Research on Tire Surface Damage Detection Method Based on Image Processing.

The performance of the tire has a very important impact on the safe driving of the car, and in the actual use of the tire, due to complex road conditions or use conditions, it will inevitably cause immeasurable wear, scratches and other damage. In order to effectively detect the damage existing in the key parts of the tire, a tire surface damage detection method based on image processing was proposed. In this method, the image of tire side is captured by camera first.

Binding Mechanism of Inhibitors to BRD4 and BRD9 Decoded by Multiple Independent Molecular Dynamics Simulations and Deep Learning.

Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop.

Jitter solution in parameter identification based on cross-time scale fusion algorithm of lithium-ion batteries.

Accurate state-of-charge (SOC) estimation is the core index of battery management system (BMS). When the battery equivalent circuit model (ECM) identifies the parameters under complex operating conditions, there is more jitter or even divergence, which will affect the estimation accuracy of battery SOC. To solve this problem, this paper proposes a new algorithm, namely the cross time scale fusion (CTSF) algorithm.

Multi-scale attention network (MSAN) for track circuits fault diagnosis.

As one of the three major outdoor components of the railroad signal system, the track circuit plays an important role in ensuring the safety and efficiency of train operation. Therefore, when a fault occurs, the cause of the fault needs to be found quickly and accurately and dealt with in a timely manner to avoid affecting the efficiency of train operation and the occurrence of safety accidents. This article proposes a fault diagnosis method based on multi-scale attention network, which uses Gramian Angular Field (GAF) to transform one-dimensional time series into two-dimensional images, making full use of the advantages of convolutional networks in processing image data.

Experimental Study on Water-Plugging Performance of Grouted Concrete Crack.

In this paper, ordinary Portland cement, ultrafine cement, polyurethane, and epoxy resin were selected as typical grouting materials. Grouting simulation tests were first conducted to prepare the grouted concrete crack sample. The effect of concrete crack parameters (i.

An integrated design concept evaluation model based on interval valued picture fuzzy set and improved GRP method.

The objective of this research is to enhance the precision and efficiency of design concept assessments during the initial stages of new product creation. Design concept evaluation, which occurs at the end of the conceptual design phase, is a critical step in product development. The outcome of this evaluation significantly impacts the product's eventual success, as flawed design concepts are difficult to remedy in later stages.

Enhancing Ionic Conductivity and Electrochemical Stability of LiPS via Zn, F Co-Doping for All-Solid-State Li-S Batteries.

Sulfide solid-state electrolytes have garnered considerable attention owing to their notable ionic conductivity and mechanical properties. However, achieving an electrolyte characterized by both high ionic conductivity and a stable interface between the electrode and electrolyte remains challenging, impeding its widespread application. In this work, we present a novel sulfide solid-state electrolyte, LiPZnSF, prepared through a solid-phase reaction, and explore its usage in all-solid-state lithium sulfur batteries (ASSLSBs).

Road surface crack detection based on improved YOLOv5s.

In response to the issues of low efficiency and high cost in traditional manual methods for road surface crack detection, an improved YOLOv5s (you only look once version 5 small) algorithm was proposed. Based on this improvement, a road surface crack object recognition model was established using YOLOv5s. First, based on the Res2Net (a new multi-scale backbone architecture) network, an improved multi-scale Res2-C3 (a new multi-scale backbone architecture of C3) module was suggested to enhance feature extraction performance.

Global Dynamic Path Planning of AGV Based on Fusion of Improved A* Algorithm and Dynamic Window Method.

Designed to meet the demands of AGV global optimal path planning and dynamic obstacle avoidance, this paper proposes a combination of an improved A* algorithm and dynamic window method fusion algorithm. Firstly, the heuristic function is dynamically weighted to reduce the search scope and improve the planning efficiency; secondly, a path-optimization method is introduced to eliminate redundant nodes and redundant turning points in the path; thirdly, combined with the improved A* algorithm and dynamic window method, the local dynamic obstacle avoidance in the global optimal path is realized. Finally, the effectiveness of the proposed method is verified by simulation experiments.

24Model-based comparative analysis of two catastrophic hazardous chemical pipeline accidents.

This study conducted a comparative analysis of two catastrophic pipeline accidents in China in order to identify some common mistakes and lessons learned to prevent similar accidents. The 24Model was used in this study, which provides a universal pathway for accident analysis from the individual level to the organizational level. There were similarities between the two cases in the aspects of the occurrence, development, emergency and causation at different levels: both were caused by leaks of pipelines and evolved into multiple explosions during emergency response; both leaks were caused by the corrosion of pipelines in the confined space of a damp or salt-spray environment; both were classified as 'responsibility accidents', and unsafe acts, such as the failure to identify hidden hazards of pipelines that were the direct cause of accidents, reflected the shortcomings of individual safety habitual behaviour in terms of knowledge, awareness, habits and psychology; weaknesses in the organizational management mainly concerned hazard identification, pipeline maintenance, emergency disposal, etc.

Automatic berthing of unmanned surface vessels with predetermined performance.

To solve the problem of ship automatic berthing control due to unknown time-varying disturbance and dynamic uncertainty of model parameters, an automatic berthing control law based on predefined performance time function is proposed. First, a predefined performance time function is designed and coupled with tracking error to achieve the predetermined performance of tracking error. Secondly, radial basis function neural network is used to approach the dynamic uncertainty of ship model parameters, and the complex uncertainty of model parameters and unknown time-varying disturbance is represented by linearized parameter form with single virtual parameter, which makes the calculation simple and easy to implement in engineering.

Effective social spider optimization algorithms for distributed assembly permutation flowshop scheduling problem in automobile manufacturing supply chain.

This paper presents a novel distributed assembly permutation flowshop scheduling problem (DAPFSP) based on practical problems in automobile production. Different from the existing research on DAPFSP, this study considers that each component of the final product is composed of more than one part. Components are processed in a set of identical components manufacturing factories and are assembled into products in the assembly factory.

Effect of Industrial Solid Waste as Fillers on the Rheology and Surface Free Energy of Asphalt Mastic.

The continuous growth of industrial solid waste production has generated many environmental problems. We evaluated the potential of industrial solid waste as a substitute filler in asphalt mastic, with the aim of increasing the use of sustainable road construction materials. In this study, X-ray fluorescence spectroscopy (XRF) and scanning electron microscopy (SEM) were used to characterize the oxide composition and micromorphology of limestone (LS), red mud (RM), steel slag (SS), and ground granulated blast-furnace slag (GGBFS).

Discrete element simulation of vibration compaction of slag subgrade.

In this study, to improve the compaction quality and parameters of slag, discrete element models of irregular rock particles (10-60 mm) and circular soil particles (5 mm) were established based on on-site slag screening results. The motion of the vibratory roller was captured by coupling the roadbed model with the roller model in a simulation in which the roller vibrated and compacted the slag subgrade. The results indicated that (1) the best compaction was achieved when the small particle content was 40%, the medium particle content was 20%, and the large particle content was 40%.

Lightweight Vehicle Detection Based on Improved YOLOv5s.

A vehicle detection algorithm is an indispensable component of intelligent traffic management and control systems, influencing the efficiency and functionality of the system. In this paper, we propose a lightweight improvement method for the YOLOv5 algorithm based on integrated perceptual attention, with few parameters and high detection accuracy. First, we propose a lightweight module IPA with a Transformer encoder based on integrated perceptual attention, which leads to a reduction in the number of parameters while capturing global dependencies for richer contextual information.

Research on highway rain monitoring based on rain monitoring coefficient.

The real-time and accurate monitoring of severe weather is the key to reducing traffic accidents on highways. Currently, rainy day monitoring based on video images focuses on removing the impact of rain. This article aims to build a monitoring model for rainy days and rainfall intensity to achieve precise monitoring of rainy days on highways.

Research on variable universe fuzzy PID control for semi-active suspension with CDC dampers based on dynamic adjustment functions.

The vehicle suspension system is a complex system with multiple variables, nonlinearity and time-varying characteristics, and the traditional variable universe fuzzy PID control algorithm has the problems of over-reliance on expert experience and non-adaptive adjustment of the contracting-expanding factor parameters, which make it difficult to achieve a better control effect. In this paper, the system error e(t) and its change rate ec(t) are introduced into the contracting-expanding factor as dynamic parameters to realize the adaptive adjustment of the contracting-expanding factor parameters, and propose a variable universe fuzzy PID control based on dynamic adjustment functions (VUFP-DAF), which uses the real-time contracting-expanding factor to realize the adaptive adjustment of the fuzzy universe, so as to improve the ride comfort of vehicles. The research results show that the proposed VUFP-DAF has strong adaptability and can effectively improve the ride comfort and handling stability of vehicles under different speeds and road excitations, providing a certain technical basis for the development of the semi-active suspension system.

Roles of Accelerated Molecular Dynamics Simulations in Predictions of Binding Kinetic Parameters.

Rational predictions on binding kinetics parameters of drugs to targets play significant roles in future drug designs. Full conformational samplings of targets are requisite for accurate predictions of binding kinetic parameters. In this review, we mainly focus on the applications of enhanced sampling technologies in calculations of binding kinetics parameters and residence time of drugs.

Multi-label classification of retinal disease via a novel vision transformer model.

Introduction: The precise identification of retinal disorders is of utmost importance in the prevention of both temporary and permanent visual impairment. Prior research has yielded encouraging results in the classification of retinal images pertaining to a specific retinal condition. In clinical practice, it is not uncommon for a single patient to present with multiple retinal disorders concurrently.

Research on the Deformation Law of Foundation Excavation and Support Based on Fluid-Solid Coupling Theory.

To investigate the impact of underground water seepage and soil stress fields on the deformation of excavation and support structures, this study initially identified the key influencing factors on excavation deformation. Subsequently, through a finite element simulation analysis using Plaxis, this study explored the effects of critical factors, such as the excavation support form, groundwater lowering depth, permeability coefficient, excavation layer, and sequence on excavation deformation. Furthermore, a comprehensive consideration of various adverse factors was integrated to establish excavation support early warning thresholds, and optimal dewatering strategies.

Temperature Field Characterization of Iron Tailings Based on Microwave Maintenance Technology.

Microwave maintenance technology, as a new development trend, can realize the environmentally noninvasive and rapid repair of asphalt pavement and gradually replace traditional maintenance methods. Iron tailings were used as a self-healing material in this study to investigate the temperature response matching of microwave maintenance technology. Firstly, the physical properties and the mechanism of iron tailings were elaborated through macroscopic physical index testing and microscopic X-ray diffraction (XRD) analysis.

Identification of marine microplastics based on laser-induced fluorescence and principal component analysis.

Although the laser-induced fluorescence method shows great potential for microplastic particle detection, overlapping fluorescence signals make accurate type and proportion identification difficult. This paper presents the identification of marine microplastics based on laser-induced fluorescence and principal component analysis. This method works by measuring the fluorescence spectra of water-containing microplastic samples irradiated with a 405-nm laser, which are then analyzed using the principal component analysis (PCA) method.

Injectable, thermo-sensitive and self-adhesive supramolecular hydrogels built from binary herbal small molecules towards reusable antibacterial coatings.

Herbal hydrogels as a new class of sustainable functional materials have attracted extensive attention. However, the development of herbal hydrogels is significantly hindered due to their poor hydrogel performances and the lack of universal preparation methods. In this study, four herbal hydrogels composed of phytochemical polyphenols and stevioside compounds are prepared through a facile heating-cooling process, where multiple hydrogen bonding interactions between two monomers provide the main driving force for gelation.

Vehicle re-identification based on dimensional decoupling strategy and non-local relations.

Vehicle re-identification (Re-ID) is a challenging task that aims to recognize the same vehicle across different non-overlapping cameras. Existing attention mechanism-based methods for vehicle Re-ID often suffer from significant intra-class variation and inter-class variation due to various factors such as illumination, occlusion, viewpoint, etc. In this paper, we propose a novel network architecture for vehicle Re-ID, named Dimensional Decoupling Strategy and Non-local Relationship Network (DMNR-Net), which uses three modules to extract complementary features: global feature extraction module, non-local relationship capture module(NRCM), and dimensional decoupling module (DDS).

Insights into the selectivity of a brain-penetrant CDK4/6 vs CDK1/2 inhibitor for glioblastoma used in multiple replica molecular dynamics simulations.

Cyclin dependent kinases (CDKs) play an important role in cell cycle regulation and their dysfunction is associated with many cancers. That is why CDKs have been attractive targets for the treatment of cancer. Glioblastoma is a cancer caused by the aberrant expression of CDK4/6, so exploring the mechanism of the selection of CDK4/6 toward inhibitors relative to the other family members CDK1/2 is essential.