Research and Development of a Wireless Self-Powered Sensing Device Based on Bridge Vibration Energy Collection

Traditional bridge monitoring has found it difficult to meet the current diversified needs, and frequent replacement of sensor batteries is neither economical nor environmentally friendly. This paper presents a wireless acceleration sensor with low power consumption and high sensitivity through integrated circuit design, data acquisition and wireless communication design, package design, etc. The accuracy of the sensor in data collection was verified through calibration and performance comparison tests. The ability of triangular piezoelectric cantilever beam (PCB) was tested through design and physical manufacture. Finally, the self-powered performance of the sensor was tested by connecting the sensor and the triangular PCB through a circuit, which verifies the feasibility of using the PCB to collect bridge vibration energy and convert it into electrical energy to supply power for sensor, and also explore the green energy collection and application

Establishment and Analysis of the Relationship Model between Macro-Texture and Skid Resistance Performance of Asphalt Pavement

Pavement surface texture evaluation is mainly analyzed based on elevation data in previous research, and attention also need to be paid to wavelength information. Furthermore, a well-established relationship model between surface texture and skid resistance for real road sections still needs further investigation to help provide useful information on appropriate maintenance time considering skid resistance attenuation. In this research, the macro-texture of asphalt pavement was evaluated from different aspects, including elevation, wavelength information, and geometry, and the relationship models between the macro-texture and skid resistance (at both low and high speeds) were established and compared using the multiple linear regression (MLR) and back propagation (BP) neural network to recommend a suitable one. In order to achieve this, this study monitored anti-skidding performance and the macro-texture of six road sections for 18 months. Firstly, the Dynamic Friction Coefficient (DFC) test and core drilling were conducted on site at three different service times. Additionally, a laboratory accelerated loading test was carried out on specimens prepared by similar material composition to one of the road sections, and the British Pendulum Number (BPN) was tested after different passes of loading. Secondly, 3D laser scanning was carried out on core samples from road sections and laboratory specimens after different passes of loading. The correlation degree between macro-texture indexes and anti-skidding performance was analyzed with the grey correlation entropy analysis method. Finally, the relationship models between the anti-skidding performance at high and low speeds and macro-texture were established based on the MLR and BP neural network. The results indicate that the macro-texture indexes calculated based on elevation data to characterize vertical irregularities have a good correlation with the skid resistance despite the different service times and pavement types. Compared with the BP neural network model, the MLR model has low correlation and noticeable error. The relationship model between F60 (DFC at the speed of 60 km/h) and macro-texture could be well established by the BP neural network. In addition, the relationship between F20, BPN, and pavement surface macro-texture is poor, making it impossible to establish a model with good correlation. Generally, it is recommended to use the BP neural network to establish the relationship model between macro-texture and skid resistance

Platelet-derived extracellular vesicles play an important role in platelet transfusion therapy

Extracellular vesicles (EVs) contain the characteristics of their cell of origin and mediate cell-to-cell communication. Platelet-derived extracellular vesicles (PEVs) not only have procoagulant activity but also contain platelet-derived inflammatory factors (CD40L and mtDNA) that mediate inflammatory responses. Studies have shown that platelets are activated during storage to produce large amounts of PEVs, which may have implications for platelet transfusion therapy. Compared to platelets, PEVs have a longer storage time and greater procoagulant activity, making them an ideal alternative to platelets. This review describes the reasons and mechanisms by which PEVs may have a role in blood transfusion therapy

The Application of a Pavement Distress Detection Method Based on FS-Net

In order to solve the problem of difficulties in pavement distress detection in the field of pavement maintenance, a pavement distress detection algorithm based on a new deep learning method is proposed. Firstly, an image data set of pavement distress is constructed, including large-scale image acquisition, expansion and distress labeling; secondly, the FReLU structure is used to replace the leaky ReLU activation function to improve the ability of two-dimensional spatial feature capture; finally, in order to improve the detection ability of this model for long strip pavement distress, the strip pooling method is used to replace the maximum pooling method commonly used in the existing network, and a new method is formed which integrates the FReLU structure and the strip pooling method, named FS-Net in this paper. The results show that the average accuracy of the proposed method is 4.96% and 3.67% higher than that of the faster R-CNN and YOLOv3 networks, respectively. The detection speed of 4 K images can reach about 12 FPS. The accuracy and computational efficiency can meet the actual needs in the field of road detection. A set of lightweight detection equipment for highway pavement was formed in this paper by purchasing hardware, developing software, designing brackets and packaging shells, and the FS-Net was burned into the equipment. The recognition rate of pavement distress is more than 90%, and the measurement error of the crack width is within ±0.5 mm through application testing. The lightweight detection equipment for highway pavement with burning of the pavement distress detection algorithm based on FS-Net can detect pavement conditions quickly and identify the distress and calculate the distress parameters, which provide a large amount of data support for the pavement maintenance department to make maintenance decisions

Cudraflavone B induces human glioblastoma cells apoptosis via ER stress-induced autophagy

Abstract Background Glioblastoma (GBM) is the most common malignant intracranial tumor with a low survival rate. However, only few drugs responsible for GBM therpies, hence new drug development for it is highly required. The natural product Cudraflavone B (CUB) has been reported to potentially kill a variety of tumor cells. Currently, its anit-cancer effect on GBM still remains unknown. Herein, we investigated whether CUB could affect the proliferation and apoptosis of GBM cells to show anti-GBM potential. Results CUB selectively inhibited cell viability and induced cell apoptosis by activating the endoplasmic reticulum stress (ER stress) related pathway, as well as harnessing the autophagy-related PI3K/mTOR/LC3B signaling pathway. Typical morphological changes of autophagy were also observed in CUB treated cells by microscope and scanning electron microscope (SEM) examination. 4-Phenylbutyric acid (4-PBA), an ER stress inhibitor, restored the CUB-caused alteration in signaling pathway and morphological change. Conclusions Our finding suggests that CUB impaired cell growth and induced cell apoptosis of glioblastoma through ER stress and autophagy-related signaling pathways, and it might be an attractive drug for treatment of GBM