Search Results (243)

Asynchronous flowering between male and female date palms (Phoenix dactylifera L.) makes pollen storage a practical necessity for growers, especially for cultivars like ‘Mejhoul’, which require artificial pollination. This study examined the stainability of pollen as an indicator of cytoplasmic integrity, from four male date plant pollen donor genotypes (‘Mejhoul’, ‘Deglet Nour’, ‘Khadrawy’, and ‘Zahidi’) stored at 4 °C for different durations (fresh, one-year, and two-year storage) and their effects on fruit set and physical fruit characteristics of the Mejhoul cultivar in Mexico. Pollen stainability was assessed in vitro using 1% acetocarmine. Fruit and seed set percentages were evaluated as indicators of the practical effectiveness of stored pollen under field conditions, but not as direct measures of viability. Results showed that fresh pollen exhibited the highest stainability (91.2–95.6%), followed by one-year-stored pollen (59.4–68.3%), and two-year-stored pollen (38.8–45.4%). Fruit set percentages were highest with fresh pollen (63.8–81.7%), decreasing with storage duration. ‘Deglet Nour’ pollen consistently showed superior compatibility with ‘Mejhoul’ females. Physical fruit characteristics (weight, length, diameter) and seed traits were minimally affected by reduced pollen stainability, indicating that there were enough viable grains for effective pollination. The study also observed Metaxenia and Xenia effects, where pollen genotypes influenced fruit and seed size. Overall, these findings suggest that pollen stored at 4 °C for short and medium terms can be used in Mejhoul production, but longer storage significantly reduces efficacy, recommending sub-zero temperatures for extended preservation. Full article

Virtual Machine Introspection (VMI) is a powerful technology used to detect and analyze malicious software inside Virtual Machines (VMs) from the outside. Asynchronous access to the VM’s memory can be insufficient for efficient monitoring of what is happening inside of a VM. Active VMI introduces breakpoints to intercept VM execution at relevant points. Especially for frequently visited breakpoints, and even more so for production systems, it is crucial to keep performance overhead as low as possible. In this paper, we present an empirical study that compares the performance of four VMI breakpoint-implementation variants—EPT switching (SLAT view switching) with and without fast single-stepping acceleration, instruction repair, and instruction emulation—from two VMI applications (DRAKVUF, SmartVMI) with the XEN hypervisor on 20 Intel Core i processors ranging from the fourth to the thirteenth generation. Instruction emulation was the fastest method across all 20 tested platforms. Modern processors such as the Intel Core i7 12700H and Intel Core i9 13900HX achieved median breakpoint-processing times as low as 15 µs for the emulation mechanism. The slowest method was instruction repair, followed by EPT switching and EPT switching with FSS. The order was the same for all measurements, indicating that this is a strong and generalizable result. Full article

The rise of English-medium instruction (EMI) in higher education presents challenges for supporting language development alongside disciplinary learning, as it is typically delivered by content specialists with limited time and little or no background in language pedagogy. Against this backdrop, this study examines the effectiveness of computer-assisted content-based structured input (CBSI), compared to input flood (IF) and unmodified disciplinary input (Control), in enhancing students’ acquisition of English verb patterns in an EMI university course in Poland. All participants received the same asynchronous, computer-assisted disciplinary instruction, aligned with the course syllabus. The groups differed only in the type of input enhancement, which was developed by a language specialist in coordination with the course instructor. A split-block design was used to measure learning gains through a pre-test, post-test, and delayed post-test. Students in the CBSI group showed significantly greater and more sustained improvement than those in the IF and Control groups. These findings support CBSI as an effective and pedagogically feasible way to promote language development in EMI, integrating linguistic and disciplinary concerns while respecting the roles and integrity of both domains. Full article

This study develops a stochastic SIQR epidemic model with mean-reverting Ornstein–Uhlenbeck (OU) processes for both transmission rate $\beta \left(t\right)$ and quarantine release rate $k\left(t\right)$; this is distinct from existing non-white-noise stochastic epidemic models, most of which focus on single-parameter perturbation or only stability analysis. It synchronously embeds OU dynamics into two core epidemic parameters to capture asynchronous fluctuations between infection spread and control measures. It adopts a rare measure solution framework to derive rigorous infection extinction conditions, linking OU’s ergodicity to long-term ${\beta }^{+}\left(t\right)$ averages. It obtains the explicit probability density function of the four-dimensional SIQR system, filling the gap of lacking quantifiable density dynamics in prior studies. Simulations validate that $R_0^d<1$ ensures almost sure extinction, while $R_0^e>1$ leads to stable stochastic persistence. Full article

In recent years, quantum network technology has been rapidly developing, with new theories, solutions, and protocols constantly emerging. The breakthrough experiments and achievements are impressive, such as the construction and operation of ultra-long-distance and multi-user quantum key distribution (QKD) networks, the proposal, verification, and experimental demonstration of new network nonlocality characteristics, etc. The results of recent research on QKD and network nonlocality are summarized and analyzed in this paper, including CV-MDI-QKD (continuous-variable measurement-device-independent QKD), TF-QKD (twin-field QKD), AMDI-QKD (asynchronous MDI-QKD), the generalization, sharing, and certification of network nonlocality, as well as the main achievements and related research tools of full network nonlocality and genuine network nonlocality, aiming to identify the current status and future development paths of the QKD and network nonlocality. Full article

Indoor localization of fast-moving targets under asynchronous acoustic sensing is severely constrained by non-line-of-sight (NLOS) propagation and sparse anchor deployments. To overcome these limitations, we propose a trajectory reconstruction-based framework that simultaneously exploits time-of-arrival (ToA) and frequency-of-arrival (FoA) measurements. By embedding temporal continuity and motion dynamics into the localization model, we cast the problem as a constrained nonlinear least squares optimization over the entire trajectory rather than isolated snapshots. To efficiently solve this high-dimensional problem, we design an enhanced particle swarm optimization (PSO) algorithm featuring adaptive phase switching and noise-resilient updates. Simulation results under varying noise conditions show that our method achieves superior accuracy and robustness compared to conventional least squares estimators, especially for high-speed trajectories. Real-world experiments using a passive acoustic testbed further validate the effectiveness of the proposed framework, with over 90% of localization errors confined within 3 m. The method is model-driven, training-free, and scalable to asynchronous and anchor-sparse environments. Full article

The spindle motion error significantly affects the surface quality and dynamic precision of machined workpieces. This study proposes a novel detection method for workpiece surface morphology with arbitrary rotation angles. A mathematical model was established for the relationship between the detection signal, spindle error, and workpiece contour when the workpiece rotates at different angles. Unlike traditional reversal methods, this approach allows a flexible selection of workpiece rotation angles and simplifies calculations. Simulation results demonstrate the method’s accuracy, with the slight mean square errors and determination coefficients R² approaching 1. Experimental validation confirms the method’s reliability. Furthermore, the influences of asynchronous errors and sensor errors on measurement results were systematically investigated, highlighting the importance of increasing sampling periods and accurate positioning of sensors. This method offers a cost-effective and versatile solution for precision machining and can be extended to other rotating machinery applications. Full article

Aiming to address the problems of asynchronous acquisition time of multiple sensors in the crop phenotype acquisition system and high cost of the acquisition equipment, this paper developed a low-cost crop phenotype synchronous acquisition system based on the PTP synchronization protocol, realizing the synchronous acquisition of three types of crop data: visible light images, thermal infrared images, and laser point clouds. The paper innovatively proposed the Difference Structural Similarity Index Measure (DSSIM) index, combined with statistical indicators (average point number difference, average coordinate error), distribution characteristic indicators (Charm distance), and Hausdorff distance to characterize the stability of the system. After 72 consecutive hours of synchronization testing on the timing boards, it was verified that the root mean square error of the synchronization time for each timing board reached the ns level. The synchronous trigger acquisition time for crop parameters under time synchronization was controlled at the microsecond level. Using pepper as the crop sample, 133 consecutive acquisitions were conducted. The acquisition success rate for the three phenotypic data types of pepper samples was 100%, with a DSSIM of approximately 0.96. The average point number difference and average coordinate error were both about 3%, while the Charm distance and Hausdorff distance were only 1.14 mm and 5 mm. This system can provide hardware support for multi-parameter acquisition and data registration in the fast mobile crop phenotype platform, laying a reliable data foundation for crop growth monitoring, intelligent yield analysis, and prediction. Full article

High penetration of photovoltaic (PV) generation presents new challenges for voltage regulation in distribution networks (DNs), primarily due to output intermittency and constrained reactive power capabilities. This paper introduces a distributed voltage control method leveraging reactive power compensation from PV inverters. Instead of relying on centralized computation, the proposed method allows each inverter to make local decisions using real-time voltage measurements and delayed communication with neighboring PV nodes. To account for practical asynchronous communication and feedback delay, a Distributed Online Primal–Dual Push–Sum (DOPP) algorithm that integrates a fixed-step delay model into the push–sum coordination framework is developed. Through extensive case studies on a modified IEEE 123-bus system, it has been demonstrated that the proposed method maintains robust performance under both static and dynamic scenarios, even in the presence of fixed feedback delays. Specifically, in static scenarios, the proposed strategy rapidly eliminates voltage violations within 50–100 iterations, effectively regulating all nodal voltages into the acceptable range of [0.95, 1.05] p.u. even under feedback delays with a delay step of 10. In dynamic scenarios, the proposed strategy ensures 100% voltage compliance across all nodes, demonstrating superior voltage regulation and reactive power coordination performance over conventional droop and incremental control approaches. Full article

Background/Objectives: Migraine is a debilitating neurologic disorder with diet-related triggers. No studies exist on education on migraine in conjunction with an elimination diet as a non-pharmacologic management approach. Methods: Higher education students who self-reported migraine were enrolled in this observational, pilot feasibility study. At baseline, participants completed questionnaires on demographics, migraine disability, and their understanding of migraine and an elimination diet. After one month of self-paced, asynchronous, online modules, participants were reassessed on their understanding of migraine and an elimination diet. Two months later, participants completed follow-up questionnaires on migraine disability, whether they implemented components of the diet, and any barriers they encountered. Results: Of 66 students who completed baseline measures, 33 completed the modules and all questionnaires. Of participants who completed the study, 100% found the modules helpful in learning about migraine and an elimination diet; 57.6% incorporated aspects of the elimination diet into their lives. Participants had significant (p < 0.001) increases in knowledge both about migraine and an elimination diet. Participants had a potentially clinically significant decrease (14-point MIDAS drop, p = 0.10) in migraine symptoms after completing the educational intervention, with a greater decrease among participants who implemented the elimination diet. Conclusions: It is feasible to design and implement an education intervention on diet for higher education students, though loss to follow-up was high in this population. The majority of participants who completed the modules adopted aspects of an elimination diet, indicating its feasibility. Further studies with a larger sample size powered to assess the efficacy of this approach are needed. Full article

Traditional motor temperature rise testing generally uses temperature sensors. To solve problems such as sensor detachment, aging, and space occupation, this study takes a three-phase asynchronous motor as an example to propose a method for building a temperature rise monitoring model driven by a multi-physics field model based on the digital twin framework of power equipment. A twin monitoring model with defined input–output parameters is constructed to solve the problems of measurement inconvenience in traditional methods. Firstly, the losses of the iron core and the winding copper in the motor were obtained through electromagnetic field simulation. Secondly, the temperature distribution of the motor stator was obtained based on the bidirectional coupling characteristics of the magnetic and thermal fields. Subsequently, a temperature field reduced-order model based on the proper orthogonal decomposition method was built in Twin Builder, achieving fast calculation of the motor stator temperature. Finally, using the YE3-80M1-4 motor as the experimental subject, the model’s output results were compared with and validated against the experimental results. The results indicate that the simulation time of the reduced-order model is 2.1 s, and the relative error compared with the test values is within 5%, which confirms the practical applicability of the proposed method. Full article

Star sensors, as the most precise attitude measurement devices currently available, play a crucial role in spacecraft attitude estimation. However, traditional frame-based cameras tend to suffer from target blur and loss under high-dynamic maneuvers, which severely limit the applicability of conventional star sensors in complex space environments. In contrast, event cameras—drawing inspiration from biological vision—can capture brightness changes at ultrahigh speeds and output a series of asynchronous events, thereby demonstrating enormous potential for space detection applications. Based on this, this paper proposes an event data extraction method for weak, high-dynamic space targets to enhance the performance of event cameras in detecting space targets under high-dynamic maneuvers. In the target denoising phase, we fully consider the characteristics of space targets’ motion trajectories and optimize a classical spatiotemporal correlation filter, thereby significantly improving the signal-to-noise ratio for weak targets. During the target extraction stage, we introduce the DBSCAN clustering algorithm to achieve the subpixel-level extraction of target centroids. Moreover, to address issues of target trajectory distortion and data discontinuity in certain ultrahigh-dynamic scenarios, we construct a camera motion model based on real-time motion data from an inertial measurement unit (IMU) and utilize it to effectively compensate for and correct the target’s trajectory. Finally, a ground-based simulation system is established to validate the applicability and superior performance of the proposed method in real-world scenarios. Full article

Asynchronous-pouring construction (APC) technology employs a suspended hanging basket directly supported by corrugated steel webs (CSWs) with high shear strength, significantly enhancing construction efficiency. To further elucidate the characteristics of APC and promote its application in prestressed concrete (PC) composite box girder bridges with CSWs, this study analyzes the sustainable development of APC from two aspects, including environmental impact and economic performance. Finite element models of APC and traditional balanced cantilever construction (TBCC) were established for the case bridge with a main span of 105 m. The stress distribution and deflection of the main girder in the cantilever construction state are compared with field measurements, and the variations in stress and deflection in typical sections during construction are analyzed. Additionally, a simplified theoretical method is proposed for calculating stress and deflection in PC composite girder bridges during the cantilever construction stage using APC. Results demonstrate that APC demonstrates significant advantages in reducing economic costs and minimizing long-term environmental impacts. Furthermore, this method ensures acceptable stress and deflection throughout construction. The proposed simplified formula for CSW deflection in the maximum segment agrees well with both measured data and finite element results, providing a valuable reference for deflection calculation in APC applications. Full article

With the hierarchical evolution of distribution network control architectures, distributed state estimation has become a focal point of research. To address communication delays arising from inter-level data exchanges, this paper proposes a multi-level, asynchronous, robust state estimation algorithm that accounts for such delays. First, a multi-level state estimation model is formulated based on the concept of a maximum normal measurement rate, and a hierarchical decoupling modeling approach is developed. Then, an event-driven broadcast transmission strategy is designed to unify boundary information exchanged between levels during iteration. A multi-threaded parallel framework is constructed to decouple receiving, computation, and transmission tasks, thereby enhancing asynchronous scheduling capabilities across threads. Additionally, a round-based synchronization mechanism is proposed to enforce fully synchronized iterations in the initial stages, thereby improving the overall process of asynchronous state estimation. Case study results demonstrate that the proposed algorithm achieves high estimation accuracy and strong robustness, while reducing the average number of iterations by nearly 40% and shortening the runtime by approximately 35% compared to conventional asynchronous methods, exhibiting superior estimation performance and computational efficiency under communication delay conditions. Full article

As designers push engine efficiency closer to thermodynamic limits, the analysis of flow instabilities developed in a high-pressure turbine (HPT) is crucial to minimizing aerodynamic losses and optimizing secondary air systems. Purge flow, while essential for protecting turbine components from thermal stress, significantly impacts the overall efficiency of the engine and is strictly connected to cavity modes and rim-seal instabilities. This paper presents an experimental investigation of these instabilities in an HPT stage, tested under engine-representative flow conditions in the short-duration turbine rig of the von Karman Institute. As operating conditions significantly influence instability behavior, this study provides valuable insight for future turbine design. Fast-response pressure measurements reveal asynchronous flow instabilities linked to ingress–egress mechanisms, with intensities modulated by the purge rate (PR). The maximum strength is reached at PR = 1.0%, with comparable intensities persisting for higher rates. For lower PRs, the instability diminishes as the cavity becomes unsealed. An analysis based on the cross-power spectral density is applied to quantify the characteristics of the rotating instabilities. The speed of the asynchronous structures exhibits minimal sensitivity to the PR, approximately 65% of the rotor speed. In contrast, the structures’ length scale shows considerable variation, ranging from 11–12 lobes at PR = 1.0% to 14 lobes for PR = 1.74%. The frequency domain analysis reveals a complex modulation of these instabilities and suggests a potential correlation with low-engine-order fluctuations. Full article