Search Results (3,703)

Under the backdrop of low-carbon energy transition, the increasing integration of grid-following (GFL) and grid-forming (GFM) converters into power systems is profoundly altering transient synchronous stability. A critical challenge lies in analyzing synchronous stability in grids with high penetration converters and improving converter control strategies to enhance stability. This paper selects virtual synchronous generator (VSG)-based converters as representative GFM units to investigate synchronous stability and control in hybrid systems with both VSG and GFL converters. To simplify stability analysis, this study proposes a novel distribution scheme of power supplies based on an assessment of the ability of different sources to reshape synchronous stability. Specifically, synchronous generators (SGs) and GFL converters are located in the power sending area, while VSGs are deployed in the power receiving area. Under this configuration, synchronous risk is predominantly determined by the power-angle difference between VSGs and SGs. Subsequently, the mechanism by which voltage stability affects synchronous stability between SGs and VSGs is revealed. Furthermore, enhanced control strategies for both VSG and GFL converters are proposed which adjust their transient active/reactive power response characteristics to enhance synchronous stability between SGs and VSGs. Finally, the theoretical analysis and control strategies are validated through simulations on a multi-machine, two-area interconnected power system. Under the proposed enhanced control strategies for GFLs and VSGs, the first-swing power-angle amplitude between VSGs and SGs is reduced by 60% and 49%. Full article

Identifying reliable geochemical signals that reflect crustal stress evolution remains a major challenge in earthquake monitoring. Spring fluids, due to their deep circulation and rapid response, provide an important window into fault-zone processes. This study presents three years (May 2022–March 2025) of hourly hydrogen gas (H₂) concentration monitoring in spring gases from the Muji Basin on the northern Pamir Plateau, integrated with meteorological and seismic data. H₂ concentrations exhibited a stable diurnal pattern, positively correlated with water and air temperatures and negatively correlated with atmospheric pressure. Short-term anomalies during seismically quiet periods may reflect a combination of temperature-dependent solubility effects and transient degassing caused by localized gas accumulation and sudden release under heterogeneous fault and aquifer conditions. During seismically active phases, sustained increases in H₂ concentrations were also recorded; however, such anomalies did not consistently precede earthquakes, instead reflecting broader phases of tectonic instability and episodic fault-zone degassing. These findings highlight the potential of long-term H₂ monitoring to improve our understanding of the coupling between crustal stress, fluid transport, and degassing processes in tectonically active regions. Full article

This article discusses the automated control of dynamic loads in drive systems using the example of a wind turbine screw drive. A mathematical model was developed, including differential equations of system motion, the voltage balance of the electric motor, and transfer functions of the control system. The Laplace transform was applied to obtain the system’s frequency and time characteristics. Numerical calculations and simulation results are presented, demonstrating the system’s stability and the effectiveness of the proposed control method. The generated amplitude–frequency and transient response graphs confirm the system’s operability. The proposed approach enhances the reliability of the screw drive, reduces mechanical loads, and extends the equipment’s service life. Full article

Greenhouse vegetable production faces significant challenges due to the non-stationary and nonlinear dynamics of the cultivation environment, which demand adaptive and intelligent control strategies. This study presents an intelligent control system for greenhouse complexes based on artificial neural networks and fuzzy logic, optimized using genetic algorithms. The proposed system dynamically adjusts PI controller parameters to maintain optimal microclimatic conditions, including temperature and humidity, enhancing resource efficiency. Comparative analyses demonstrate that the genetic algorithm-based tuning outperforms traditional and fuzzy adaptation methods, achieving superior transient response with reduced overshoot and settling time. Implementation of the intelligent control system results in energy savings of 10–12% compared to conventional stabilization algorithms, while improving decision-making efficiency for electrotechnical subsystems such as heating and ventilation. These findings support the development of resource-efficient cultivation regimes that reduce energy consumption, stabilize agrotechnical parameters, and increase profitability in greenhouse vegetable production. The approach offers a scalable and adaptable solution for modern greenhouse automation under varying environmental conditions. Full article

Ultra-wide bandgap β-Ga₂O₃ is a promising low-cost alternative to conventional direct X-ray detector materials that are limited by fabrication complexity, instability, or slow temporal response. Here, we comparatively investigate β-Ga₂O₃ thin films grown on c-sapphire by low-pressure chemical vapor deposition (LPCVD) and plasma-enhanced CVD (PECVD), establishing a quantitative linkage between growth kinetics, microstructure, defect landscape, and X-ray detection figures of merit. The LPCVD-grown film (thickness ≈ 0.289 μm) exhibits layered coalesced grains, a narrower rocking curve (FWHM = 1.840°), and deep-level oxygen-vacancy-assisted high photoconductive gain, yielding a high sensitivity of 1.02 × 10⁵ μC Gy_air⁻¹ cm⁻² at 20 V and a thickness-normalized sensitivity of 3.539 × 10⁵ μCGy_air⁻¹ cm⁻² μm⁻¹. In contrast, the PECVD-grown film (≈1.57 μm) shows dense columnar growth, higher O/Ga stoichiometric proximity, and shallow-trap dominance, enabling a lower dark current, superior dose detection limit (30.13 vs. 57.07 nGy_air s⁻¹), faster recovery, and monotonic SNR improvement with bias. XPS and dual exponential transient analysis corroborate a deep-trap persistent photoconductivity mechanism in LPCVD versus moderated shallow trapping in PECVD. The resulting high-gain vs. low-noise complementary paradigm clarifies defect–gain trade spaces and provides a route to engineer β-Ga₂O₃ thin-film X-ray detectors that simultaneously target high sensitivity, low dose limit, and temporal stability through trap and electric field management. Full article

Obesity has traditionally been considered a major risk factor for numerous metabolic disorders and diseases. However, a subset of individuals with obesity, classified as having “metabolically healthy obesity” (MHO), display relatively normal metabolic parameters despite excess adiposity. This review critically examines the current knowledge surrounding MHO, including its various definitions, prevalence, clinical characteristics, contributing factors, and long-term outcomes. While MHO carries lower health risks compared to metabolically unhealthy obesity (MUO), evidence consistently demonstrates increased disease risk compared to metabolically healthy normal-weight individuals, particularly for type 2 diabetes, cardiovascular disease, chronic kidney disease, and certain cancers. MHO prevalence ranges from 10 to 30% among individuals with obesity globally, varying by sex, age, BMI, and ethnicity. Multiple factors contribute to the MHO phenotype, including beneficial adipose tissue distribution patterns, enhanced adipocyte function, favorable genetic profiles, and lifestyle factors. Recent single-cell transcriptomic analyses have identified specific cell populations, particularly mesothelial cells, as key drivers of metabolic health in visceral adipose tissue. The discovery of persistent epigenetic memory of obesity provides molecular evidence for why MHO often represents a transient state, with many individuals progressing to MUO over time. Emerging evidence also reveals differential therapeutic responses to GLP-1 receptor agonists between MHO and MUO phenotypes, highlighting the need for precision medicine approaches. The concept of MHO has important clinical implications for risk stratification and personalized treatment approaches. This review synthesizes current evidence while highlighting knowledge gaps and future research directions in this rapidly evolving field. Full article

Event-based cameras, as a revolutionary class of dynamic vision sensors, offer transformative advantages for capturing transient mechanical phenomena through their asynchronous, per-pixel brightness change detection mechanism. These neuromorphic sensors excel in challenging industrial environments with their microsecond-level temporal resolution, ultra-low power requirements, and exceptional dynamic range that significantly outperform conventional imaging systems. In this way, the event-based camera provides a promising tool for machine vibration sensing and fault diagnosis. However, the dynamic vision data from the event-based cameras have a complex structure, which cannot be directly processed by the mainstream methods. This paper proposes a dynamic vision-based non-contact machine fault diagnosis method. The Eagle Vision Transformer (EViT) architecture is proposed, which incorporates biologically plausible computational mechanisms through its innovative Bi-Fovea Self-Attention and Bi-Fovea Feedforward Network designs. The proposed method introduces an original computational framework that effectively processes asynchronous event streams while preserving their inherent temporal precision and dynamic response characteristics. The proposed methodology demonstrates exceptional fault diagnosis performance across diverse operational scenarios through its unique combination of multi-scale spatiotemporal feature analysis, adaptive learning capabilities, and transparent decision pathways. The effectiveness of the proposed method is extensively validated by the practical condition monitoring data of rotating machines. By successfully bridging cutting-edge bio-inspired vision processing with practical industrial monitoring requirements, this work creates a new paradigm for dynamic vision-based non-contact machinery fault diagnosis that addresses critical limitations of conventional approaches. The proposed method provides new insights for predictive maintenance applications in smart manufacturing environments. Full article

Efficient utilization of low-calorific-value gases reduces emissions but remains challenging. Self-heat-maintained combustion uses fuel’s exothermic heat to sustain stability without external heat, yet the feed gas typically requires preheating (typically 573–673 K). This study innovatively proposes a compact regenerative catalytic reactor featuring an integrated helical heat-recovery structure and replaces empirical preheating with a user-defined function (UDF) programmed heat transfer efficiency model. This dual innovation enables self-sustained combustion at 0.16 vol.% methane, the lowest reported concentration for autonomous operation. Numerical results confirm stable operation under ultra-lean conditions, with significantly reduced preheating energy demand and accelerated thermal response. Transient analysis shows lower space velocities enable self-maintained combustion across a broader range of methane concentrations. However, higher methane concentrations require higher inlet temperatures for self-heat maintenance. This study provides significant insights for recovering energy from low-calorific-value gases and alleviating global energy pressures. Full article

In this study, the impact resistance of WUF-B steel frame beam–column joints under fire was investigated using ABAQUS finite element software through a sequential thermal–mechanical coupling approach. By integrating a room-temperature impact model with a single-sided fire field applied to the lower flange of the steel beam, the multi-parameter influence mechanisms—including temperature (150–750 °C), fire area distribution, and impact momentum—were systematically analyzed. Results indicate that elevated temperatures significantly degrade structural impact resistance. At 750 °C, the peak impact force decreases by 73.3% compared to room temperature, while the mid-span bending moment increases by 63.3%. When the fire zone is near the impact point, localized thermal softening further reduces the peak impact force. Under constant impact energy, lower momentum (i.e., higher velocity) accelerates the rebound of the falling mass, revealing the role of momentum transfer efficiency in governing the transient response of high-temperature structures. Additionally, an analytical prediction model based on Timoshenko beam theory and thermo-mechanical stiffness degradation is developed. By introducing a segmented temperature reduction function, the model significantly enhances the accuracy of mid-span displacement predictions for steel structures under fire. Full article

Reducing environmental impacts and energy consumption in construction is increasingly important, prompting the use of renewable, ecological, and cost-effective materials. This research investigates an ecological building material combining clay and ground reed fibers, offering a promising alternative to conventional resources. A composite made of 50% clay and 50% ground reed was developed to study the influence of fiber size after grinding, as reed is typically used in its unprocessed form. Initial analyses included a physico-chemical characterization of both clay and reed. Thermal performance was then evaluated under steady-state and transient conditions to assess heat storage, heat transfer, and the material’s thermal inertia. The results showed a thermal conductivity of 0.38 W/m·K and an estimated 50% energy savings compared to clay alone, demonstrating the composite’s enhanced insulation capacity. Mechanical tests revealed compressive strengths of 2.48 MPa and flexural strengths of 0.79 MPa, with no significant effect from fiber size. The composite is lighter and more insulating than traditional clay blocks, indicating potential for reduced heating demand and improved indoor comfort. This study confirms the feasibility of incorporating ground reed fibers into clay-based composites to produce more sustainable building materials, supporting the transition toward energy-efficient and environmentally responsible construction practices. Full article

Drought seriously affects wheat yield; it is therefore important to study the molecular mechanism of wheat resistance to drought stress to ensure national food security. Plants can remove harmful substances through autophagy, thus improving their drought resistance. The results of previous studies have shown that autophagy is involved in the drought stress response; however, the molecular mechanism of autophagy in response to drought stress has yet to be elucidated. In this study, molecular biological methods such as immunohistochemistry, Co-Immunoprecipitation (Co-IP), and pull-down were used to explain the molecular mechanism of autophagy in response to drought stress at the protein level. We found that a dehydrin protein called cold-regulated 410 (TaCOR410) interacts with autophagy-related 8 (TaATG8, a key protein of wheat autophagy). TaCOR410 interacted with TaATG8 through its ATG8-interacting motif (AIM), and interaction was inhibited after mutation of the AIM. Interference with TaCOR410 inhibited autophagy and reduced the drought resistance of wheat. In contrast, transient transfection of TaCOR410 promoted autophagy. In wheat, overexpression of TaATG8 improved the drought resistance of wheat. Following interference with TaATG5, TaATG7 inhibited autophagy and reduced the drought resistance of wheat. From the above results, it is evident that autophagy can improve the drought resistance of wheat and can respond to drought stress through the interaction of TaCOR410 with TaATG8. Full article

Rosa roxburghii Tratt., a fruit crop known for its high Vitamin C content and other nutritional compounds, has not yet been studied for its auxin response factor (ARF) family members. ARFs are important proteins in auxin-mediated pathways, playing a vital role in plant physiological and biochemical processes such as plant development, and flower and fruit maturation. In the present study, we identified 14 ARF genes (designated as RrARFs) in R. roxburghii, which are distributed across seven chromosomes and grouped into four subfamilies. An analysis of cis-acting elements revealed that these genes might be involved in various biological processes, including plant development, flower development, light responses, cell cycle regulation, phytohormone responses, and responses to abiotic and biotic stresses. A gene expression analysis demonstrated differential expression of RrARF genes across different tissues and stages of fruit development, with four members showing higher expression during the fruit ripening stages. Furthermore, a coexpression analysis identified that RrARF5 was highly coexpressed with RrMDHAR1, a key enzyme involved in Vitamin C biosynthesis. Moreover, transactivation assays and transient overexpression experiments confirmed that RrARF5 activates the transcription of RrMDHAR1. The findings of this study suggest a potential role of the ARF gene family in Vitamin C accumulation in R. roxburghii and enhance our understanding of the diverse regulatory function of the ARF gene family in plants. Full article

This study investigates the influence of electrical actuation parameters on the performance of a morphing composite aerodynamic profile actuated by Shape Memory Alloy (SMA) wires. A fully coupled electro-thermo-mechanical finite element model has been developed to simulate the transient response of NiTi SMA, capturing the nonlinear interplay between temperature evolution, phase transformation, and mechanical deformation under Joule heating. The model incorporates phase-dependent material properties, heat effects, and geometric constraints, enabling accurate prediction of actuation dynamics. To validate the model, a morphing spoiler prototype has been fabricated using high-performance additive manufacturing with a carbon fibre-reinforced polymer. The SMA wires have been pretensioned and electrically actuated at different current levels (3 A and 6 A), and the resulting deformation has been recorded through video analysis with embedded timers. Experimental measurements confirmed the model’s ability to predict both actuation time and displacement, with maximum deflections of 33 mm and 40 mm corresponding to different current inputs. This integrated approach demonstrates an efficient and compact solution for active aerodynamic surfaces without the need for mechanical linkages, enabling future developments in adaptive structures for automotive and aerospace applications. Full article

Polarization information is essential for material identification, stress mapping, biological imaging, and robust vision under strong illumination, yet conventional approaches rely on external polarization optics and active biasing, which are bulky, alignment-sensitive, and power-hungry. A more desirable route is to encode polarization at the pixel level and read it out at zero bias, enabling compact, low-noise, and polarization imaging. Low-symmetry layered semiconductors provide persistent in-plane anisotropy as a materials basis for polarization selectivity. Here, we construct an eight-terminal radial ‘star-shaped’ Au/ReS₂ metal-semiconductor junction array pixel that operates in a genuine photovoltaic mode under zero external bias based on the photothermoelectric effect. Based on this, electrical summation of phase-matched multi-junction channels increases the signal amplitude approximately linearly without sacrificing the two-lobed modulation depth, achieving ‘gain by stacking’ without external amplification. The device exhibits millisecond-scale transient response and robust cycling stability and, as a minimal pixel unit, realizes polarization-resolved imaging and pattern recognition. Treating linear combinations of channels as operators in the polarization domain, these results provide a general pixel-level foundation for compact, zero-bias, and scalable polarization cameras and on-pixel computational sensing. Full article

When the speed of an induction motor (IM) exceeds its rated value, voltage saturation occurs, which degrades its performance. Traditional flux-weakening (FW) control suffers from delays due to cascaded PI regulators and sensitivity to rotor field orientation lag. Addressing these two issues, the proposed ancillary flux-weakening (AFW) method introduces two d-axis current compensation paths. One compensation path is from the reference value of the q-axis current, which simplifies the traditional three-PI cascade FW path into a single PI path in the transient process. The other compensation path is derived from the q-axis current tracking error to mitigate voltage saturation caused by orientation error. Comparative experiments show that during precise direction acceleration, the AFW method increases the current response time by 35% and reduces the peak voltage fluctuation by 38.98%. It also reduces low voltage ripple by 76.4% in inaccurate direction and burst load conditions. The results confirm a significant enhancement of dynamic performance and voltage anti-saturation capability in the FW region. Full article