understanding of the species’ biology and its interaction with environmental conditions, offering valuable data for the conservation and management of freshwater mollusc populations in wetland ecosystems. Full article

This systematic review explores recent advancements in antenna and rectifier systems for radio frequency (RF) energy harvesting within the gigahertz frequency range, aiming to support the development of sustainable and efficient low-power electronic applications. Conducted under the PRISMA methodology, our review filtered 2465 initial records down to 80 relevant studies, addressing three research questions focused on antenna design, operating frequency bands, and rectifier configurations. Key variables such as antenna type, resonant frequency, gain, efficiency, bandwidth, and physical dimensions were examined. Antenna designs including fractal, spiral, bow-tie, slot, and rectangular structures were analyzed, with fractal antennas showing the highest efficiency, while array antennas exhibited lower performance despite their compact dimensions. Frequency band analysis indicated a predominance of 2.4 GHz and 5.8 GHz applications. Evaluation of substrate materials such as FR4, Rogers, RT Duroid, textiles, and unconventional composites highlighted their impact on performance optimization. Rectifier systems including Schottky, full-wave, half-wave, microwave, multi-step, and single-step designs were assessed, with Schottky rectifiers demonstrating the highest energy conversion efficiency. Additionally, correlation analyses using boxplots explored the relationships among antenna area, efficiency, operating frequency, and gain across design variables. The findings identify current trends and design considerations crucial for enhancing RF energy harvesting technologies. Full article

Oat is a highly nutritious cereal crop, and the moisture content of its seeds plays a vital role in cultivation management, storage preservation, and quality control. To enable efficient and non-destructive prediction of this key quality parameter, this study presents a modeling framework integrating hyperspectral imaging (HSI) technology with a dual-optimization machine learning strategy. Seven spectral preprocessing techniques—standard normal variate (SNV), multiplicative scatter correction (MSC), first derivative (FD), second derivative (SD), and combinations such as SNV + FD, SNV + SD, and SNV + MSC—were systematically evaluated. Among them, SNV combined with FD was identified as the optimal preprocessing scheme, effectively enhancing spectral feature expression. To further refine the predictive model, three feature selection methods—successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and principal component analysis (PCA)—were assessed. PCA exhibited superior performance in information compression and modeling stability. Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). Bayesian optimization was used for global tuning of network structural parameters, while ASFSSA was applied to fine-tune the initial weights and thresholds, improving convergence efficiency and predictive accuracy. The proposed Bayes-ASFSSA-BP model achieved determination coefficients (R²) of 0.982 and 0.963, and root mean square errors (RMSEs) of 0.173 and 0.188 on the training and test sets, respectively. The corresponding mean absolute error (MAE) on the test set was 0.170, indicating excellent average prediction accuracy. These results significantly outperformed benchmark models such as SSA-BP, ASFSSA-BP, and Bayes-BP. Compared to the conventional BP model, the proposed approach increased the test R² by 0.046 and reduced the RMSE by 0.157. Moreover, the model produced the narrowest 95% confidence intervals for test set performance (Rp²: [0.961, 0.971]; RMSE: [0.185, 0.193]), demonstrating outstanding robustness and generalization capability. Although the model incurred a slightly higher computational cost (480.9 s), the accuracy gain was deemed worthwhile. In conclusion, the proposed Bayes-ASFSSA-BP framework shows strong potential for accurate and stable non-destructive prediction of oat seed moisture content. This work provides a practical and efficient solution for quality assessment in agricultural products and highlights the promise of integrating Bayesian optimization with ASFSSA in modeling high-dimensional spectral data. Full article

In view of the difficulties encountered when tuning parameters and the lack of anti-interference capabilities exhibited by high-precision trajectory-tracking control of quadrotor UAVs in complex dynamic environments, this paper proposes a fusion control framework based on an improved crowned pig optimisation algorithm (ICPO) and preset performance anti-disturbance control (PPC-ADRC). Initially, this paper addresses the limited convergence efficiency of the traditional crowned pig algorithm (CPO) by introducing a dynamic time threshold mechanism and an adaptability-based directed elimination strategy to balance the algorithm’s global exploration and local development capabilities. This results in a significant improvement in the convergence speed and optimisation accuracy. Secondly, a hierarchical control architecture is designed, with the outer loop using a PPC-ADRC controller to dynamically constrain the tracking error boundary using an exponential performance funnel function and a combined state observer (ESO) to estimate the compound disturbance in real time. The inner-loop attitude control uses ADRC, and the 24-dimensional parameters of the ADRC (including the ESO bandwidth and non-linear feedback gain) are optimised autonomously using the ICPO to achieve efficient parameter tuning. The simulation experiments demonstrate that, in comparison with the original CPO, the ICPO attains an average fitness ranking that is superior in the CEC2014–2022 benchmark test, thereby substantiating its global optimisation capability. In the PPC-ADRC controller parameter optimisation, the preset performance of the ICPO-tuned PPC-ADRC controller (PPC-ADRC) is superior to that of the particle swarm optimisation (PSO), genetic algorithm (GA) and original CPO. The ICPO-based PPC-ADRC controller is shown to reduce the total error by more than 45.6% compared to the ordinary ADRC controller in the task of tracking a spiral trajectory, and it effectively reduces the overshoot. Its capacity to withstand complex wind disturbances is notably superior to that of the traditional PID and ADRC architectures. Stability analysis further proves that the system satisfies the Lyapunov convergence condition in a finite time. This research provides a theoretical foundation for the high-precision control of UAVs in complex dynamic environments. Full article

In order to achieve precise vector control of permanent magnet synchronous motors and maintain reliability during operation, it is necessary to obtain more accurate rotor position and rotor angular velocity. However, the installation of sensors can lead to increased motor volume and cost, so it is necessary to use sensorless estimation of rotor position and angular velocity. The switching function of traditional sliding mode observers is a discontinuous sign function, which can lead to serious chattering problems and phase lag problems caused by low-pass filters. Therefore, this article proposes an improved fuzzy hyper spiral sliding mode observer based on the traditional sliding mode observer. Firstly, the observer takes the current as the observation object and uses the difference between the actual current and the observed current and its derivative as the fuzzy input. The sliding mode gain is used as the fuzzy output to tune the parameters of the sliding mode gain. Secondly, in response to the chattering problem caused by traditional sliding mode control methods, the hyper spiral algorithm is adopted and a $sin (arctan(nx)$) nonlinear function is introduced instead of the sign function as the switching function to achieve switch continuous sliding mode control, thereby suppressing the system’s chattering. Finally, the rotor position information is extracted through an orthogonal normalized phase-locked loop to improve observation accuracy. For time-varying nonlinear permanent magnet synchronous motor control systems, fractional order PID can improve the control accuracy of the system and adjust the dynamic performance of the system more quickly compared to traditional PID control algorithms. Therefore, fractional order PID is used instead of traditional PID controllers. By comparing simulation experiments with traditional sliding mode observers and fuzzy improved adaptive sliding mode observers, it was proven that the improved fuzzy super spiral sliding mode observer can effectively suppress chattering and extract rotor position with higher accuracy, a faster response rate, and better dynamic performance. This provides a new approach for the sensorless control strategy of permanent magnet synchronous motors. Full article

This paper presents a novel Spiral Slot Planar Inverted-F Antenna (SSPIFA) specifically designed for telemedicine and healthcare applications, featuring compact size, biocompatible safety, and high integration suitability. By replacing the conventional top metal patch of a Planar Inverted-F Antenna (PIFA) with a slot spiral radiator whose geometry is precisely matched to the ground plane, the proposed antenna achieves a significant size reduction, making it ideal for encapsulation in miniaturized medical devices—a critical requirement for implantation scenarios. Tailored for the ISM 915 MHz band, the antenna is fabricated with a four-turn slot spiral etched on a 30 mm-diameter dielectric substrate, achieving an overall height of 22 mm and an electrically small profile of approximately 0.09λ × 0.06λ (λ: free-space wavelength at the center frequency). Simulation and measurement results demonstrate a −16 dB impedance matching (S11 parameter) at the target frequency, accompanied by a narrow fractional bandwidth of 1% and stable right-hand circular polarization (RHCP). When implanted in a layered biological tissue model (skin, fat, muscle), the antenna exhibits a near-omni directional radiation pattern in the azimuthal plane, with a peak gain of 2.94 dBi and consistent performance across the target band. These characteristics highlight the SSPIFA’s potential for reliable wireless communication in implantable medical systems, balancing miniaturization, radiation efficiency, and biocompatible design. Full article

Low temperature plasmas (LTPs) generated at atmospheric pressure and room temperature have gained increasing attention in biomedical research due to their ability to control cellular behavior through the production of reactive oxygen and nitrogen species (RONS), electric fields, and UV radiation. Among several LTP configurations, dielectric barrier discharge (DBD) plasma has been extensively studied for its ability to stimulate controlled biological effects while maintaining low gas temperature, making it suitable for cell-based applications. This study designed a novel spiral-wound DBD plasma device to investigate the voltage-dependent effects of plasma discharge on DBC1.2 epithelial cells. Plasma was applied at 2 kV_p-p, 3 kV_p-p, and 4 kV_p-p to evaluate its effect on cellular permeability, mitochondrial activity, viability, and apoptosis. FITC-dextran-70 (FD-70, MW: 70 kDa) was used as a model permeation marker to assess cellular uptake. The results showed a voltage-dependent increase in FD-70 uptake, suggesting improved plasma-assisted drug delivery. The cell mitochondrial activity, evaluated with a MT-1 MitoMP detection kit, revealed that plasma exposure at 2 kV_p-p and 3 kV_p-p slightly enhanced mitochondrial membrane potential (MMP), signifying increased metabolic and mitochondrial activity, whereas exposure at 4 kV_p-p led to a reduction in MMP, suggesting oxidative stress and early apoptosis. Early and late apoptosis was further assessed using FITC Annexin-V and propidium iodide (PI). The results showed enhanced cell viability and a reduced apoptotic cell at 2 kV_p-p and 3 kV_p-p plasma exposure when compared to the control. However, at 4 kV, there was a decline in cell viability and an increase in apoptosis, suggesting a shift towards plasma-induced cytotoxicity. This study established a safe plasma exposure threshold for DBC1.2 cells and explored the potential use of a spiral-wound DBD plasma device for biomedical applications, particularly in drug delivery and cell modulation. Full article

From a positive psychological standpoint, access to decent work extends beyond fulfilling economic needs: it is a fundamental human right. While significant efforts have been made to examine the societal implications of decent work, surprisingly little attention has been directed toward its impact on individual employees. Integrating the Conservation of Resources theory and the Self-Determination theory, this study aims to advance understanding of this topic by exploring the dynamic and reciprocal interplay among decent work, flourishing (namely, an indicator of strong individual well-being), and job performance. Data were collected from 426 Italian employees (62.7% female) by administering a survey in three waves with a one-month lag. A Cross-Lagged Panel Model approach was employed. The findings highlight that (a) decent work is positively associated with later flourishing; (b) flourishing positively affects later job performance; (c) flourishing fully mediates the relationship between decent work and job performance; and (d) the relationship between flourishing and decent work is reciprocal, with flourishing also enhancing the perception of decent work over time. Our study contributes to advancing the understanding of decent work and its implications, demonstrating the importance of promoting a decent work environment to foster flourishing and performance. This creates a mutually reinforcing cycle of well-being and productivity. Full article