Synchronous Model Research Articles

Distributed Database Architectures for Federated Medical Training

Federated Learning (FL) has emerged as a promising approach for collaborative medical model training while preserving patient privacy. This research proposes the integration of FL with distributed database architectures to enable secure and efficient medical model training across diverse healthcare institutions. The approach addresses challenges such as real-time data synchronization, data heterogeneity, and low-latency model updates. Key innovations include hybrid SQL/NoSQL databases for structured and unstructured data, dynamic partitioning for improved data locality, and adaptive indexing for optimized query performance. The system incorporates secure data handling mechanisms like encryption and differential privacy, ensuring compliance with healthcare regulations. Scalability is achieved through decentralized database management, enabling broad healthcare node participation. The framework’s effectiveness is evaluated in real-world smart healthcare networks, focusing on model accuracy, query latency, scalability, and energy efficiency, with potential impacts on personalized medicine and collaborative healthcare analytics.

DEVS-Based CDC Synchronizer Design for Fast Debugging of Metastability

This paper proposes a DEVS (Discrete Event System Specification) formalism-based approach to analyze Clock Domain Crossing (CDC) issues in digital circuit design. As modern System on Chip (SoC) designs increasingly integrate multiple clock domains, the verification of CDC-related metastability becomes more challenging and costly. While conventional EDA tools offer solutions for CDC analysis, they often involve substantial computational resources and licensing costs. We present a DEVS-based simulation framework that leverages its inherent advantages in time management and modular structuring to model and analyze CDC scenarios. The framework includes a CDC synchronizer model implemented within the HDL partially compatible DEVS environment, enabling precise analysis of metastability violations based on setup time and hold time requirements. Circuit designers or related engineers can potentially solve timing issues such as CDC by incorporating DEVS-based analysis tools into the design pipeline.

A Comprehensive Review of Smartphone and Other Device-Based Techniques for Road Surface Monitoring

Deteriorating road infrastructure is a global concern, especially in low-income countries where financial and technological constraints hinder effective monitoring and maintenance. Traditional methods, like inertial profilers, are expensive and complex, making them unsuitable for large-scale use. This paper explores the integration of cost-effective, scalable smartphone technologies for road surface monitoring. Smartphone sensors, such as accelerometers and gyroscopes, combined with data preprocessing techniques like filtering and reorientation, improve the quality of collected data. Machine learning algorithms, particularly CNNs, are utilized to classify road anomalies, enhancing detection accuracy and system efficiency. The results demonstrate that smartphone-based systems, paired with advanced data processing and machine learning, significantly reduce the cost and complexity of traditional road surveys. Future work could focus on improving sensor calibration, data synchronization, and machine learning models to handle diverse real-world conditions. These advancements will increase the accuracy and scalability of smartphone-based monitoring systems, particularly for urban areas requiring real-time data for rapid maintenance.

Separable synchronous auxiliary model adaptive momentum estimation strategy for a time-varying system with colored noise from on-line measurements.

The primary focus of this article is to explore parameter estimation for time-varying systems affected by colored noise. Based on the attributes of the time-varying system with colored noise under investigation, the original system is separated and two different subsystems are reconstructed. To address the influence of the hidden variables in the system and the time-varying noise signal, we introduce auxiliary models into the reconstructed systems to achieve the separation and synchronization estimation of the time-varying parameters within the system. With the aim of achieving high-precision performance in estimating the time-varying parameters, a separable synchronous auxiliary model adaptive momentum algorithm is presented by introducing bias correction to the momentum and gradient square term and online parameter estimation is implemented. The proposed algorithm is used for estimating the time-varying output error moving average model to verify the performance. The results of simulation experiments illustrate the efficacy of the proposed method for estimating the time-varying system with colored noise. Additionally, the proposed algorithm is extended to a kind of direct current (DC) motor modeling parameter identification problem and shows good tracking performance.

Efficient Asynchronous Multi-Participant Vertical Federated Learning

Vertical Federated Learning (VFL) is a private-preserving distributed machine learning paradigm that collaboratively trains machine learning models with participants whose local data overlap largely in the sample space, but not so in the feature space. Existing VFL methods are mainly based on synchronous computation and homomorphic encryption (HE). Due to the differences in the communication and computation resources of the participants, straggling participants can cause delays during synchronous VFL model training, resulting in low computational efficiency. In addition, HE incurs high computation and communication costs. Moreover, it is difficult to establish a VFL coordinator (a.k.a. server) that all participants can trust. To address these problems, we propose an efficient Asynchronous Multi-participant Vertical Federated Learning method (AMVFL). AMVFL leverages asynchronous training which reduces waiting time. At the same time, secret sharing is used instead of HE for privacy protection, which further reduces the computational cost. In addition, AMVFL does not require a trusted entity to serve as the VFL coordinator. Experimental results based on real-world and synthetic datasets demonstrate that AMVFL can significantly reduce computational cost and improve the accuracy of the model compared to five state-of-the-art VFL methods.

On the semiclassical limit of the Schrödinger-Lohe model and concentration estimates

We study the semiclassical limit of quantum synchronization model and concentration estimates for the resulting limit model. From the Schrödinger-Lohe model, we rigorously derive the Vlasov-Lohe model using Wigner transform and Wigner measure method. In semiclassical limit, generalized Wigner distributions to the Schrödinger-Lohe model converge to a set of Wigner measures which corresponds to a weak solution to the Vlasov-Lohe model, and then we show the asymptotic collective behaviors of the Vlasov-Lohe model. When one-body potentials are identical, we show that complete synchronization emerges for the Vlasov-Lohe model. In contrast, for non-identical potentials the lack of boundedness results in practical synchronization for the integrals of solutions. Moreover, we construct a global existence of classical solutions to the Vlasov-Lohe model using the standard method of characteristics. Analysis in this work can deal with possibly non-identical potentials in which their differences are constant.

Mutual Synchronization of Spintronic Nano-Oscillator Ensembles

Introduction. The use of spintronic components significantly enhances the performance, reduces the size, and lowers the power consumption of modern electronic devices. The spintronic oscillator (SO) is an integral part of spintronic devices. Connecting several SOs (> 100) into ensembles with subsequent synchronization mitigates such SO drawbacks as low output power and high phase noise. These drawbacks appear as a result of an increase in the output power of an SO ensemble compared to a single oscillator under a simultaneous decrease in the spectral linewidth of the ensemble.Aim. To investigate the impact of connection topologies, synchronization mechanisms, and oscillator failures on the synchronization of oscillator ensembles.Materials and methods. The Kuramoto phase model was used to simplify the numerical modeling of synchronization of SOs connected into an ensemble.Results. A Kuramoto equation for phases of SOs connected in an ensemble was derived, and the influence of connection topologies and oscillator failures on the synchronization parameters of an ensemble of N connected oscillators was demonstrated.Conclusion. In order to ensure the shortest transition time of an SO ensemble to the synchronous mode, topologies with a higher number of connections between oscillators (e.g., "all-to-all") are preferable. The results obtained confirm the advantages of local connection of an SO ensemble by a common current, thus forming an "all-to-all" topology. This makes the transition time of the SO ensemble to the synchronous mode less dependent on both oscillator failures and the number of synchronized SOs.

Flows, circulations, and energy transport in the outer and deep atmospheres of synchronous and non-synchronous hot Jupiters

Aims. Recent studies have shown that vertical enthalpy transport can explain the inflated radii of highly irradiated gaseous exoplanets. Simultaneously, they have also shown that rotation can influence this transport, leading to highly irradiated, rapidly rotating objects that are uninflated. Here, we explore the flows that underpin this transport, including the impact of synchronous or non-synchronous rotation. Methods. We used DYNAMICO to run a series of long timescale HD209458b-like atmospheric models at various rotation rates. For models that are tidally locked, we considered rotation rates between 1/16th and 40 times the rotation rate of HD209458b, whilst for non-synchronous models, we considered the range one-eighth to four times HD209458b. Results. We find that our synchronous models fall into one of three Ω-dependent regimes. At low Ω, we find that the outer atmosphere dynamics are driven by a divergent day-night wind, which drives weak vertical transport and can lead to the formation of a night-side hot-spot. At intermediate Ω, we find classical hot Jupiter dynamics, whilst at high Ω we find a strong Coriolis effect that suppresses off-equator dynamics, including the jet-driving standing waves, thus also reducing vertical transport. As for non-synchronicity, when small, we find that it has little effect on the dynamics. However as it grows, we find that temporal variations prevent the formation of the persistent structures that drive large-scale dynamics and transport. Conclusions. We find that rotation can significantly impact the atmospheric dynamics of irradiated exoplanets, including vertical enthalpy advection, which may help explain the scatter in the hot Jupiter radius-irradiation relation. We have also identified a seemingly robust atmospheric feature at slow rotation: a night-side hot-spot. As this may have important implications for both the phase curve and atmospheric chemistry, we suggest that this study be followed up with next-generation global circulation models (GCMs) that robustly model radiation and chemistry.

Green path development: The agency of the City of Vaasa in establishing the battery industry

AbstractEmpirical studies on agency in green path development (GPD) have underexplored non‐firm actors' roles. Through a semi‐structured interview, this article provides insight into how the City of Vaasa exercises agency toward developing the battery industry and the concomitant effects. The findings reveal that the City of Vaasa provides place‐based leadership, for example, through a local‐based initiative, that is, the GigaVaasa, as a platform to increase participation and coordinate the actions of public and private actors. As an institutional entrepreneur, they govern the issuance of operating licenses to optimize their economic interest; as innovative entrepreneur, they strategically plan and coordinate infrastructure development to increase the region's attractiveness to external investors and talents. The City of Vaasa agency increases the chances for the region to participate in the global battery market and stimulate the region's economic development. Nonetheless, environmental sustainability concerns remain a profound unintended effect. Conceptually, the article introduces the agency cyclicality and synchronization model to enhance the understanding of the interplay and effect of agency in an emerging green industry's development trajectory.

Almost global synchronization of Kuramoto oscillators with symmetry breaking terms

M.A. Lohe first proposed the high-dimensional Kuramoto model with symmetry-breaking terms (Quantum synchronization over quantum networks, Journal of Physics A: Mathematical and Theoretical, 43:465301, 2010), which is the real form of a quantum network synchronization model. For the homogeneous case, by analyzing the limit set and the spectrum of the linearized model, the almost global synchronization is derived from the topology of some kind of connecting graphs.

A Study Of Accreditation Status Synchronization And Regional Public Service Agency As A Model Of Public Health Service (Puskesmas) Management Improvement

Indonesia still has public health centre (Puskesmas) health care issues. The data from Bengkulu is comparable to those from the national level. It shows that Puskesmas has not maximised gatekeeping. We need responsible Puskesmas management and high-quality, sustainable health care to address these problems. Pushesmas' accreditation and Regional Public Service Agency status help the government improve Puskesmas administration. We need a synchronization model because we implement accreditation and BLUD separately. Given the current situation, this study explores potential synchronization strategies between accreditation and BLUD to enhance Puskesmas management. The study describes the condition of accredited and BLUD Puskesmas, identifies the problems, investigates the role capabilities of the parties involved, seeks to synchronise Puskesmas management, and formulates a strategy to improve management. This qualitative descriptive research uses a case study approach with purposive sampling to examine Puskesmas, an accredited and BLUD school in Bengkulu Province. Researchers conduct in-depth interviews, observations, library studies, and documentation. Researchers analyse data through collection, reduction, presentation, and verification or conclusion. They also triangulate data, sources, and procedures for data validity analysis. This research created a Puskesmas Management Improvement Strategy Model as a Novelty

Clinical Effects of Asynchronous Provider-Guided Practice Sessions During Blended Care Therapy for Anxiety and Depression: Pragmatic Retrospective Cohort Study.

Blended care therapy models are intended to increase the efficiency and effectiveness of evidence-based psychotherapy by combining synchronous and asynchronous components of care. This retrospective cohort study evaluated the clinical effects of synchronous video therapy sessions and asynchronous guided practice session elements on anxiety and depression in a blended care therapy program, with a novel focus on asynchronous provider feedback messages. Participants were adults (N=33,492) with clinical symptoms of anxiety (Generalized Anxiety Disorder 7-item scale [GAD-7] score of ≥8) and depression (Patient Health Questionnaire 9-item scale [PHQ-9] score of ≥10) at intake. Symptom trajectories were evaluated via individual growth curve models. Time-varying covariates evaluated effects of synchronous video session attendance and the presence or absence of each asynchronous guided practice session element occurring within 7 days and 8-14 days prior to each clinical outcome assessment. Guided practice session elements included client digital lesson completion, client digital exercise completion, and feedback messages sent by providers. Approximately 86.6% (29,012/33,492) of clients met criteria for clinical improvement by end of care (median 6, IQR 4-8 synchronous sessions). Synchronous video session attendance and client digital lesson completion in the past 7 days and in the past 8-14 days were each uniquely and significantly associated with lower GAD-7 scores (video session effects: bsession7=-0.82, bsession8-14=-0.58, P values<.001; digital lesson effects: blesson7=-0.18, blesson8-14=-0.26, P values <.001) and PHQ-9 scores (video session effects: bsession7=-0.89, bsession8-14=-0.67, P values <.001; digital lesson effects: blesson7=-0.12, blesson8-14=-0.30, P values <.001). Client digital exercise completion in the past 8-14 days was significantly associated with lower GAD-7 scores (bexercise8-14=-0.10; P<.001) but exercise completion in the 7 days prior to clinical outcome assessment was not (bexercise7=0.00; P=.89). Exercise completion in the past 7 days was significantly associated with lower PHQ-9 scores (bexercise7=-0.16; P<.001) but exercise completion in the past 8-14 days was not (bexercise8-14=-0.05; P=.09). Provider feedback messaging in the past 7 days and in the past 8-14 days was significantly associated with lower GAD-7 and PHQ-9 scores, respectively (GAD-7: bfeedback7=-0.12, P<.001; bfeedback8-14=-0.07, P=.004; PHQ-9: bfeedback7=-0.15, P<.001; bfeedback8-14=-0.08, P=.01). Provider feedback between synchronous therapy sessions provided significant benefit for symptom reduction, beyond the effects of client digital engagement and synchronous video sessions. When guided practice sessions are well integrated into care, blended care therapy provides meaningful improvements upon the traditional, synchronous session-only therapy model. Provider guidance and feedback for clients between synchronous sessions support more efficient and effective mental health care overall.

Analysis of rotor vibration characteristics of surface mounted permanent magnet synchronous motor under air gap eccentricity fault

Taking a permanent magnet synchronous motor as the research object, the effect of air gap eccentricity fault on the vibration response characteristics of the motor rotor is analyzed through theoretical calculations, numerical simulation and finite element simulation. First, the change of air gap magnetic field under air gap eccentricity fault is analyzed, and then further calculated to obtain the unbalanced magnetic force under air gap fault by the expression of air gap magnetic field, at last, the rotor’s vibration response characteristics under the action of unbalanced electromagnetic force are obtained by the Newmark- β calculation method. Detailed analysis of the effects of eccentricity distance, eccentricity angle and motor pole-pair number on motor rotor vibration. Finally, the synchronous motor eccentricity fault model is built in ANSYS Maxwell electromagnetic simulation software, and the change characteristics of rotor unbalanced magnetic force after eccentricity fault are calculated and the results are consistent with the theoretical calculations.

Research on inertia characteristics of two-stage photovoltaic systems under generalized sag control

With the vast majority of photovoltaic (PV) power generation linked to the grid, the mainstream maximum power point tracking control cannot provide effective inertia support capability for the system. This paper examines the inertia source and action rules of three typical grid-tied photovoltaic systems under generalized sag control at the physical mechanism level, using the theory of the static synchronous generator model as a guide. It is found that the PV system under generalized sag is also capable of supporting the system through inertia. The boost converter, direct current bus capacitor, and inverter all contribute to the inertia capability of the PV system, but it is necessary to couple the control of the responding link with the grid frequency. The closer the action link is to the grid, the faster the speed of the corresponding grid frequency, but the weaker the inertia effect is provided to the system. The accuracy of the aforementioned analysis is confirmed by the simulation.

The Role of e-Learning During Martial Law: The Ukrainian Experience

The research aim is to reveal the role of e-learning during Martial law by the example of Ukrainian experience. It focuses on the following objectives: to outline the advantages and challenges of e-learning; to describe the peculiarities of implementation of e-learning at the different levels of education; to analyse teaching methods used to integrate e-learning; and to develop the recommendations to implement e-learning. The systemic literature review was carried out to provide an objective summary of the current topic. All sources were published between March, 2022 and May, 2024. The literature focused on e-learning in Ukraine or similar conflict-affected areas. All articles were available in English or Ukrainian. To analyse the data, the synthesis method was applied. The findings proved that e-learning became an important tool during emergencies, providing continuity in education. It was explained that e-learning is introduced at primary, secondary, and higher levels of education. It includes synchronous and asynchronous models. Certain teaching methods are used to implement e-learning effectively. They relate to interactive simulations, multimedia content, gamification, discussion forums, and personalized learning. These methods, combined, create a dynamic e-learning environment that enhances students’ educational outcomes, particularly during emergencies. The implementation of e-learning in Ukraine during Martial law requires careful consideration of the recommendations: enhancement of digital infrastructure, adoption of flexible learning, formation of digital literacy, support of mental health, using interactive methods, increase of content quality, regular assessment, encouragement of positive teacher-student interaction, implementation of adaptive learning tools, and protection of students and educators' data. The research outcomes on the role of e-learning during Martial law can be used for the development of strategic plan of implementation of e-learning tools within the learning process in the regions affected by war or other emergencies. Also, the study can contribute to future educational practices, encouraging the development of more innovative learning solutions.

VividWav2Lip: High-Fidelity Facial Animation Generation Based on Speech-Driven Lip Synchronization

Speech-driven lip synchronization is a crucial technology for generating realistic facial animations, with broad application prospects in virtual reality, education, training, and other fields. However, existing methods still face challenges in generating high-fidelity facial animations, particularly in addressing lip jitter and facial motion instability issues in continuous frame sequences. This study presents VividWav2Lip, an improved speech-driven lip synchronization model. Our model incorporates three key innovations: a cross-attention mechanism for enhanced audio-visual feature fusion, an optimized network structure with Squeeze-and-Excitation (SE) residual blocks, and the integration of the CodeFormer facial restoration network for post-processing. Extensive experiments were conducted on a diverse dataset comprising multiple languages and facial types. Quantitative evaluations demonstrate that VividWav2Lip outperforms the baseline Wav2Lip model by 5% in lip sync accuracy and image generation quality, with even more significant improvements over other mainstream methods. In subjective assessments, 85% of participants perceived VividWav2Lip-generated animations as more realistic compared to those produced by existing techniques. Additional experiments reveal our model’s robust cross-lingual performance, maintaining consistent quality even for languages not included in the training set. This study not only advances the theoretical foundations of audio-driven lip synchronization but also offers a practical solution for high-fidelity, multilingual dynamic face generation, with potential applications spanning virtual assistants, video dubbing, and personalized content creation.

Application of Synchronous Evaluation-Diagnosis Model with Quantitative Stressor-Response Analysis (SED-QSR) to Urban Lake Ecological Status: A Proposed Multiple-Level System.

Ecological integrity assessment and degradation diagnosis are used globally to evaluate the health of water bodies and pinpoint critical stressors. However, current studies mainly focus on separate evaluation or diagnosis, leading to an inadequate exploration of the relationship between stressors and responses. Here, based on multiple data sets in an urban lake system, a synchronous evaluation-diagnosis model with quantitative stressor-response analysis was advanced, aiming to improve the accuracy of evaluation and diagnosis. The weights for key physicochemical stressors were quantitatively determined in the sequence of NDAVIadj > CODMn > TP > NH4+-N by the combination of generalized additive model and structural equation modeling, clarifying the most significant effects of aquatic vegetation on the degradation of fish assemblages. Then, sensitive biological metrics were screened by considering the distinct contributions of four key stressors to alleviate the possible deviation caused by common methods. Finally, ecological integrity was evaluated by summing the key physicochemical stressors and sensitive biological metrics according to the model-deduced weights instead of empirical weights. Our system's diagnosis and evaluation results achieved an accuracy of over 80% when predicting anthropogenic stress and biological status, which highlights the great potential of our multiple-level system for ecosystem management.

Transient Synchronous Stability Modeling and Comparative Analysis of Grid-Following and Grid-Forming New Energy Power Sources

New energy power sources can be categorized into grid-following and grid-forming types based on their synchronization characteristics with the grid. Due to the different basic control operation principles of these two types of new energy power sources, they can lead to the instability of the grid-connected system through different paths. A mathematical model is established to describe the dynamic characteristics of the grid-following and the grid-forming new energy power resources, and the control block diagram of the nonlinear dynamic characteristic equation is compared and analyzed. The similarity between grid-following and grid-forming new energy power supply is revealed, and we preliminarily discuss the influencing factors of the stability of new energy sources. Using a single-machine infinite system model, the influence of key control parameters on transient stability is separately investigated for grid-following and grid-forming types. The influence of the converter synchronous loop control parameters on the system is verified, and the factors affecting the stability are discussed in combination with current limiting and frequency limiting. The research will provide reference for the design of a new energy power grid connection system.

Knowledge embedding synchronous surrogate modeling for multi-objective operational reliability evaluation of complex mechanical systems

To effectively assess the multi-objective operational reliability of complex mechanical system, the concept of Knowledge Embedding Surrogate Modeling (KeSM) is proposed by integrating Knowledge-based Decomposition-Coordination (K-DC) strategy, Knowledge-based Parameter Decomposition (K-PD) strategy, and the surrogate model. In this concept, the K-DC strategy is used to decompose a complex problem into several smaller sub problems, coordinating outcomes from the bottom-up; the K-PD is applied to decompose complex parameters into two parts: associated trends and local fluctuations; the surrogate model is adopted to establish the mapping relationship between input and output. Under this concept, the Knowledge Embedding Synchronous Surrogate Modeling (S-KeSM) multi-objective operational reliability evaluation method is developed by combining linkage important sampling technique and synchronous modeling thought with KeSM concept. In addition, an engineering case (civil aircraft braking system temperature with multi-failures) is employed to validate the proposed method. Through comparison and validation with multiple methods, the results show that the proposed method has significant advantages in analysis accuracy and efficiency. This study can provide theoretical references for the multi-objective operational reliability evaluation of complex mechanical systems.

Low concentration dimethyl sulfoxide (DMSO) modulates epileptiform synchronization in the 4-aminopyridine in vitro model

Dimethyl sulfoxide (DMSO) is commonly used to dissolve water-insoluble drugs due to its dipolar and aprotic properties. It also serves as a vehicle in many pharmacological studies. However, it has been reported that DMSO can induce seizures in human patients, lower seizure threshold in vivo, and modulate ion receptors activities in vitro. Therefore, we investigated here the effect of 0.03 % and 0.06 % DMSO, which are 10–50 times lower than what usually employed in previous studies, in the 4-aminopyridine (4AP) model of epileptiform synchronization in male mouse brain slices. We found that 0.03 % and 0.06 % DMSO increase 4AP-induced ictal discharge rate, while 0.06 % DMSO decreases ictal discharge duration. Our results suggest that the effects of DMSO on neuronal excitability deserve further analysis and that investigators need to be aware of its confounding effect as a solvent, even at very low concentrations.