Deep Learning Overloaded Vehicle Identification for Long Span Bridges Based on Structural Health Monitoring Data

Overloaded vehicles bring great harm to transportation infrastructures. BWIM (bridge weigh-in-motion) method for overloaded vehicle identification is getting more popular because it can be implemented without interruption to the traffic. However, its application is still limited because its effectiveness largely depends on professional knowledge and extra information, and is susceptible to occurrence of multiple vehicles. In this paper, a deep learning based overloaded vehicle identification approach (DOVI) is proposed, with the purpose of overloaded vehicle identification for long-span bridges by the use of structural health monitoring data. The proposed DOVI model uses temporal convolutional architectures to extract the spatial and temporal features of the input sequence data, thus provides an end-to-end overloaded vehicle identification solution which neither needs the influence line nor needs to obtain velocity and wheelbase information in advance and can be applied under the occurrence of multiple vehicles. Model evaluations are conducted on a simply supported beam and a long-span cable-stayed bridge under random traffic flow. Results demonstrate that the proposed deep-learning overloaded vehicle identification approach has better effectiveness and robustness, compared with other machine learning and deep learning approaches

Automatic Extraction Method of 3D Feature Guidelines for Complex Cultural Relic Surfaces Based on Point Cloud

Cultural relics line graphic serves as a crucial form of traditional artifact information documentation, which is a simple and intuitive product with low cost of displaying compared with 3D models. Dimensionality reduction is undoubtedly necessary for line drawings. However, most existing methods for artifact drawing rely on the principles of orthographic projection that always cannot avoid angle occlusion and data overlapping while the surface of cultural relics is complex. Therefore, conformal mapping was introduced as a dimensionality reduction way to compensate for the limitation of orthographic projection. Based on the given criteria for assessing surface complexity, this paper proposed a three-dimensional feature guideline extraction method for complex cultural relic surfaces. A 2D and 3D combined factor that measured the importance of points on describing surface features, vertex weight, was designed. Then the selection threshold for feature guideline extraction was determined based on the differences between vertex weight and shape index distributions. The feasibility and stability were verified through experiments conducted on real cultural relic surface data. Results demonstrated the ability of the method to address the challenges associated with the automatic generation of line drawings for complex surfaces. The extraction method and the obtained results will be useful for line graphic drawing, displaying and propaganda of cultural relics

Anomaly extraction capability analysis based on the mean line difference enhancement ratio method for thermal infrared phenomena before the Jishishan M6.2 earthquake in Gansu Province and Noto M7.6 earthquake in Japan

On December 18, 2023, a M6.2 earthquake occurred in Jishishan County of Gansu Province, and on January 1, 2024, a M7.6 earthquake occurred in Noto, Japan, with a short interval between the two earthquakes. They caused a large number of deaths and huge property losses with causing great concern in the seismic community. By using the mean line difference amplitude enhancement ratio method, it was found that there were significant thermal infrared anomalies before the two earthquakes. About 110 to 90 days before the Jishishan earthquake, the activity of long-wave radiant thermal infrared was 1.5 to 5 times higher than the historical average. Thermal infrared activity levels were 3 to 4 times higher than the historical average for about 140 to 100 days before the Noto earthquake in Japan. These results once again prove that there are thermal infrared anomalies before strong earthquakes, and also indicate that the mean line difference amplitude enhancement ratio method has strong ability to extract thermal infrared anomalies

3D snapshot: Invertible embedding of 3D neural representations in a single image

3D neural rendering enables photo-realistic reconstruction of a specific scene by encoding discontinuous inputs into a neural representation. Despite the remarkable rendering results, the storage of network parameters is not transmission-friendly and not extendable to metaverse applications. In this paper, we propose an invertible neural rendering approach that enables generating an interactive 3D model from a single image (i.e., 3D Snapshot). Our idea is to distill a pre-trained neural rendering model (e.g., NeRF) into a visualizable image form that can then be easily inverted back to a neural network. To this end, we first present a neural image distillation method to optimize three neural planes for representing the original neural rendering model. However, this representation is noisy and visually meaningless. We thus propose a dynamic invertible neural network to embed this noisy representation into a plausible image representation of the scene. We demonstrate promising reconstruction quality quantitatively and qualitatively, by comparing to the original neural rendering model, as well as video-based invertible methods. On the other hand, our method can store dozens of NeRFs with a compact restoration network (5MB), and embedding each 3D scene takes up only 160KB of storage. More importantly, our approach is the first solution that allows embedding a neural rendering model into image representations, which enables applications like creating an interactive 3D model from a printed image in the metaverse

Anisotropic Singlet Fission in Single Crystalline Hexacene

Singlet fission is known to improve solar energy utilization by circumventing the Shockley-Queisser limit. The two essential steps of singlet fission are the formation of a correlated triplet pair and its subsequent quantum decoherence. However, the mechanisms of the triplet pair formation and decoherence still remain elusive. Here we examined both essential steps in single crystalline hexacene and discovered remarkable anisotropy of the overall singlet fission rate along different crystal axes. Since the triplet pair formation emerges on the same timescale along both crystal axes, the quantum decoherence is likely responsible for the directional anisotropy. The distinct quantum decoherence rates are ascribed to the notable difference on their associated energy loss according to the Redfield quantum dissipation theory. Our hybrid experimental/theoretical framework will not only further our understanding of singlet fission, but also shed light on the systematic design of new materials for the third-generation solar cells

Effect of nano-SiO₂ and lime on characteristics and mechanical properties of coastal clay

In this study, the effect of nano-SiO₂ and lime on the characteristics and mechanical properties of coastal clay were investigated. The California bearing ratio (CBR) test and hydraulic conductivity tests were performed to investigate the improved coastal clay strength and hydraulic parameters. The clay specimens were prepared in 5 groups: unmixed, mixed with 3 % lime, 5 % lime, 3 % lime + 1.5 % nano-SiO₂ and 5 % lime + 3 % nano-SiO₂. The results show that the cementation of nano-SiO2 and lime leads to larger CBR values and lower permeability of the coastal clay. Scanning electron microscopy reveals that nano-SiO₂ particles fill in the interspace between lime particles or gel pores, with the diameters of capillary pores and micro-pores reduced

A Joint User Selection and Resources Optimization Scheduling Algorithm for CoMP

Coordinated Multi-point (CoMP) transmission technology is one of the key techniques in LTE-Advanced, Which can share the channel and data information in multiple cells, and optimize the whole system performance. In order to opti-mize the average sector throughput and improve the fairness of resource scheduling, a scheduling algorithm based on the resource is mainly investigated. In this algorithm, users in the network are classified firstly and then we combine the fixed resources division and flexible scheduling. System level simulation platform is set up to validate the algorithm and the results turn out that the average throughput is better compared with the traditional scheme

NMR-Based Metabonomic Study Reveals Intervention Effects of Polydatin on Potassium Oxonate-Induced Hyperuricemia in Rats

Previous studies have disclosed the antihyperuricemic effect of polydatin, a natural precursor of resveratrol; however, the mechanisms of action still remain elusive. The present study was undertaken to evaluate the therapeutic effects and the underlying mechanisms of polydatin on potassium oxonate-induced hyperuricemia in rats through metabonomic technology from a holistic view. Nuclear magnetic resonance (NMR) spectroscopy was applied to capture the metabolic changes in sera and urine collected from rats induced by hyperuricemia and polydatin treatment. With multivariate data analysis, significant metabolic perturbations were observed in hyperuricemic rats compared with the healthy controls. A total of eleven and six metabolites were identified as differential metabolites related to hyperuricemia in serum and urine of rats, respectively. The proposed pathways primarily included branched-chain amino acid (BCAA) metabolism, glycolysis, the tricarboxylic acid cycle, synthesis and degradation of ketone bodies, purine metabolism, and intestinal microflora metabolism. Additionally, some metabolites indicated the risk of renal injury induced by hyperuricemia. Polydatin significantly lowered the levels of serum uric acid, creatinine, and blood urea nitrogen and alleviated the abnormal metabolic status in hyperuricemic rats by partially restoring the balance of the perturbed metabolic pathways. Our findings shed light on the understanding of the pathophysiological process of hyperuricemia and provided a reference for revealing the metabolic mechanism produced by polydatin in the treatment of hyperuricemia

Reliability model and algorithm research on HVDC system and flexible HVDC system

The main difference between flexible high-voltage direct current (HVDC) system and the traditional HVDC system is that there are two control degrees of freedom in the flexible HVDC system that is the amplitude and phase angle of the output voltage. While, there is only one control degrees of freedom in the traditional HVDC system which is the amplitude of the output voltage. Therefore, compared with the traditional HVDC system, there will not be the problem of commutation failure in the flexible HVDC system, and the control systems of the rectifier side and the inverter side being operated independently make the reliability of the system greatly improved. This article analyses and compares the main methods of reliability assessment. Analysing and comparing the reliability parameters of the two systems by using the state enumeration method, and using the economic characterisation to make the comparison more intuitive

Fyn gene silencing reduces oligodendrocytes apoptosis through inhibiting ERK1/2 phosphorylation in epilepsy

AbstractThis study aimed to investigate the effect of Fyn gene silencing on the apoptosis of oligodendrocytes (OLs) in epileptic model in vitro and the involved mechanism. Primary oligodendrocyte pro-genitor cells (OPCs) were separated from rats and differentiated to OLs. Immunofluorescent labeling showed positive expression of A2B5 in OPCs and Olig2 in OLs, suggesting the successful separation of OPCs and OLs. Three Fyn siRNAs (si-Fyn) and Fyn siRNA negative control (NC) were transfected into OLs. Western blot showed that among three si-Fyn groups, si-Fyn3 caused the lowest Fyn expression, so si-Fyn3 was chosen for following experiment. Cells were divided into four groups: Control, Model, NC and si-Fyn. In the Model group, cells were cultured in Mg-free extracellular fluid for 3 h. The morphology of control cells was normal. However, the migration of neurons, the aggregation of cell bodies and the “grid-like” changes of neural networks were observed in the model cells. OLs apoptosis in various groups was assessed by flow cytometry. Expression of Fyn, ERK1/2 and phosphorylated ERK1/2 (p-ERK1/2) in OLs of various groups was evaluated by western blot. Compared with the Control group, the apoptotic rates, the Fyn expression and p-ERK1/2/ERK1/2 ratio in the Model and NC groups increased significantly (p < .05). However, the apoptotic rate, the Fyn expression and p-ERK1/2/ERK1/2 ratio in the si-Fyn group were remarkably smaller than those in the Model group (p < .05). In conclusion, Fyn gene silencing reduced the apoptosis of OLs through inhibiting the phosphorylation of ERK1/2 in epileptic model