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  1. 661

    Exploring mediators of the Amaka Amasanyufu Multiple Family Group Intervention (2016–2022) on parenting stress reduction among caregivers of children with disruptive behavior disor... by Rachel Brathwaite, Massy Mutumba, Fred M. Ssewamala, Ozge Sensoy Bahar, Torsten B. Neilands, Phionah Namatovu, Mary M. McKay, Kimberly Hoagwood

    Published 2024-12-01
    “…At the end of the intervention, caregivers displayed lower levels of parenting stress than controls, however the mechanisms by which stress reduction occurred is unknown. …”
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    Article
  2. 662
  3. 663

    Algorithmic Support of Adaptive Automatic Control Systems with Data Compression by V. V. Alekseev, E. M. Antonyuk, I. E. Varshavskiy

    Published 2020-12-01
    “…The exponential growth of measurement information caused by ongoing complication of technical and production facilities necessitates the development of improved or brand new information and measurement systems, including those performing adaptive automatic control functions. Automatic criteria-based selection and reduction of measurement information continuously supplied by multi-parameter sources characterizing the objects under study require algorithms ensuring reconfiguration of automatic control systems during operation. …”
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  4. 664
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  7. 667

    Two‐Step Tandem Catalysis for High‐Efficiency Ammonia Synthesis Via Nitrate Reduction on Anion‐Intercalated CoNi LDH and Cu/Cu2O by Changzheng Lin, Weijia Li, Hao Chen, Jiangtao Feng, Mengyuan Zhu, Jinwen Shi, Mingtao Li, Bo Hou, Zhenyu Wang, Xin Chen, Jia Liu, Wei Yan

    Published 2025-07-01
    “…However, the NitRR pathway, which involves sequential reactions, poses challenges in synchronizing the rate of nitrate‐to‐nitrite conversion with the subsequent reduction of nitrite to ammonia, particularly as the initial reduction step is rate‐limiting. …”
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  8. 668

    Carbon flow tracking and network reconfiguration: a network evolution analysis of embodied carbon emissions from belt and road trade under regional and industry perspectives by Ying Wang, Ruohan Zhang, Shali Wang, Liya Wang, Xinglan Dai, Zishuai Zu

    Published 2025-08-01
    “…The findings offer a factual basis for B&R countries to coordinate cross-regional and cross-sector carbon emission control, clarifying emission responsibilities, identifying reduction pathways, and promoting the high-quality construction of the B&R.…”
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    Article
  9. 669

    Two-Stage Optimal Dispatching Method for Highway Service-Area Microgrid Considering Emergency Power-Supply Vehicles by HU Junjie, QU Jiatong, LIU Xuetao, GUI Jiangyi

    Published 2025-04-01
    “…In this stage, based on model predictive control theory, an intraday rolling optimization scheduling model is established. …”
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  10. 670
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    Immunological AI Optimizer Deployment in a 330 MW Lignite-Fired Unit for NO<sub>x</sub> Abatement by Konrad Świrski, Łukasz Śladewski, Konrad Wojdan, Xianyong Peng

    Published 2025-06-01
    “…Real-time temperature data from the AGAM acoustic system inform the combustion optimizer’s fireball modeling, ensuring combustion uniformity. A urea-based SNCR system serves as a secondary layer, controlled based on local furnace conditions to target thermal zones. …”
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  12. 672

    A Hierarchically Structured Ni-NOF@ZIF-L Heterojunction Using Van Der Waals Interactions for Electrocatalytic Reduction of CO<sub>2</sub> to HCOOH by Liqun Wu, Xiaojun He, Jian Zhou

    Published 2025-07-01
    “…The electrocatalytic CO<sub>2</sub> reduction reaction (CO<sub>2</sub>RR) offers an energy-saving and environmentally friendly approach to producing hydrocarbon fuels. …”
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    Article
  13. 673

    Robust super-twisting algorithm-based single-phase sliding mode frequency controller in power systems integrating wind turbines and energy storage systems by Van Van Huynh, Shahalam Naqvi, Bang Le-Huy Nguyen, Anh-Tuan Tran, Jae Woong Shim, Ton Duc Do

    Published 2025-06-01
    “…Simulation results under step and stochastic load variations show that the proposed method achieves up to 56% and 84.5% reduction in overshoot compared to PD and PI SMC schemes, respectively, along with a 54.5% improvement in settling time over the PI SMC scheme, thereby confirming its enhanced performance and robustness relative to existing control strategies.…”
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    Article
  14. 674

    A data-driven control method for ground locomotion on sloped terrain of a hybrid aerial-ground robot by Xinhang Xu, Yizhuo Yang, Muqing Cao, Thien-Minh Nguyen, Kun Cao, Lihua Xie

    Published 2024-12-01
    “…Experiments show improvements of the proposed neural network in training speed and robustness over a baseline ReLU network, and a 40% reduction in tracking error compared to a baseline PID controller.…”
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  15. 675

    Attitude tracking control for quadrotor UAVs based on extremum seeking by GUO Dali, ZHAO Zhongyuan, LUO Zijuan

    Published 2023-12-01
    “…Firstly, a nonlinear attitude model of a four rotor UAV was established, and considering the uncertainty of model parameters, a robust controller was designed to ensure the dynamic boundedness of tracking errors. …”
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  16. 676

    Modeling of chronic ovary inflammation by N. А. Volkova, M. S. Yuhta, Т. А. Yurchuk, L. V. Stepanuk, E. D. Ivanova, E. V. Pavlovich

    Published 2014-04-01
    “…Efficiency of the modeling pathology was performed by histomorphometric and hematological methods on the 7th, 14th, 21st and 31st days. …”
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  17. 677

    Multi-objective coordinated control and optimization for photovoltaic microgrid scheduling by Da Yu, Kai Hou, Xu Lin, Guoyang Cai, Xin Shan, Weihua Wang

    Published 2025-06-01
    “…This paper proposes a multi-objective coordinated control and optimization system for PV microgrids. …”
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  18. 678

    Spindle Bearing Preload Control Using NI MyRIO by Paweł Turek

    Published 2024-12-01
    “…The article presents an application for controlling the preload of bearings in a model spindle system. …”
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    Predictive Control for Steel Rib Bending Based on Deep Learning by Yijiang Xia, Jinhui Luo, Zhuolin Ou, Xin Han, Junlin Deng, Ning Wu

    Published 2024-12-01
    “…Results show that the T-CNN model outperforms traditional control methods and standard CNNs in prediction accuracy, stability, and efficiency, making it a superior choice for cold bending control.…”
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