Distributed Drive Electric Vehicle Handling Stability Coordination Control Framework Based on Adaptive Model Predictive Control.

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 β-β˙ phase plane stability boundary and designs variable weight factors based on this stability boundary.

Morphology and Alignment Transition of Hexabenzocoronene (HBC) Mesogen Films by Bar Coating: Effect of Coating Speed.

Films of the discotic liquid crystalline hexabenzocoronene (HBC) derivative, , were prepared on the quartz substrate by the bar-coating method. Depending on the coating speed, regularly spaced stripes or continuous films were observed. In the former case, columns of the HBC derivatives align more along the stripes, which are perpendicular to the coating direction, whereas in the latter case, columns of the HBC derivatives in the film align more along the coating direction.

Ground air pollutants explanation based on multiple visibility graph of complex network by temporal community division.

In air pollution studies, the correlation analysis of environmental variables has usually been challenged by parametric diversity. Such variable variations are not only from the extrinsic meteorological conditions and industrial activities but also from the interactive influences between the multiple parameters. A promising solution has been motivated by the recent development of visibility graph (VG) on multi-variable data analysis, especially for the characterization of pollutants' correlation in the temporal domain, the multiple visibility graph (MVG) for nonlinear multivariate time series analysis has been verified effectively in different realistic scenarios.

Aspiration-driven co-evolution of cooperation with individual behavioral diversity.

In evolutionary game, aspiration-driven updates and imitation updates are the two dominant game models, and individual behavior patterns are mainly categorized into two types: node player and link player. In more recent studies, the mixture strategy of different types of players has been proven to improve cooperation substantially. Motivated by such a co-evolution mechanism, we combine aspiration dynamics with individual behavioral diversity, where self-assessed aspirations are used to update imitation strategies.

Federated Learning via Conditional Mutual Learning for Alzheimer's Disease Classification on T1w MRI.

Data-driven deep learning has been considered a promising method for building powerful models for medical data, which often requires a large amount of diverse data to be sufficiently effective. However, the expensive cost of collecting and the privacy constraints lead to the fact that existing medical datasets are small-scale and distributed. Federated learning via model distillation is a data-private collaborative learning where the model can leverage all available data without direct sharing.

One-Pot CuI/DBU-Catalyzed Carboxylative Cyclization toward Oxazolidinones Using Recyclable Molecular Sieves as Efficient Promoters for Fixation of CO in Water Medium.

An efficient one-pot synthesis of oxazolidinones was developed through CuI/DBU/MS joint system-catalyzed carboxylative cyclization of arylacetylene, arylaldehyde, and arylamine in water medium under a 1 atm carbon dioxide (CO) atmosphere. The 4 Å molecular sieves (MSs) were added to improve CO capture and facilitate carboxylation to give the products in high yields. The CuI/DBU/MS system is robust and highly effective for the reactions with different substrates, and some target products were obtained in an excellent yield of ∼96%, with no side products in the final step.

Behavior Score-Embedded Brain Encoder Network for Improved Classification of Alzheimer Disease Using Resting State fMRI.

The ability to accurately detect onset of dementia is important in the treatment of the disease. Clinically, the diagnosis of Alzheimer Disease (AD) and Mild Cognitive Impairment (MCI) patients are based on an integrated assessment of psychological tests and brain imaging such as positron emission tomography (PET) and anatomical magnetic resonance imaging (MRI). In this work using two different datasets, we propose a behavior score-embedded encoder network (BSEN) that integrates regularly adminstrated psychological tests information into the encoding procedure of representing subject's resting-state fMRI data for automatic classification tasks.

Automation of fizzy extraction enabled by inexpensive open-source modules.

The implementation of most instrumental analysis methods requires a considerable amount of human effort at every step, including sample preparation, detection, and data processing. Automated analytical workflows decrease the amount of required work. However, commercial automated platforms are mainly available for well-established sample processing methods.

On-line coupling of fizzy extraction with gas chromatography.

Fizzy extraction (FE) is carried out by first dissolving a carrier gas (typically, carbon dioxide) in a liquid sample at a moderate pressure (typically, 150 kPa) and then rapidly depressurizing the sample. The depressurization leads to instant release of numerous microbubbles in the liquid matrix. The abruptly released gas extracts the volatile solutes and elutes them toward a detector in a short period of time.

Fizzy Extraction of Volatile Organic Compounds Combined with Atmospheric Pressure Chemical Ionization Quadrupole Mass Spectrometry.

Chemical analysis of volatile and semivolatile compounds dissolved in liquid samples can be challenging. The dissolved components need to be brought to the gas phase, and efficiently transferred to a detection system. Fizzy extraction takes advantage of the effervescence phenomenon.