Synchronous Model Research Articles

Negative emotions disrupt intentional synchronization during group sensorimotor interaction.

Emotions play a fundamental role in human interactions and trigger responses in physiological, psychological, and behavioral modalities. Interpersonal coordination often entails attunement between individuals in various modalities. Previous research has elucidated the mechanisms of interpersonal synchronization and the emotions aroused by joint action: cardiac activity aligns in disputing marital couples, spectators share enjoyment in observing live dance performances, and joint finger-tapping evokes positive emotions. However, little is known about the impact of emotions on intentional interpersonal synchronization. To address this problem, we conducted an experiment in 2022 asking 60 participants to engage in a three-way finger-tapping synchronization task. We systematically induced emotional states (positive, neutral, and negative) with social comparison feedback using success-failure manipulations. An analysis of behavior synchronization using the Kuramoto order parameter revealed that negative emotion induction significantly diminished time spent in synchrony compared to positive induction. Moreover, the results exposed incremental struggles in attaining higher levels of synchronization (Q2-Q3) after the induction of negative emotions. These outcomes further substantiate the necessity of integrating the indices of agents' emotions into interpersonal synchronization and coordination models. We discuss the implications of this work for research on interpersonal emotion in joint action and applied outcomes in emotion-aware technologies and interventions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Dual three-phase permanent magnet synchronous motors model predictive torque control based on zero common-mode voltage

This article proposes a multi-vector model predictive torque control strategy based on zero common-mode voltage to suppress common-mode voltage and harmonic currents in a dual three-phase permanent magnet synchronous motor. Firstly, 20 zero common-mode voltage vectors are selected from the traditional 64 basic voltage vectors. By synthesizing these 20 vectors into 6 virtual voltage vectors (VVV), control over the harmonic plane is achieved, reducing harmonic currents and eliminating common-mode voltage. Then, the control error of the flux is reduced by increasing the number of vectors to achieve the purpose of reducing the flux ripple. Finally, through duty cycle modulation, multi-vector model predictive torque control extends the modulation range to the entire sector plane. Simulation results confirm that this strategy can effectively suppress harmonic currents and common mode voltage.

The counting principle makes number words unique

Abstract Following Ariel (2021. Why it’s hard to construct ad hoc number concepts. In Caterina Mauri, Ilaria Fiorentini, & Eugenio Goria (eds.), Building categories in interaction: Linguistic resources at work, 439–462. Amsterdam: John Benjamins), we argue that number words manifest distinct distributional patterns from open-class lexical items. When modified, open-class words typically take selectors (as in kinda table), which select a subset of their potential denotations (e.g., “nonprototypical table”). They are typically not modified by loosening operators (e.g., approximately), since even if bare, typical lexemes can broaden their interpretation (e.g., table referring to a rock used as a table). Number words, on the other hand, have a single, precise meaning and denotation and cannot take a selector, which would need to select a subset of their (single) denotation (??kinda seven). However, they are often overtly broadened (approximately seven), creating a range of values around N. First, we extend Ariel’s empirical examination to the larger COCA and to Hebrew (HeTenTen). Second, we propose that open-class and number words belong to sparse versus dense lexical domains, respectively, because the former exhibit prototypicality effects, but the latter do not. Third, we further support the contrast between sparse and dense domains by reference to: synchronic word2vec models of sparse and dense lexemes, which testify to their differential distributions, numeral use in noncounting communities, and different renewal rates for the two lexical types.

Exploring the molecular regulation of vernalization-induced flowering synchrony in Arabidopsis.

Many plant populations exhibit synchronous flowering, which can be advantageous in plant reproduction. However, molecular mechanisms underlying flowering synchrony remain poorly understood. We studied the role of known vernalization-response and flower-promoting pathways in facilitating synchronized flowering in Arabidopsis thaliana. Using the vernalization-responsive Col-FRI genotype, we experimentally varied germination dates and daylength among individuals to test flowering synchrony in field and controlled environments. We assessed the activity of flowering regulation pathways by measuring gene expression across leaves produced at different time points during development and through a mutant analysis. We observed flowering synchrony across germination cohorts in both environments and discovered a previously unknown process where flower-promoting and repressing signals are differentially regulated between leaves that developed under different environmental conditions. We hypothesized this mechanism may underlie synchronization. However, our experiments demonstrated that signals originating from sources other than leaves must also play a pivotal role in synchronizing flowering time, especially in germination cohorts with prolonged growth before vernalization. Our results suggest flowering synchrony is promoted by a plant-wide integration of flowering signals across leaves and among organs. To summarize our findings, we propose a new conceptual model of vernalization-induced flowering synchrony and provide suggestions for future research in this field.

Improving Individual Innovative Behavior and Post-COVID-19 Student’ Learning Outcomes Through Project-Based Blended Learning

Objective: This study aims to improve individual innovative behavior and learning outcomes and determine differences in individual innovative behavior and student learning outcomes after being taught with Project_Based Blended Learning synchronous and asynchronous online models followed by face-to-face offline models in the post-COVID-19 era. Method: The research used a quasi-experiment; the control class samples were 33, and the experimental class was 33 students. Data were collected using questionnaires, test instruments, and observation sheets, and the collected data were analyzed using descriptive statistics, gain tests, and t-tests. Result: The increase in individual innovative behavior and learning outcomes before and after teaching in the control class in the moderately effective category is lower and significantly different compared to the experimental class in the practical category. The final score of individual innovative behavior and learning outcomes of the control class is lower and significantly different than that of the experimental class. Novelty: Blended Learning in this research is integrated with Project-Based Learning with synchronous and asynchronous online models to produce project products assigned to be used in practical courses.

A novel model for transfer synchronization in transit networks and a Lagrangian-based heuristic solution method

To realize the benefits of network connectivity in transfer-based transit networks, it is critical to minimize transfer disutility for passengers by synchronizing timetables of intersecting routes. We propose a mixed-integer linear programming timetable synchronization model that incorporates new features, such as dwell time determination and vehicle capacity consideration, which have been largely overlooked in the literature at the scheduling stage. We introduce a new concept of pre-planned holding time, called transfer buffer time, to reduce the transfer waiting time, particularly for transfers to low-frequency routes, while taking into account the penalty of extra in-vehicle time for onboard passengers and the possible consequences on headway regularity of a route. We develop a Lagrangian relaxation-based heuristic to obtain high-quality solutions efficiently for large instances. Our experiments on instances with up to 12 transfer nodes in the City of Toronto, with a mixture of low- and high-frequency routes, illustrate the potential benefits of the proposed model over the state of the art. The results indicate that incorporating transfer buffer time, dwell time determination, and vehicle capacity consideration improves model outcomes considerably, also demonstrating the computational efficiency of our Lagrangian-based solution method.

Hierarchical synchronization with structured multi-granularity interaction for video question answering

Video Question Answering (VideoQA) requires a thorough comprehension of linguistic and visual modalities. However, recent methods confront two problems: (1) Synchronous modeling of object action and frame scene instead of a step-by-step manner, which can better mine potential semantic attributes of videos, lacks research; (2) The relationship between cross-modal alignments at different granularity of abstraction is not fully utilized. Based on these insights, we propose a novel method named hierarchical synchronization with structured multi-granularity interaction (HSSMI) for VideoQA. First, a hierarchical synchronous reasoning module is put forward to model objects’ relations and dynamics and synchronously capture their synergistic influences over time when analyzing whole frames. It is seen as multiple Object ConvLSTMs (O-CLSTMs) in isolation or a Frame ConvLSTM (F-CLSTM) in collectivity. Specifically, O-CLSTM learns the object-level action states under neighboring spatial interplays. Meanwhile, F-CLSTM learns the frame-level scene state, where action information from O-CLSTMs is selectively aggregated into a common memory cell of F-CLSTM as instructed by questions. Besides, a boundary detector is equipped to discover scene discontinuities, enabling F-CLSTM to alter its time connectivity and adapt its sequential encoding process to videos. Thereafter, we develop a conditional VLAD with topic constraints for discriminative modality summarization. Last, a structured multi-granularity interaction module is proposed to integrate complemented clues on the global alignment between scene summary and full question and the local alignments between action summaries and words. This module encourages useful information passing through compositional syntactical topologies of questions to predict answers. Experiments on three public benchmark datasets demonstrate the superiority of our HSSMI against other state-of-the-art methods. Codes will be publicly available at https://github.com/Qiss33/HSSMI.

Timetable Synchronisation for the First Trains in the Day According to Actual Transfer Times

Non-synchronised timetables of the first hour trains can lead to longer waiting times for passengers wishing to transfer at the transfer station. This study aims to reduce the waiting time of passengers by synchronising the timetables of first hour trains using actual transfer times. The transfer times of the passengers are obtained from the observations and are used in this synchronisation study. The genetic and simulated annealing algorithms are implemented to solve the first train synchronisation model. Finally, a case study is conducted on a section of the Istanbul metro network to test the synchronisation model. The results show that the total waiting time of the first hour trains transfer passengers is reduced by 35% by applying the proposed model. Another result of the study shows that using the actual transfer time instead of the average transfer time of the passengers reduces the average waiting time of the passengers by 19%.

Dynamic multiple-graph spatial-temporal synchronous aggregation framework for traffic prediction in intelligent transportation systems.

Accurate traffic prediction contributes significantly to the success of intelligent transportation systems (ITS), which enables ITS to rationally deploy road resources and enhance the utilization efficiency of road networks. Improvements in prediction performance are evident by utilizing synchronized rather than stepwise components to model spatial-temporal correlations. Some existing studies have designed graph structures containing spatial and temporal attributes to achieve spatial-temporal synchronous learning. However, two challenges remain due to the intricate dynamics: (a) Accounting for the impact of external factors in spatial-temporal synchronous modeling. (b) Multiple perspectives in constructing spatial-temporal synchronous graphs. To address the mentioned limitations, a novel model named dynamic multiple-graph spatial-temporal synchronous aggregation framework (DMSTSAF) for traffic prediction is proposed. Specifically, DMSTSAF utilizes a feature augmentation module (FAM) to adaptively incorporate traffic data with external factors and generate fused features as inputs to subsequent modules. Moreover, DMSTSAF introduces diverse spatial and temporal graphs according to different spatial-temporal relationships. Based on this, two types of spatial-temporal synchronous graphs and the corresponding synchronous aggregation modules are designed to simultaneously extract hidden features from various aspects. Extensive experiments constructed on four real-world datasets indicate that our model improves by 3.68-8.54% compared to the state-of-the-art baseline.

The Influence of Additional Virtual Synchronous Generator Technology in VSC-MTDC Systems with Wind Power on System Frequency

Introduction: A frequency control strategy is proposed based on additional virtual synchronous generator technology for voltage source converter-based multi-terminal high voltage direct current systems with wind power. Method: This strategy addresses the system's inertia reduction and frequency stability issues caused by integrating large amounts of wind power through multi-terminal DC transmission. Firstly, the virtual synchronous generator mathematical model is constructed based on the system structure. Secondly, for the problem of zero rotational inertia of voltage source converter in a flexible DC transmission system, based on the P-U droop control method of the converter station, additional virtual synchronous control generation technology is applied to simulate the P-f droop characteristics of the synchronous generator by adding virtual rotational inertia, so that the converter has the inertial response of synchronous generator to realize primary frequency regulation. Result: Finally, the simulation is verified on the PSCAD/ EMTDC platform with an example of a three-terminal parallel MTDC transmission system. Conclusion: the analyzed results demonstrate that the virtual synchronous generator control strategy is very valuable and useful for improving the frequency performance of the system.

Effectiveness and safety of telehealth medication abortion in the USA

Telehealth abortion has become critical to addressing surges in demand in states where abortion remains legal but evidence on its effectiveness and safety is limited. California Home Abortion by Telehealth (CHAT) is a prospective study that follows pregnant people who obtained medication abortion via telehealth from three virtual clinics operating in 20 states and Washington, DC between April 2021 and January 2022. Individuals were screened using a standardized no-test protocol, primarily relying on their medical history to assess medical eligibility. We assessed effectiveness, defined as complete abortion after 200 mg mifepristone and 1,600 μg misoprostol (or lower) without additional intervention; safety was measured by the absence of serious adverse events. We estimated rates using multivariable logistic regression and multiple imputation to account for missing data. Among 6,034 abortions, 97.7% (95% confidence interval (CI) = 97.2–98.1%) were complete without subsequent known intervention or ongoing pregnancy after the initial treatment. Overall, 99.8% (99.6–99.9%) of abortions were not followed by serious adverse events. In total, 0.25% of patients experienced a serious abortion-related adverse event, 0.16% were treated for an ectopic pregnancy and 1.3% abortions were followed by emergency department visits. There were no differences in effectiveness or safety between synchronous and asynchronous models of care. Telehealth medication abortion is effective, safe and comparable to published rates of in-person medication abortion care.

Synchronizing TSN Devices via 802.1AS over 5G Networks

The 3GPP release 16 integrates TSN functionality into 5G and standardizes various options for TSN time synchronization over 5G such as transparent mode and bridge mode. The time domains for the TSN network and the 5G network are kept separate with an option to synchronize either of the networks to the other. The TSN time synchronization over 5G is possible either by using the IEEE 1588 generalized Precision Time Protocol (gPTP) based on UDP/IP multicast or via IEEE 802.1AS based on Ethernet PDUs. The INET and Simu5G simulation frameworks, which are both based on the OMNeT++ discrete event simulator, are widely used for simulating TSN and 5G networks. The INET framework comprises the 802.1AS based time synchronization mechanism, and Simu5G provides the 5G user plane carrying IP PDUs. We modified the 802.1AS-based synchronization model of INET so that it works over UDP/IP. With that, it is possible to synchronize TSN slaves (connected to 5G UEs), across a 5G network, with a TSN master clock, present within a TSN network, that is connected to the 5G core network. Our simulation results show that 500 microseconds of synchronization accuracy can be achieved with the corrected asymmetric propagation delay of uplink and downlink between the gNodeB (gNB) and the User Equipment (UE). Furthermore, the synchronization accuracy can be improved if the delay difference between uplink and downlink is known.

Explaining long-term bond yields synchronization dynamics in Europe

We present a novel empirical assessment of the determinants of sovereign yield synchronization dynamics in the European Monetary Union. This topic has been seldom addressed in the existing macroeconometric literature. We use a time-varying measure of government bond yields synchronization and Bayesian Model Averaging methods to show that the persistence of synchronization measures differs significantly between GIIPS countries (Greece, Ireland, Italy, Portugal and Spain) and the rest of the monetary union, as well as across periods characterized by whether the zero lower bound of interest rates was binding or not. The degree of synchronization in inflation rates with the rest of the currency area is a robust predictor of the synchronization of sovereign yields, as opposed to economic fundamentals describing the fiscal positions of individual countries. An out-of-sample forecasting exercise reveals that accounting for the most relevant economic fundamentals can lead to improvements in the directional accuracy of the forecasts of yield synchronization rates for GIIPS countries.

Control strategy and research on energy storage unit participation in power system frequency regulation based on VSG technology

When large-scale photovoltaic power plants are integrated into the grid, it will cause the grid-connected capacity to gradually expand, causing greater harm to the safe and stable operation of the power system, which will affect the FM characteristics of the power system. This requires the PV power plant to actively participate in power system frequency control. Through the PV virtual synchronous generator frequency control technology, coupled with the virtual synchronous PV power plant modeling, the PV new energy units can have the same frequency control characteristics as synchronous generator sets. In the virtual synchronous technology, due to the existence of damping windings, electromagnetic damping will be generated, and it is also due to virtual damping that the virtual synchronous technology has the ability to damp power oscillations. It is also because of the excellent virtual inertia and damping characteristics of the virtual synchronous generator in the grid that this FM technology helps to regulate the frequency fluctuations of the new energy grid, meet the requirements of the power system to maintain stable operation, and then realize the large-scale PV grid connection.

The Efficacy of the MOOC+SPOC Synchronous Learning Model in Vocational Education for Process Control Systems

Incorporating the Industrial Revolution into vocational education, particularly in enhancing curriculum and learning, encounters numerous obstacles. Utilizing technology in interactive learning is anticipated to actively involve learners and enhance their abilities in critical thinking, creativity, innovation, and problem-solving. This study emphasizes the limitations of traditional learning approaches in Process Control Systems and presents a novel framework of MOOC+SPOC Synchronous using a Research and Development (R&D) methodology. The Process Control System course encounters impediments that negatively impact the graduation rate, which is suboptimal. The merging of MOOC (Massive Open Online Course) and SPOC (Small Private Open Course) models into a synchronous MOOC+SPOC learning model seeks to enhance learning outcomes through the utilization of a cloud computing-based Virtual Remote Laboratory (VRLab). The outcome is a model that has been rigorously evaluated and proven effective through empirical research. The research data demonstrated this model's statistically significant positive effect on enhancing student learning outcomes. The Pre-Test and Post-Test results revealed that the experimental group experienced a notable improvement in learning outcomes, with an increase ranging from 10% to 46%. In comparison, the control group also exhibited increased learning outcomes, ranging from 5% to 39%. The statistical analysis reveals a consistent and significant growth in the Experimental group, indicating that students exhibit a favorable level of motivation throughout the learning process, as indicated by the average significance value exceeding 0.5. Based on the test findings acquired from this study, it can be concluded that the Synchronous MOOC+SPOC model is a viable alternative for addressing future difficulties in vocational education. This model is effective and has been proven to work.

Correlation of strontium anharmonicity with charge-lattice dynamics of the apical oxygens and their coupling to cuprate superconductivity

By means of Cu K edge x-ray absorption spectra of overdoped high-pressure oxygenated superconducting and , we demonstrate a remarkably strong three way correlation between the superconductivity and the local dynamics of their highly anharmonic Cu–Sr and Cu-apical O pairs. We model the latter as aspects of the Internal Quantum Tunneling Polarons (IQTPs) that give the two-site distributions in extended x-ray absorption fine structure and inelastic pair distribution function measurements. This finding obviates the common assumption that the universal Ba/Sr-apical O dielectric layer, far from only maintaining the separation of charges between the charge reservoir and the conducting domains, plays an unexpectedly active role in the unusual electronic properties of cuprate superconductors. Furthermore, we investigate the effects of the dynamic structure associated with these pairs by means of the exact diagonalization of a prototype Hamiltonian based on a six-atom cluster, with two neighboring Cu-apical O pairs bridged by an anharmonically coupled Sr atom and a planar O atom. In terms of the Kuramoto model for synchronization, these calculations show a first order phase transition, driven by anharmonicity, to a synchronized state of the IQTPs, in which a fraction of the charge originally confined to the apical O sites is transferred onto the planar O in the superconducting plane. This combination of experimental results and theory demonstrates that the Ba/Sr-apical O layer of cuprates most likely plays an important role in high temperature superconductivity via its collective charge dynamics.

Efficient and lightweight grape and picking point synchronous detection model based on key point detection

Precise positioning of fruit and picking point is crucial for harvesting table grapes using automated picking robots in an unstructured agricultural environment. Most studies employ multi-step methods for locating picking points based on fruit detection, leading to slow detection speed, cumbersome models, and algorithmic fragmentation. This study proposes an improved YOLOv8-GP (YOLOv8-Grape and picking point) model based on YOLOv8n-Pose to solve the problem of simultaneous detection of grape clusters and picking points. YOLOv8-GP is an end-to-end network that integrates object detection and key point detection. Specifically, the Bottleneck in C2f is replaced with FasterNet Block that incorporates EMA (Efficient Multi-Scale Attention), resulting in C2f-Faster-EMA. BiFPN is applied to substitute the original PAN as Neck network. The FasterNet Block, designed based on partial convolution (PConv), reduces redundant computation and memory access, thereby extracting spatial features more efficiently. The EMA attention mechanism achieves performance gains with lower computational overhead. Furthermore, BiFPN is employed to enhance the effect of feature fusion. Experimental results demonstrate that YOLOv8-GP achieves AP of 89.7 % for grape cluster detection and a Euclidean distance error of less than 30 pixels for picking point detection. Additionally, the number of Params is reduced by 47.73 %, and the model complexity GFlops is 6.1G. In summary, YOLOv8-GP offers excellent detection performance, while the reduced number of parameters and model complexity contribute to lower deployment costs and easier implementation on mobile robots.

Synchronization of non-smooth chaotic systems via an improved reservoir computing

The reservoir computing (RC) is increasingly used to learn the synchronization behavior of chaotic systems as well as the dynamical behavior of complex systems, but it is scarcely applied in studying synchronization of non-smooth chaotic systems likely due to its complexity leading to the unimpressive effect. Here proposes a simulated annealing-based differential evolution (SADE) algorithm for the optimal parameter selection in the reservoir, and constructs an improved RC model for synchronization, which can work well not only for non-smooth chaotic systems but for smooth ones. Extensive simulations show that the trained RC model with optimal parameters has far longer prediction time than those with empirical and random parameters. More importantly, the well-trained RC system can be well synchronized to its original chaotic system as well as its replicate RC system via one shared signal, whereas the traditional RC system with empirical or random parameters fails for some chaotic systems, particularly for some non-smooth chaotic systems.

Development of Synchronous Transportation Model for Trackless Vehicle Dispatching During the Construction of Long‐Distance Single‐Headed Shield Tunnel

With the increasing demands for long‐distance single‐headed tunnels, trackless vehicles have been widely accepted for transporting construction materials from storage yard to working face. During the trackless transportation of construction materials, the synchronization of material supply and shield tunneling is critical to ensure tunneling efficiency. However, there is still a lack of a reliable synchronous transportation model for trackless vehicle dispatching. In the present study, the material transportation processes and vehicle transportation parameters have been investigated based on the Sutong GIL Yangtze River Crossing Cable Tunnel. The synchronous transportation model has been established to improve transportation efficiency during the construction stage. An optimized scheme of vehicle schedule has been proposed to minimize trackless vehicle and retention time. Comparative analysis has been carried out to evaluate the trackless vehicle and retention time between the optimized scheme and the original scheme. The results indicate that the number of dual‐headed trucks required for material transportation decreases from nine to six, and the maximum retention time decreases from 166 to 35 min. Compared with the original scheme, the optimized scheme is available for reducing the number of trackless vehicles and improving the efficiency of material transportation. The present study contributes to optimizing material transport scheduling and synchronizing material supply with tunnel excavation in long‐distance single‐headed shield tunnels.

Inertia Estimation Through Covariance Matrix

This work presents a technique to estimate on-line the inertia of a power system based on ambient measurements. The proposed technique utilizes the covariance matrix of these measurements and solves an optimization problem that fits such measurements to the synchronous machine classical model. We show that the proposed technique is adequate to accurately estimate the actual inertia of synchronous machines and also the virtual inertia provided by the controllers of converter-interfaced generators that emulate the behavior of synchronous machines. We also show that the proposed approach is able to estimate the equivalent damping of the classical synchronous machine model. This feature is exploited to estimate the droop of grid-following converters, which has a similar effect of the swing equation equivalent damping. The technique is comprehensively tested on a modified version of the IEEE 39-bus system as well as on a dynamic 1479-bus model of the all-island Irish transmission system.