Search Results (22,325)

Virtual synchronous generator (VSG) technology introduces synthetic rotational inertia and damping into inverter-based systems, thereby enhancing regulation performance under grid-connected operation. However, the output characteristics of VSGs are strongly influenced by virtual inertia and damping. This paper develops a self-tuning inertia–damping coordination mechanism for VSGs. The coupling between virtual inertia and damping with respect to grid power quality is systematically investigated, and a power-angle dynamic response model for synchronous generators (SGs) under extreme operating conditions is established. Building on these results, an improved adaptive control strategy for the VSG’s virtual inertia and damping is proposed. The proposed strategy detects changes in frequency and load power, enabling adaptive tuning of virtual inertia and damping in response to system variations, thereby reducing frequency overshoot while accelerating the dynamic response. The effectiveness of the proposed strategy is validated by hardware-in-the-loop real-time simulations. Full article

Background: Eye tracking technology can be utilized to identify early markers of autism. Several neurodivergent features of social attention have been revealed by eye tracking studies in ASD toddlers. Our aim was to develop stimulus material that elicits highly distinctive gaze patterns in toddlers at low and high risk for autism as indicated by ADOS (i.e., scoring below and above the ADOS cut-off point). Additionally, we sought to identify the variables most effective in differentiating between these groups. Methods: In our research, we analyzed the data of 74 toddlers between 12 and 30 months. Children were divided into two groups based on their ADOS scores: the lower ADOS (lrADOS) group included those scoring below the ADOS cut-off point (n = 42; mean age = 22.5 ± 5.0 months), while the higher ADOS (hrADOS) group comprised children scoring above the cut-off (n = 32; mean age = 23.3 ± 4.8 months). We recorded eye gaze data during the presentation of dynamic social attention stimuli with a self-developed eye tracking device. We used two types of social attention stimuli: joint attention (ostensive) and preferential looking paradigm. We analyzed the area of interest based on the gaze–time ratio. To ensure sufficient robustness, we selected gaze retention interval (GRI) variables characterized by broader spatial and temporal parameters compared to traditional fixation-based measures. Results: As anticipated, we observed significant differences between the two groups across most variables. Typically, within the preferential paradigm, the distinct indicators of the social domain were higher on average in the lrADOS group compared to the hrADOS group, while the non-social domain exhibited the opposite trend. The results of correlations with ADOS scores indicated that the social ratio in the preferential paradigm exhibited the strongest negative correlation. Notably, there were higher effect sizes within the hrADOS group in comparison to the lrADOS group when correlation with ADOS scores was tested separately for each group. Conclusions: We developed stimulus materials and eye tracking variables that, thanks to their robustness, appear promising even when dealing with noisy eye tracking data typical of young children. In the preferential paradigm, beyond AOI ratio measures, GRI variables show promise in distinguishing between toddler groups with higher vs. lower ADOS scores. Furthermore, they may be related to severity based on their marked and significant correlations with ADOS scores. Especially when used in combination, these variables appear well-suited to capturing characteristics indicative of an elevated likelihood of autism. Full article

Forest ecological compensation policies (FECPs) are a key institutional arrangement for balancing ecological conservation and farmers’ development needs in national parks. Existing research has often treated such policies as a homogeneous whole, failing to clearly reveal the mechanisms through which different policy types affect farmers’ livelihoods, while also paying insufficient attention to complex property-rights settings. This study takes Wuyi Mountain National Park—a typical representative of collective forest regions in southern China—as a case study. Based on 239 micro-survey datasets from farming households and employing the mprobit model and moderating effect models, it investigates the influence, mechanisms, and heterogeneity of farmers’ livelihood capital in terms of their livelihood strategy choices under the moderating roles of “blood-transfusion” and “blood-making” FECPs. The results show the following: (1) Among the sample farmers, livelihood strategies are distributed as follows: pure agricultural type (31.8%), out-migration for work type (20.5%), and commercial operation type (47.7%). (2) Farmers’ livelihood capital has a significant impact on their livelihood strategy choice, with different dimensions of capital playing distinct roles. (3) FECPs follow differentiated moderating pathways. “Blood-transfusion” policies emphasize compensation and buffering functions, reducing farmers’ livelihood transition pressure through direct cash transfers; “blood-making” policies reflect empowerment and restructuring characteristics, activating physical assets and reshaping the role of social capital through productive investment. Together, they constitute a complementary system of protective security and transformative empowerment. Accordingly, this study proposes policy insights such as building a targeted ecological compensation system that is categorized, dynamically linked, and precise; innovating compensation fund allocation mechanisms that integrate collective coordination with household-level benefits; optimizing policy design oriented toward enhancing productive capital; and establishing robust monitoring, evaluation, and adaptive management mechanisms for dynamic FECPs. Full article

Advancing rapidly in modern bridge engineering technology, through concrete-filled steel tubular (CFST) arch bridges have achieved widespread application in transportation infrastructure development. Nevertheless, vehicle fires occurring in complicated operational settings may rapidly escalate into major disasters. Fires in oil tankers are particularly dangerous for the safety of bridges. This study examines the fire resistance of through concrete-filled steel tubular (CFST) arch bridges exposed to tanker truck fires. The study formulates a detailed model utilizing Fire Dynamics Simulator (FDS) to simulate fire scenarios, elucidating the spatial temperature distribution characteristics within arch bridge structures. A three-dimensional finite element model established in ABAQUS (Abaqus 2024, Dassault Systèmes Simulia Corp, Providence, RI, USA) is employed to simulate structural responses by analyzing the mechanical behavior of key components under different fire conditions. Practical fire resistance design recommendations for extreme tanker truck fire scenarios are ultimately proposed. Numerical results demonstrate that structural components near the fire source (such as transverse bracings, hangers, and fire-exposed arch surfaces) experience significantly higher temperatures than other regions. Notable temperature gradients developing along hangers and arch ribs in fire-affected zones are observed, while substantial cross-sectional temperature gradients occurring in these components under tanker truck fires reveal their damage evolution mechanisms. The fire exposure scenario at the quarter-point of the midspan is identified as the most critical fire exposure scenario for through CFST arch bridges under tanker truck fires. Under this extreme scenario, the deflection on the fire-exposed side of the global structure exhibits a significant three-stage distribution characteristic: an initial ascending phase around 0–800 s, followed by a sharp descending phase during 800–1100 s, and then a stabilization trend. A fire resistance limit criterion based on component failure (t_f3 = 853.43 s) is established, and a global fire resistance limit assessment methodology for through CFST arch bridges under extreme tanker truck scenarios is proposed. Full article

Intelligent lower-limb exoskeleton rehabilitation robots are increasingly superseding traditional rehabilitation equipment, making them a focus of research in this field. However, existing systems remain challenged by dynamic instability resulting from various disturbances during actual walking. To address this limitation, this study proposes a novel dynamic stability criterion. Through an analysis of the principles and limitations of the traditional zero-moment point (ZMP) stability criterion, particularly during the late single-leg support phase, a new stability criterion is introduced, which is founded on the swing projection polygon during single-leg support. This approach elucidates the variation patterns of the stability polygon during a single-step motion and facilitates a qualitative analysis of the stability characteristics of the human–robot system in multiple postures. To further enhance the stability and smoothness of gait trajectories in lower-limb exoskeleton rehabilitation robots, the shortcomings of conventional gait planning approaches, namely their non-intuitive nature and discontinuity, are addressed. A recurrent gait planning method leveraging Long Short-Term Memory (LSTM) neural networks is proposed. The integration of the periodic motion characteristics of human gait serves to validate the feasibility and correctness of the proposed method. Finally, based on the recurrent gait planning method, the dynamic stability of walking postures is verified through theoretical analysis and experimental comparisons, accompanied by an in-depth analysis of key factors influencing dynamic stability. Full article

In this paper, the impact of negative bias temperature instabilities (NBTIs) on commercial power p-channel Vertical Double-Diffused MOS (VDMOS) transistors from the standpoint of practical applications was analyzed. The effects of NBTI are one of the main reliability concerns for this type of device, so it is necessary to investigate how these effects influence various applications. A series of experiments were carried out including negative bias temperature stressing, infra-red thermographic recording and circuit characterization, with the goal of evaluating the effects of negative bias temperature stressing on the self-heating of samples in load-driving circuits operating with higher currents and circuit performance of a CMOS inverter circuit containing the examined samples. The findings suggest that negative bias temperature stressing-induced threshold voltage shift directly affects increased self-heating in load-driving circuits and that it also directly affects transfer and dynamics characteristics in CMOS inverters. Full article

Background: Rhythmic sensory stimulation, including structured musical interventions, has gained renewed interest as a non-pharmacological strategy that may modulate cortical excitability and network stability in focal epilepsy. Although several small studies have reported changes in seizure frequency or epileptiform activity during rhythmic or music exposure, the underlying mechanisms and translational relevance remain insufficiently synthesized. Objective: This narrative review summarizes clinical evidence on music-based and rhythmic sensory interventions in focal epilepsy, outlines plausible neurophysiological mechanisms related to neural entrainment and large-scale network regulation, and discusses emerging opportunities for digital delivery of rhythmic protocols in everyday self-management. Methods: A structured search of recent clinical, neurophysiological, and rehabilitation literature was performed with emphasis on rhythmic auditory, tactile, and multimodal stimulation in epilepsy or related conditions. Additional theoretical and translational sources addressing oscillatory dynamics, entrainment, timing networks, and patient-centered digital tools were reviewed to establish a mechanistic framework. Results: Existing studies—although limited by small cohorts and heterogeneous methodology—suggest that certain rhythmic structures, including specific musical compositions, may transiently modulate cortical synchronization, reduce epileptiform discharges, or alleviate seizure-related symptoms in selected patients. Evidence from neurologic music therapy and rhythmic stimulation in other neurological disorders further supports the concept that externally delivered rhythms can influence timing networks, attentional control, and interhemispheric coordination. Advances in mobile health platforms enable structured rhythmic exercises to be delivered and monitored in real-world settings. Conclusions: Music-based and rhythmic sensory interventions represent a promising but underexplored adjunctive approach for focal epilepsy. Their effectiveness likely depends on individual network characteristics and on the structure of the applied rhythm. Digital integration may enhance personalization and adherence. Rigorous clinical trials and mechanistic studies are required to define optimal parameters, identify responders, and clarify the role of rhythmic stimulation within modern epilepsy care. Full article

Accurate evaluation of demand response (DR) potential at the individual user level is critical for the effective implementation and optimization of demand response programs. However, existing data-driven methods often suffer from insufficient feature representation, limited characterization of load profile dynamics, and ineffective fusion of heterogeneous features, leading to suboptimal evaluation performance. To address these challenges, this paper proposes a novel demand response potential evaluation method based on multivariate heterogeneous features and a Stacking-based ensemble mechanism. First, multidimensional indicator features are extracted from historical electricity consumption data and external factors (e.g., weather, time-of-use pricing), capturing load shape, variability, and correlation characteristics. Second, to enrich the information space and preserve temporal dynamics, typical daily load profiles are transformed into two-dimensional image features using the Gramian Angular Difference Field (GADF), the Markov Transition Field (MTF), and an Improved Recurrence Plot (IRP), which are then fused into a single RGB image. Third, a differentiated modeling strategy is adopted: scalar indicator features are processed by classical machine learning models (Support Vector Machine, Random Forest, XGBoost), while image features are fed into a deep convolutional neural network (SE-ResNet-20). Finally, a Stacking ensemble learning framework is employed to intelligently integrate the outputs of base learners, with a Decision Tree as the meta-learner, thereby enhancing overall evaluation accuracy and robustness. Experimental results on a real-world dataset demonstrate that the proposed method achieves superior performance compared to individual models and conventional fusion approaches, effectively leveraging both structured indicators and unstructured image representations for high-precision demand response potential evaluation. Full article

China has abundant deep coalbed methane (CBM) resources; however, high temperature, stress, and reservoir pressure complicate the gas adsorption–desorption–diffusion–seepage processes, severely restricting the development of deep CBM. Through experimental research on adsorption, desorption, diffusion, and seepage behaviors of various coal samples, the control mechanisms of deep coal reservoir properties on CBM production in the Linxing–Shenfu region have been revealed. The results indicate that CBM adsorption and desorption characteristics are jointly controlled by coal rank, ash yield, temperature. and pressure. Among the above conditions, coal rank and pressure exhibit positive effects, while ash yield and temperature show inhibitory effects. Analysis of desorption efficiency based on the Langmuir model further identifies sensitive desorption and rapid desorption stages as key phases for enhancing productivity. Moreover, the gas diffusion mechanism is dynamically evolving, with Knudsen diffusion and Fick diffusion being the main modes during high ground pressure stages, gradually transitioning to the coexistence of Knudsen, transition, and Fick diffusions as pressure decreases. Concurrently, gas–water seepage experiments demonstrate that increasing temperature will reduce the irreducible water saturation and enhance the relative permeability of the gas. Since irreducible water saturation is negatively correlated with relative permeability of gas, the relative permeability of the gas phase, cross-point saturation, and the range of the two-phase co-seepage zone all significantly increases with the increase in temperature. The findings systematically elucidate the regulatory mechanisms of deep coal reservoir properties in the process of “adsorption–desorption–diffusion–seepage,” providing critical theoretical support for optimizing development strategies and enhancing the efficiency of deep CBM development. Full article

The article studies the influence of chlorosulfonated polyethylene CSM 40 as a compatibilizer on the curing characteristics of the rubber compound, dynamic mechanical analysis, morphology, physico-mechanical and performance properties of vulcanized rubber based on a compound of ethylene propylene diene monomer EPDM S 501A and nitrile butadiene NBR 2645 rubbers. DMA studies indicate that the temperature dependence of tanδ for vulcanizates with and without a compatibilizer based on EPDM S 501A/NBR 2645 at a ratio of 75/25 parts per hundred parts of rubber (phr) has a bimodal character, which indicates the incompatibility of the rubber phases. The temperature dependence for EPDM S 501A/NBR 2645 vulcanizates (25/75 phr) with and without a compatibilizer has a monomodal form, which characterizes the improved compatibility of the rubber phases. SEM showed that a clearly defined microporous structure is observed on a cleavage of vulcanizate sample EPDM/NBR (25/75 phr) without a compatibilizer; with the addition of CSM 40, this feature is retained, but becomes less pronounced. It is shown that vulcanizates containing the compatibilizer CSM 40 are characterized by increased strength properties and hardness compared to vulcanized rubber without a compatibilizer. It was established that the vulcanized rubber based on EPDM S 501A/NBR 2645/CSM 40 (25/75/5 phr) is characterized by the smallest changes in the elastic-strength properties and hardness of vulcanizates after a day of thermo-oxidative aging in air and their weight after exposure to industrial oil I-20A and standard petroleum fluid SZhR-1 at room temperature among vulcanizates based on EPDM S 501A and NBR 2645. The vulcanizate of the rubber compound, including a compound of EPDM/NBR (25/75 phr) with a compatibilizer CSM 40 in an amount of 5 phr (2.88 wt.%), is characterized by stable physico-mechanical properties and improved performance properties. This rubber compound can be used for the manufacture of rubber products operating under the influence of oils and hydrocarbon environments. Full article

This paper proposes a compressive-sensing (CS) acquisition algorithm for low-power, high-dynamic GNSS receivers based on low-dimensional time-domain measurements, a non-iterative compressive-domain direct-projection peak-search pipeline, and a coherence-optimized sensing-matrix design. Unlike most existing GNSS-CS acquisition approaches that rely on explicit sparse-recovery formulations (e.g., OMP/BP/LS-type iterative reconstruction) to identify the delay–Doppler support—often incurring substantial computational burden and acquisition latency—the proposed method performs peak detection directly in the compressive measurement domain and is supported by unified Gram-matrix optimization and perturbation/detection analyses. Specifically, the measurement Gram matrix is optimized on the symmetric positive-definite (SPD) manifold to obtain a diagonally dominant and well-conditioned structure with reduced inter-column correlation, thereby bounding reconstruction-induced perturbations and preserving the main correlation peak. Simulation results show that the proposed scheme retains the low online complexity characteristic of direct-projection baselines while achieving a 2–3 dB acquisition sensitivity gain, and it requires substantially fewer operations than iterative OMP-based CS acquisition schemes whose cost scales approximately linearly with the sparsity level K. The proposed framework enables robust, low-latency acquisition suitable for resource-constrained GNSS receivers in high-dynamic environments. Full article

Background/Objectives: The biogenic synthesis of silver nanoparticles (AgNPs) is a promising alternative method, driven by the presence of metabolites in plant matrices capable of acting as reducing and stabilizing agents. Seasonality is a key factor that influences the phytochemical composition of plants and can directly impact the yield, physicochemical characteristics, stability, and bioactivities of the obtained AgNPs. This study aimed to synthesize AgNPs using aqueous extracts from Paullinia cupana leaves collected during dry and rainy seasons, prepared by two different methods (agitation or infusion), to evaluate the impact of these variables on the biosynthesis and properties of the nanostructures. Methods: The extracts were characterized by UHPLC-HRMS/MS, and their total phenolic compound (TPC) content and antioxidant potential against DPPH and ABTS radicals were determined. The AgNPs were characterized by UV/Vis spectrophotometry, dynamic light scattering (DLS), zeta potential (ZP), nano-particle tracking analysis (NTA), transmission electron microscopy (TEM), and energy-dispersive X-ray spectroscopy (EDX). Results: The metabolic profile results showed a predominance of alkaloids and flavonoids in all extracts, with greater phytochemical diversity in samples prepared by infusion. TPC indicated superior phenolic extraction in extracts prepared by infusion during the rainy season, correlating with greater antioxidant potential via the elimination of free radicals. The evolution of AgNP synthesis was accompanied by a gradual change in the color of the suspensions and the formation of plasmon bands between 410 and 430 nm, characteristic of spherical AgNPs. The nanostructures presented hydrodynamic diameters between 37.49 and 145.5 nm, PdI between 0.222 and 0.755, and Zeta potential between −11.3 and −39.9 mV, suggesting satisfactory colloidal stability. Morphological analyses revealed predominantly spherical particles with average diameters ranging from 33.61 to 48.86 nm and uniform distribution, while EDX spectra confirmed the presence of silver. Conclusions: Thus, our results demonstrate that both seasonality and the method of extract preparation influence the phytochemical composition and, consequently, the morphology, stability, and optical properties of AgNPs, with subtle emphasis on collections made during the rainy season and extracts prepared by infusion. Such knowledge contributes to the advancement of more reproducible and purpose-oriented syntheses in the field of green nanotechnology, enabling applications in various sectors. Full article

Electron beam powder bed fusion (EB-PBF) Ti6Al4V often exhibits high vertical surface roughness, limiting its use in high-end applications. In this study, an infrared continuous-wave laser was applied to precisely polish the vertical surface. An orthogonal design identified the optimal condition as 10,400 kW/cm² power density, 800 mm/s scanning speed, and one pass, achieving a minimum Sa of 0.24 μm and a 98.03% reduction compared with the as-built surface. To address the adhered semi-molten particle characteristics of EB-PBF sidewalls, a molten-pool-dynamics-based polishing model was developed and validated, yielding an error as low as 1.24%. Simulations indicate that power density governs the final morphology by controlling molten pool coverage, scanning speed affects polishing efficiency via thermocapillary force, and polishing time influences surface quality by triggering or avoiding melt splashing. Full article

In naturally ventilated dairy barns, many questions regarding airflow, indoor air quality, and emissions are still unanswered, often resulting in inaccurate environmental control of the housing. Particularly, limited understanding of the implications of the constantly changing outdoor weather conditions in interaction with the building design and the role of the characteristics of the animals’ movement inside the building enhances uncertainties in the estimation of airflows within and across the barns. Computational fluid dynamics (CFD) have been used in the past to better understand the dynamics of barn climate, but the models are typically too slow to be used for real-time prediction and control. We investigated the effect of animal characteristics (i.e., animal location, orientation, body posture, and dimensions) on the pressure drop in the animal occupied zone considering inlet wind speed from 0.1 m s⁻¹ to 5 m s⁻¹ and wind direction of 0° and 90° in a CFD model. The cow position in general had little impact on the pressure drop at low wind speeds, but became relevant at higher wind speeds. Cows distributed in a more organized alignment showed less airflow resistance, and, therefore, a lower pressure drop and higher air velocities. Moreover, the cow breed affected the pressure drop, with higher withers resulting in a higher pressure drop and air resistance. In contrast, the effects of cow lying–standing ratio on the pressure drop and airflow resistance coefficients were negligible for both investigated wind directions. Our study aims to provide guidance for optimizing parametrizations of the animal occupied zone in order to enhance the speed of simulations without significant loss in model accuracy. In addition, the conclusions drawn from our study may support the adaption of building design and herd management to improve the effectiveness of ventilation concepts of naturally ventilated dairy barns. Full article

In Vehicular Ad Hoc Networks (VANETs), vehicles act as independent nodes that can freely establish connections and exchange messages. However, during data forwarding, vehicle nodes may exhibit selfish behavior due to limited resources such as buffer space and bandwidth, or because of social bias, which leads to a decrease in message delivery rate and an increase in communication overhead. To address this issue, this paper proposes a Dual-Trust Selfish Node Detection Algorithm (DTSDA) based on behavioral and social characteristics. The algorithm first employs a node forwarding behavior evaluation mechanism to detect selfish behaviors caused by resource constraints. Then, it introduces behavioral and social features to construct a dual-trust computation model, which further identifies nodes that are difficult to classify. Finally, a message acknowledgment feedback mechanism is incorporated to detect potential false negatives. Experiments are conducted on the ONE simulation platform, and the proposed DTSDA is compared with STCDA, CCSDA, and DSNDA algorithms. The results demonstrate that DTSDA significantly improves the message delivery rate while reducing the end-to-end delay. This study shows that the proposed algorithm can accurately detect selfish nodes in highly dynamic VANET environments, providing a new approach to enhancing communication reliability in vehicular networks. Full article