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Distributed drive electric vehicles improve steering response and enhance overall vehicle stability by independently controlling each motor. This paper introduces a control framework based on Adaptive Model Predictive Control (AMPC) for coordinating handling stability, consisting of three layers: the dynamic supervision layer, online optimization layer, and low-level control layer. The dynamic supervision layer considers the yaw rate and maneuverability limits when establishing the ß-ßË phase plane stability boundary and designs variable weight factors based on this stability boundary. The online optimization layer constructs the target weight-adaptive AMPC strategy, which can adjust the control weights for maneuverability and lateral stability in real time based on the variable weight factors provided by the dynamic supervision layer. The low-level control layer precisely allocates the driver's requested driving force and additional yaw moment by using torque distribution error and tire utilization as the cost function. Finally, experiments are conducted on a Simulink-CarSim co-simulation platform to assess the performance of AMPC. Simulation results show that, compared to the traditional MPC strategy, this control strategy not only enhances maneuverability under normal conditions but also improves lateral stability control under extreme conditions.
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Providing safe, smooth, and efficient trajectories for autonomous vehicles has long been a question of great interest in the field of autopiloting. In dynamic and ever-changing urban environments, safe and efficient trajectory planning is fundamental to achieving autonomous driving. Nevertheless, the complexity of environments with multiple constraints poses challenges for trajectory planning. It is possible that behavior planners may not successfully obtain collision-free trajectories in complex urban environments. Herein, this paper introduces spatio-temporal joint optimization-based trajectory planning (SJOTP) with multi-constraints for complex urban environments. The behavior planner generates initial trajectory clusters based on the current state of the vehicle, and a topology-guided hybrid A* algorithm applied to an inflated map is utilized to address the risk of collisions between the initial trajectories and static obstacles. Taking into consideration obstacles, road surface adhesion coefficients, and vehicle dynamics constraints, multi-constraint multi-objective coordinated trajectory planning is conducted, using both differential-flatness vehicle models and point-mass vehicle models. Taking into consideration longitudinal and lateral coupling in trajectory optimization, a spatio-temporal joint optimization solver is used to obtain the optimal trajectory. The simulation verification was conducted on a multi-agent simulation platform. The results demonstrate that this methodology can obtain optimal trajectories safely and efficiently in complex urban environments.
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In this study, a sustainable and environmentally friendly method was developed for the enrichment and purification of phycocyanin from Spirulina platensis. This was achieved by utilizing a temperature-sensitive polymer, Pluronic F68, in an aqueous two-phase solvent system. The phase behavior of the temperature-sensitive polymer-based biphasic system was evaluated. The extraction conditions were optimized by both single-factor experiments and response surface methodology. Under the optimal conditions, the upper polymer-rich phase was recycled for sustainable phycocyanin extraction, resulting in a grade of 3.23 during the third extraction cycle. Pluronic F68 could be efficiently recovered and reused during the extraction process. The interaction mechanism between Pluronic F68 and phycocyanin was systematically studied using FT-IR and fluorescence analysis. This was further complemented by static and dynamic calculation of molecular motion through molecular docking and molecular dynamics simulation, indicating that hydrophobic segment of Pluronic F68 played a key role in the binding process with phycocyanin.
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Tecnología Química Verde , Ficocianina , Poloxámero , Spirulina , Temperatura , Ficocianina/química , Ficocianina/aislamiento & purificación , Spirulina/química , Poloxámero/química , Tecnología Química Verde/métodos , Simulación del Acoplamiento Molecular , Espectroscopía Infrarroja por Transformada de Fourier , Agua/química , Polímeros/química , Simulación de Dinámica MolecularRESUMEN
Inverted NiOx-based perovskite solar cells (PSCs) exhibit considerable potential because of their low-temperature processing and outstanding excellent stability, while is challenged by the carriers transfer at buried interface owing to the inherent low carrier mobility and abundant surface defects that directly deteriorates the overall device fill factor. Present work demonstrates a chemical linker with the capability of simultaneously grasping NiOx and perovskite crystals by forming a Ni-S-Pb bridge at buried interface to significantly boost the carriers transfer, based on a rationally selected molecule of 1,3-dimethyl-benzoimidazol-2-thione (NCS). The constructed buried interface not only reduces the pinholes and needle-like residual PbI2 at the buried interface, but also deepens the work function and valence band maximum positions of NiOx, resulting in a smaller VBM offset between NiOx and perovskite film. Consequently, the modulated PSCs achieved a high fill factor up to 86.24 %, which is as far as we know the highest value in records of NiOx-based inverted PSCs. The NCS custom-tailored PSCs and minimodules (active area of 18â cm2) exhibited a champion efficiency of 25.05 % and 21.16 %, respectively. The unencapsulated devices remains over 90 % of their initial efficiency at maximum power point under continuous illumination for 1700â hours.
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BACKGROUND: This study investigates the role of IGFBP3-mediated m6A modification in regulating the miR-23a-3p/SMAD5 axis and its impact on fracture healing, aiming to provide insights into potential therapeutic targets. METHODS: Utilizing fracture-related datasets, we identified m6A modification-related mRNA and predicted miR-23a-3p as a regulator of SMAD5. We established a mouse fracture healing model and conducted experiments, including Micro-CT, RT-qPCR, Alizarin Red staining, and Alkaline phosphatase (ALP) staining, to assess gene expression and osteogenic differentiation. RESULTS: IGFBP3 emerged as a crucial player in fracture healing, stabilizing miR-23a-3p through m6A modification, leading to SMAD5 downregulation. This, in turn, inhibited osteogenic differentiation and delayed fracture healing. Inhibition of IGFBP3 partially reversed through SMAD5 inhibition, restoring osteogenic differentiation and fracture healing in vivo. CONCLUSION: The IGFBP3/miR-23a-3p/SMAD5 axis plays a pivotal role in fracture healing, highlighting the relevance of m6A modification. IGFBP3's role in stabilizing miR-23a-3p expression through m6A modification offers a potential therapeutic target for enhancing fracture healing outcomes.