A bayesian approach for parameterizing and predicting plasmid conjugation dynamics by Sirinapa Kumsuwan, Chanon Jaichuen, Chakachon Jatura, Pakpoom Subsoontorn

“…This approach treats model parameters as random variables whose probability distributions are informed by data on plasmid population dynamics. …”
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Dynamics of Green and Conventional Bonds: Hedging Effectiveness and Sustainability Implication by Rihab Belguith

“…To this end, we employ a time-varying parameter vector autoregression (TVP-VAR), first deriving dynamic variance–covariance matrices and then conducting variance decomposition analysis to gauge connectedness and spillover effects of various bond benchmarks. …”
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Dynamic switching of transmission modes hydroacoustic communication MAC protocols by Chun Shi, Zijian Huang, Huiping Li, Yinbin Cai, Cuifeng Du

“…Hydroacoustic communication networks suffer from issues such as long propagation delays and rapid dynamic changes in network load, which prevent the maximization of network performance through the use of a single transmission mode. …”
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Relational dynamics and Page-Wootters formalism in group field theory by Andrea Calcinari, Steffen Gielen

“…As a result, different canonical formalisms for group field theory have been discussed in the literature. We address these issues using a parametrised version of group field theory, in which all (geometry and matter) degrees of freedom evolve in a fiducial parameter. …”
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Coupled Dynamics Modeling and Validation of Maglev Vehicle and Bridge Systems by Fei Zhou, Xiaolong Li

“…To address the vehicle-bridge coupling vibration issue of the Qingyuan Maglev Tourist Line, it is necessary to establish a maglev vehicle–bridge coupling dynamics simulation model that reflects the actual line conditions. …”
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Quantifying the Dynamic Stability of Gait Patterns in People with Hallux Valgus by Chaneun Park, Nyeonju Kang, KyoungKyu Jeon, Kiwon Park

“…Previous studies evaluating abnormal gait patterns caused by deformity used spatiotemporal parameters; however, they failed to characterize the overall gait dynamics. …”
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Influence of Bracing Systems on Pile Design Parameters: A Structure–Soil–Pile Interaction Approach by Seyma Teberik, Fatih Celik, Ersin Aydin

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Development of an information measuring and control system for a quadrocopter by V. V. Sleptsov, V. L. Afonin, A. E. Ablaeva, Ba Phuong Dinh

“…The article deals with the issues of synthesis and analysis of information-measuring and control systems of quadrocopters. …”
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Gas-dynamic Analyzer of Nitrogen-hydrogen Mixture for Industrial Application by Halyna Matiko, Yevhen Pistun

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Privacy-preserving federated learning framework with dynamic weight aggregation by Zuobin YING, Yichen FANG, Yiwen ZHANG

“…There are two problems with the privacy-preserving federal learning framework under an unreliable central server.① A fixed weight, typically the size of each participant’s dataset, is used when aggregating distributed learning models on the central server.However, different participants have non-independent and homogeneously distributed data, then setting fixed aggregation weights would prevent the global model from achieving optimal utility.② Existing frameworks are built on the assumption that the central server is honest, and do not consider the problem of data privacy leakage of participants due to the untrustworthiness of the central server.To address the above issues, based on the popular DP-FedAvg algorithm, a privacy-preserving federated learning DP-DFL algorithm for dynamic weight aggregation under a non-trusted central server was proposed which set a dynamic model aggregation weight.The proposed algorithm learned the model aggregation weight in federated learning directly from the data of different participants, and thus it is applicable to non-independent homogeneously distributed data environment.In addition, the privacy of model parameters was protected using noise in the local model privacy protection phase, which satisfied the untrustworthy central server setting and thus reduced the risk of privacy leakage in the upload of model parameters from local participants.Experiments on dataset CIFAR-10 demonstrate that the DP-DFL algorithm not only provides local privacy guarantees, but also achieves higher accuracy rates with an average accuracy improvement of 2.09% compared to the DP-FedAvg algorithm models.…”
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Modeling HTLV-1 and HTLV-2 co-infection dynamics by E. A. Almohaimeed, A. M. Elaiw, A. D. Hobiny

“…Additionally, sensitivity analysis of the basic reproduction numbers for HTLV-1 single infection ($ R_{1} $) and HTLV-2 single infection ($ R_{2} $) is performed to better understand the key parameters influencing co-infection dynamics. The study also explores the impact of CD8$ ^{+} $ T cell proliferation in the co-infection dynamics of HTLV-1 and HTLV-2, highlighting the importance of the CD8$ ^{+} $ T cell response in controlling the progression of HTLV-1. …”
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A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings by Dylan Wald, Olga Doronina, Kathryn Johnson, Ryan King, Michael Sinner, Kevin Griffin, Rohit Chintala, Deepthi Vaidhynathan, Jibonananda Sanyal, Marc Day

“…One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. …”
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Biochemical parameters and adaptation of white rats with active and passive type of behavior under immobilization stress by Fedorenko Yu.V.

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Molecular surface descriptors to predict antibody developability: sensitivity to parameters, structure models, and conformational sampling by Eliott Park, Saeed Izadi

“…However, the predictive power and reproducibility of such methods depend heavily on the selection of molecular descriptors, model parameters, accuracy of predicted structure models, and conformational sampling techniques. …”
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Electrical Equivalent Circuit Parameter Estimation of Commercial Induction Machines Using an Enhanced Grey Wolf Optimization Algorithm by Premkumar Manoharan, Sowmya Ravichandran, Jagarapu S. V. Siva Kumar, Mustafa Abdullah, Tan Ching Sin, Tengku Juhana Tengku Hashim

“…To overcome these limitations, this study introduces an Adaptive Weight Grey Wolf Optimizer (AWGWO) to enhance the accuracy and reliability of induction motor parameter estimation. The AWGWO incorporates an adaptive weight mechanism that dynamically adjusts the exploration and exploitation balance, effectively mitigating issues such as premature convergence to local optima. …”
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Controlling Complex Dynamics in a Protected Area Discrete-Time Model by Paolo Russu

“…We observed that some values of 𝛽 can generate a chaotic regime from a stable dynamic of the OAPA model. Finally, to eliminate the chaotic regime, we design a controller by OGY method, assuming the user fee as a controller parameter.…”
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Dynamic Loading of Bar Systems with a Finite Number of Degrees of Freedom by Sergei P. Ivanov, Oleg G. Ivanov, Anastasia S. Ivanova

“…In case of seismic impacts, it is necessary to check the building’s structural elements for dynamic stability. The issue of determining the critical state of systems with a finite number of degrees of freedom under dynamic loads is solved in this paper. …”
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Modeling of peatland fire risk early warning based on water dynamics by B. Kartiwa, . Maswar, A. Dariah, . Suratman, N.L. Nurida, N. Heryani, P. Rejekiningrum, H. Sosiawan, S.H. Adi, I. Lenin, S. Nurzakiah, Ch. Tafakresnanto

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A study of parameter aggregation algorithms for virtual power plant terminal decentralized resource scheduling characteristics in alpine regions by Yan Wang, Ruizhi Zhang, Ying Wang, Wen Xiang, Lu Wang

“…This approach enhances scheduling flexibility and resolves the grid-side secondary dispatch issue. An improved ant colony algorithm based on continuous optimization was used to solve the aggregation parameters. …”
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Emotional Dynamics in Social Interactions: A Multi-Strategy Synergy Model by Xinyu Wang, Lipu Zhang

“…Global sensitivity analysis identified the natural emotional decay rate as the most influential parameter for emotional dynamics. An empirical case study of commuters’ weekly emotional changes demonstrated the model’s ability to capture real-world emotional fluctuations. …”
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