A boundary thickening-based direct forcing (BTDF) immersed boundary (IB) method is proposed for fully resolved simulation of incompressible viscous flows laden with finite size particles. By slightly ...thickening the boundary thickness, the local communications between the Lagrangian points on the solid boundary and their neighboring fluid Eulerian grids are improved, based on an implicit direct forcing (IDF) approach and a partition-of-unity condition for the regularized delta function. This strategy yields a simple, yet much better imposition of the non-slip and non-penetration boundary conditions than the conventional direct forcing (DF) technique. In particular, the present BTDF method can achieve a numerical accuracy comparable with other representative improved methods, such as multi-direct forcing (MDF), implicit velocity correction (IVC) and the reproducing kernel particle method (RKPM), while its computing cost remains much lower than them and nearly equivalent to the conventional DF method. The dependence of the optimum thickness value of boundary thickening on the form of the different regularized delta functions is also revealed. By coupling the lattice Boltzmann method (LBM) with BTDF-IB, the robustness of the present BTDF IB method is demonstrated using numerical simulations of creeping flow (Re=0.1), steady vortex separating flow (Re=40) and unsteady vortex shedding flow (Re=200) around a circular cylinder. The accuracy and robustness of the present method for moving particle-laden flows are performed on three benchmark cases, such as free sedimentation of single circular cylinder, DKT sedimentation of two particles and Rayleigh-Taylor instability of 504 particles sedimentation in an enclosed cavity. The computational efficiency between the present BTDF method and the MDF method is also compared at last.
•A novel explicit immersed boundary method based on the BTDF scheme is proposed.•Control parameters and referenced values for the boundary thickness are provided.•Selection principle for the spacing step of Lagrangian points is proposed.•Detailed comparisons of BTDF and four other improved DF schemes are studied.•The robustness and efficiency of BTDF scheme is demonstrated by simulating six cases.
Parkinson disease (PD) is a neurological movement disorder resulting primarily from damage to and degeneration of the nigrostriatal dopaminergic pathway. The pathway consists of neural populations in ...the substantia nigra that project to the striatum of the brain where they release dopamine. Diagnosis of PD is based on the presence of impaired motor features such as asymmetric or unilateral resting tremor, bradykinesia, and rigidity. Nonmotor features including cognitive impairment, sleep disorders, and autonomic dysfunction are also present. No cure for PD has been discovered, and treatment strategies focus on symptomatic management through restoration of dopaminergic activity. However, proposed cell replacement therapies are promising because midbrain dopaminergic neurons have been shown to restore dopaminergic neurotransmission and functionally rescue the dopamine-depleted striatum. In this review, we summarize our current understanding of the molecular pathogenesis of neurodegeneration in PD and discuss the development of new therapeutic strategies that have led to the initiation of exploratory clinical trials. We focus on the applications of stem cells for the treatment of PD and discuss how stem cell research has contributed to an understanding of PD, predicted the efficacy of novel neuroprotective therapeutics, and highlighted what we believe to be the critical areas for future research.
Hollow mesoporous silica spheres have recently attracted increasing attention. However, effective synthesis of uniform hollow mesoporous spheres with controllable well-defined pore structures for ...fundamental research and practical applications has remained a significant challenge. In this work, a straightforward and effective "cationic surfactant assisted selective etching" synthetic strategy was developed for the preparation of high-quality hollow mesoporous silica spheres with either wormhole-like or oriented mesoporous shell. The as-prepared hollow mesoporous silica spheres have large surface area, high pore volume, and controllable structure parameters. Our experiments demonstrated that cationic surfactant plays critical roles in forming the hollow mesoporous structure. A formation mechanism involving the etching of solid SiO(2) accelerated by cationic surfactant followed by the redeposition of dissolved silica species directed by cationic surfactant is proposed. Furthermore, the strategy can be extended as a general strategy to transform silica-coated composite materials into yolk-shell structures with either wormhole-like or oriented mesoporous shell.
This study is to analyze the influence of visibility in a foggy weather environment on the accuracy of machine vision obstacle detection in assisted driving. We present a foggy day imaging model and ...analyze the image characteristics, then we set up the faster region convolutional neural network (Faster R-CNN) as the basic network for target detection in the simulation experiment and use Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) data for network detection and classification training. PreScan software is used to build weather and traffic scenes based on a foggy imaging model, and we study object detection of machine vision in four types of weather condition-clear (no fog), light fog, medium fog, and heavy fog-by simulation experiment. The experimental results show that the detection recall is 91.55%, 85.21%, 72.54~64.79%, and 57.75% respectively in no fog, light fog, medium fog, and heavy fog environments. Then we used real scenes in medium fog and heavy fog environment to verify the simulation experiment. Through this study, we can determine the influence of bad weather on the detection results of machine vision, and hence we can improve the safety of assisted driving through further research.
The efficient and accurate identification of traffic signs is crucial to the safety and reliability of active driving assistance and driverless vehicles. However, the accurate detection of traffic ...signs under extreme cases remains challenging. Aiming at the problems of missing detection and false detection in traffic sign recognition in fog traffic scenes, this paper proposes a recognition algorithm for traffic signs based on pix2pixHD+YOLOv5-T. Firstly, the defogging model is generated by training the pix2pixHD network to meet the advanced visual task. Secondly, in order to better match the defogging algorithm with the target detection algorithm, the algorithm YOLOv5-Transformer is proposed by introducing a transformer module into the backbone of YOLOv5. Finally, the defogging algorithm pix2pixHD is combined with the improved YOLOv5 detection algorithm to complete the recognition of traffic signs in foggy environments. Comparative experiments proved that the traffic sign recognition algorithm proposed in this paper can effectively reduce the impact of a foggy environment on traffic sign recognition. Compared with the YOLOv5-T and YOLOv5 algorithms in moderate fog environments, the overall improvement of this algorithm is achieved. The precision of traffic sign recognition of the algorithm in the fog traffic scene reached 78.5%, the recall rate was 72.2%, and mAP@0.5 was 82.8%.
Direct conversion of methane to methanol is an effective and practical process to improve the efficiency of natural gas utilization. Copper (Cu)-based catalysts have attracted great research ...attention, due to their unique ability to selectively catalyze the partial oxidation of methane to methanol at relatively low temperatures. In recent decades, many different catalysts have been studied to achieve a high conversion of methane to methanol, including the Cu-based enzymes, Cu-zeolites, Cu-MOFs (metal-organic frameworks) and Cu-oxides. In this mini review, we will detail the obtained evidence on the exact state of the active Cu sites on these various catalysts, which have arisen from the most recently developed techniques and the results of DFT calculations. We aim to establish the structure–performance relationship in terms of the properties of these materials and their catalytic functionalities, and also discuss the unresolved questions in the direct conversion of methane to methanol reactions. Finally, we hope to offer some suggestions and strategies for guiding the practical applications regarding the catalyst design and engineering for a high methanol yield in the methane oxidation reaction.
Urban emergencies are hard to avoid. Traffic emergency response after an incident plays an important role in reducing losses and is a key link in urban emergency management. However, the traditional ...traffic management methods have been difficult to face the complicated conditions and requirements in such problems. The introduction of Internet of Things and data mining technology to establish a traffic emergency response system under urban emergencies can significantly improve the level of urban emergency response and realize efficient intensive management. The system mainly includes sub-systems, such as personnel evacuation data collection system, vehicle operation data collection system, rescue material distribution data collection system, personnel settlement place data collection system, traffic bayonet intelligent identification system, etc. It also devises the working programs for command management, personnel evacuation and disaster disposal in case of emergency, and improves the urban emergency support management system. With the support of Internet of Things and the data mining technology, the traffic emergency response system can timely and accurately control the flowing information of personnel and vehicles, quickly and conveniently resettle personnel and vehicles, effectively carry out follow-up rescue work, effectively improve rescue efficiency and improve the level of urban management.
Small-pore zeolites catalyze the methanol-to-olefins (MTO) reaction via a dual-cycle mechanism, encompassing both olefin- and aromatic-based cycles. Zeolite topology is crucial in determining both ...the catalytic pathway and the product selectivity of the MTO reaction. Herein, we investigate the mechanistic influence of MCM-35 zeolite on the MTO process. The structural properties of the as-synthesized MCM-35 catalyst, including its confined cages (6.19 Å), were characterized, confirming them as the catalytic centers. Then, the MTO reactions were systematically performed and investigated over a MCM-35 catalyst. Feeding pure methanol to the reactor yielded minimal MTO activity despite the formation of some aromatic species within the zeolite. The results suggest that the aromatic-based cycle is entirely suppressed in MCM-35, preventing the simultaneous occurrence of the olefin-based cycle. However, cofeeding a small amount of propene in methanol can obviously enhance the methanol conversion under the same studied reaction conditions. Thus, the exclusive operation of the olefin-based cycle in the MTO reaction, independent of the aromatic-based cycle, was demonstrated in MCM-35 zeolite.
•The fate of P fertilizers in Alfisol is controlled by chemical adsorption reactions.•P is primarily immobilized by goethite, kaolinite, and illite in Alfisol.•P adsorbed by illite may serve as an ...indicator of P availability in Alfisol.
Inorganic P is adsorbed by a variety of soil minerals. For acidic subtropical Alfisols with high contents of both (hydr)oxides and clay minerals, there is an underappreciated understanding of the importance of clay minerals to P species and availability varying with soil pH and P concentration. In this study, the rate and equilibrium of P adsorption in a subtropical Alfisol were investigated by combining soil incubation with three types of P fertilizer with multi-surface modelling. Phosphorus species analysis revealed that most of the P was present in the forms of Al-P and Fe-P in the subtropical Alfisol. The multi-surface model calculation showed that goethite, kaolinite, and illite were the most important soil constituents responsible for the immobilization of P. Clay minerals were as important as Al/Fe (hydr)oxides for P adsorption in the subtropical Alfisol. In addition, there was a highly positive linear correlation between P adsorbed by illite and Olsen P, with a slope of approximately to 1. The model analysis also showed that >99% of the P adsorbed by illite was in the form of -SO2PO22-. These results suggest the important role of illite in controlling P availability and that P adsorption by illite may serve as an indicator of P availability in the subtropical Alfisol.
The issues of the degradation of the visual sensor's image quality in foggy weather and the loss of information after defogging have brought great challenges to obstacle detection during autonomous ...driving. Therefore, this paper proposes a method for detecting driving obstacles in foggy weather. The driving obstacle detection in foggy weather was realized by combining the GCANet defogging algorithm with the detection algorithm-based edge and convolution feature fusion training, with a full consideration of the reasonable matching between the defogging algorithm and the detection algorithm on the basis of the characteristics of obvious target edge features after GCANet defogging. Based on the YOLOv5 network, the obstacle detection model is trained using clear day images and corresponding edge feature images to realize the fusion of edge features and convolution features, and to detect driving obstacles in a foggy traffic environment. Compared with the conventional training method, the method improves the mAP by 12% and recall by 9%. In contrast to conventional detection methods, this method can better identify the image edge information after defogging, which significantly enhances detection accuracy while ensuring time efficiency. This is of great practical significance for improving the safe perception of driving obstacles under adverse weather conditions, ensuring the safety of autonomous driving.
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