Search

For the hazard of single column pier girder bridge lateral overturning, this paper based on the bridge dynamics modeling and simulation, studied the physical characteristics of bridge lateral vibration under differently conditions of bridge length, vehicle off-center distance and multi variable load driving respectively, then considering random disturbance load driving the loading bridge’s pulse and step acting simulations were given out with differently cases. Furthermore, the single column pier bridge lateral overturning process was equivalent the bridge box girder rigid body rotating process under the lateral vibration, then obtained the synthetical effects of the lateral vibration and its harmful period characteristics with differently bridge length variable load and vehicle speed, respectively. Lastly, the qualitative analysis was given for bridge lateral overturning conditions under variable load driving.

Background Tamoxifen (TAMR) resistance remains a massive obstacle for breast cancer (BC) management. The precise parts of long non-coding RNA ataxin 8 opposite strand (ATXN8OS) in BC TAMR resistance have not been defined. Methods The levels of ATXN8OS, vasodilator-stimulated phosphoprotein (VASP), and miR-16-5p were assessed by quantitative real-time polymerase chain reaction or western blot. Colony formation and cell viability were analyzed by MTT and colony formation assays, respectively. Targeted interactions among miR-16-5p, ATXN8OS, and VASP were confirmed by dual-luciferase reporter assay. Animal studies were performed to observe the role of ATXN8OS in TAMR sensitivity in vivo. Results ATXN8OS expression was increased in BC tissues and cells. ATXN8OS depletion promoted BC cell sensitivity to TAMR. ATXN8OS sequestered miR-16-5p by directly binding to miR-16-5p. The promotional effect of ATXN8OS knockdown on BC cell TAMR sensitivity was mediated by miR-16-5p. VASP was a direct target of miR-16-5p, and miR-16-5p overexpression enhanced TAMR sensitivity by VASP. Moreover, ATXN8OS regulated VASP expression by acting as a miR-16-5p sponge. In addition, ATXN8OS knockdown augmented BC TAMR sensitivity in vivo. Conclusion ATXN8OS knockdown enhanced BC TAMR sensitivity partially through the miR-16-5p/VASP axis, highlighting a potential therapeutic target for improving the clinical benefits of TAMR treatment in BC patients.

Simultaneous localization and mapping (SLAM) technology has always been the research focus of robot navigation in unknown environment. Aiming at the problem of cumulative errors of robot pose in the localization process of SLAM algorithm based on particle filter, a loop detection algorithm based on graph-SLAM was proposed. The algorithm uses constraints to adjust the robot attitude at different moments. In this paper, the constraint refers to the scanning matching of lidar. In the process of drawing, when the robot returns to the known area, if the current laser scanning is successfully matched with the previous laser scanning, the robot's posture can be adjusted to eliminate the accumulated errors caused by the odometer. In the process of laser scanning matching, the method of grouping step threshold value judgment is proposed to match the laser point cloud, which can effectively reduce the computation. Experimental results show that the proposed algorithm can effectively eliminate the cumulative errors of positioning and achieve a better mapping effect.

Energy is an important material and dynamic basis to promote the implementation of rural revitalization strategy. With the rapid development of informatization and digitalization, energy internet platform has become a powerful driving force for the construction of a new rural energy system. First of all, this paper analyzes the functional requirements of the rural energy internet platform from four aspects: planning and decision-making, agricultural production, clean heating and market prosperity. Secondly, according to the functional requirements of the platform, a functional framework of rural energy internet platform is established. Finally, four typical application scenarios of planning and decision-making, intelligent agriculture, intelligent heating and platform economy are established. It is of a certain significance for serving rural revitalization through energy methods.

This paper presents a new computer identification method for the diagnosis of the fissured tongue, which can not only detect the existence of fissures, but also quantify the severity from different aspects such as number of fissures, width, length and depth. First, we collecting tongue images from the hospital and given them to three Chinese clinical experts (chief physicians) for identification. Then we use Three Classification methods to analyze them. Finally, an experiment is used to analyse which kind of feature has good performance. The results show that our system have high classification accuracy.

In traditional Chinese medicine (TCM), pulse diagnosis is an important diagnostic method that has a long history and has been widely applied. Wrist pulse signals can be used to analyze a person’s health status, reflecting the pathologic changes of the person’s body condition. With regard to TCM pulse diagnosis, the However, the traditional diagnostic approach has been mainly based on the feel of the doctor, which is non-quantitative and subjective. This paper aims to present a new classification method is proposed for analyzing wrist pulse signals, to provide an automatic and quantitative approach for the diagnosis of TCM based on the pulse. Methods: First, the time domain analysis and hemodynamics method were used to extract and analyze pulse parameters. Then the filtering method was used to select all features. Furthermore, GBDT was used to classify and identify the pulse, and establish a model. Results: The wave peaks, wave valleys and time periods, pulse wave velocity and reflection factors are extracted by time domain analysis and hemodynamic analysis. Then, four important features, including h3/h1, h4/h1, w/t and R f , were selected using the filter feature selection method. Then, the GBDT classification method was used to classify the pulse image of TCM. The middle GBDT classification method exhibited the best effect. The recognition accuracy of the sliding vein, chord vein and chord pulse was 90.33%, 83.52%, 97.74% and 78.60%, respectively, and the overall recognition accuracy was 90.51%. Conclusion: The parameters of the pulse map were optimized and the classification and recognition model of the pulse image was established to realize the automatic recognition of characteristics of pulse diagnosis in TCM. Based on the GBDT classification recognition method, a more accurate classification and recognition model of TCM was established.

With the widespread of micro-turbines (MT) in the distribution network, the interaction between electricity and natural gas system is intensified. Compared with scheduling separately, the joint scheduling of the electricity and natural gas system is more economical and reliable. In this paper, we present an optimal day-ahead scheduling model of the electricity and natural gas system based on alternating direction method of multipliers (ADMM) to handle the opacity of the information between the electricity network and natural gas network. Besides, with consideration of the uncertainties of distributed generation (DG), the variations of the consumption in electricity network and the natural gas network, the worst case of the system is obtained by column-and-constraint generation (C&CG) algorithm and the natural gas flow model is processed by adopting incremental piecewise linear method (IPLM) which alleviates the difficulty of problem-solving. Finally, the effectiveness of the proposed model is validated by the case study.

This paper presents a new automatically quantitative facial features classification system for TCM spirit diagnosis based on facial features. Facial diagnosis is an important diagnostic method in TCM (Traditional Chinese Medicine) and has been used for a long time. However, this traditional diagnostic method is mainly based on observation by TCM doctors and their personal experience. To develop quantification methods for TCM is very important. First, we capture facial features from video images through some algorithms, and then we use some classification models to analyze them. Finally, IG (Information Gain) is used to analyse which kind of features has good performance. Experiment results show that our system has high classification accuracy.

In Traditional Chinese Medicine TCM, lip diagnosis is an important diagnostic method to judge whether a person is healthy or not. Lip images can reflect the physical conditions of organs in the body. Lip diagnosis has a long history in China and the lips are analyzed by experienced doctors with their nude eyes. This method is not objective and efficient especially in the condition of handling many images. Developing an automatic way to split lips from an image is an important and necessary step. What's more, lip segmentation can provide improvement in the areas of speech recognition and speaker authentication. To segment lips and facial complexions, many methods are proposed which are based on color spaces such as RGB, HSV, Lab, etc. Other methods are based on different models such as snake, geometry model, etc. This paper proposes a lip segmentation method based on facial complexion template. A facial complexion template can be constructed when the face is detected. We construct the facial complexion template using Hue channel and Saturation channel of color information. By removing the skin similar to facial complexion template values an initial lip image can be got. Finally, by smoothing the lip contour an optimized lip segmentation result can be obtained.

To explore characteristic of pulse signal to distinguish patients with coronary heart diseases (CHD) from patients without CHD and healthy adults, and accordingly evaluate the potential role of pulse signal to diagnosis CHD. Totally 407 patients enrolled from 4 collaborating medical centers were assigned to a CHD group (205 patients) and a non-CHD group (202 patients). The healthy control group (62 adults) enrolled from Shanghai University of Traditional Chinese Medicine. Pulse signals were collected using the synchronous multiplex pulse signal acquisition system. The pulse signals were analyzed and extracted using Hilbert-Huang transformation (HHT) and time-domain, respectively. The time-domain parameters of pulse signal were processed by the analysis of variance (SNK test). Special patterns in the CHD group pulse signal were found in this study: (1) time-domain parameters of pulse signal, h1, h3, h4, h3/h1, ts, t4/t were increased and w was wider; (2) 44% of C2 waves in HHT were chaotic and disordered and 72% of C waves were exhibited irregularly with average amplitude over 10 g-forces, which were all significantly different from controls. Characteristic wave and time-domain parameters of pulse signal were extracted using HHT and time-domain which could be served as a non-invasive approach for assessing patients with CHD.