Multistep-Ahead Prediction of Urban Traffic Flow Using GaTS Model

The mathematical models for traffic flow have been widely investigated for a lot of application, like planning transportation and easing traffic pressure by using statistics and machine learning methods. However, there remains a lot of challenging problems for various reasons. In this research, we mainly focused on three issues: (a) the data of traffic flow are nonnegative, and hereby, finding a proper probability distribution is essential; (b) the complex stochastic property of the traffic flow leads to the nonstationary variance, i.e., heteroscedasticity; and (c) the multistep-ahead prediction of the traffic flow is often of poor performance. To this end, we developed a Gamma distribution-based time series (GaTS) model. First, we transformed the original traffic flow observations into nonnegative real-valued data by using the Box-Cox transformation. Then, by specifying the generalized linear model with the Gamma distribution, the mean and variance of the distribution are regressed by the past data and homochronous terms, respectively. A Bayesian information criterion is used to select the proper Box-Cox transformation coefficients and the optimal model structures. Finally, the proposed model is applied to the urban traffic flow data achieved from Dalian city in China. The results show that the proposed GaTS has an excellent prediction performance and can represent the nonstationary stochastic property well

DSM Generation from Multi-View High-Resolution Satellite Images Based on the Photometric Mesh Refinement Method

Automatic reconstruction of DSMs from satellite images is a hot issue in the field of photogrammetry. Nowadays, most state-of-the-art pipelines produce 2.5D products. In order to solve some shortcomings of traditional algorithms and expand the means of updating digital surface models, a DSM generation method based on variational mesh refinement of satellite stereo image pairs to recover 3D surfaces from coarse input is proposed. Specifically, the initial coarse mesh is constructed first and the geometric features of the generated 3D mesh model are then optimized by using the information of the original images, while the 3D mesh subdivision is constrained by combining the image’s texture information and projection information, with subdivision optimization of the mesh model finally achieved. The results of this method are compared qualitatively and quantitatively with those of the commercial software PCI and the SGM method. The experimental results show that the generated 3D digital surface has clearer edge contours, more refined planar textures, and sufficient model accuracy to match well with the actual conditions of the ground surface, proving the effectiveness of the method. The method is advantageous for conducting research on true 3D products in complex urban areas and can generate complete DSM products with the input of rough meshes, thus indicating it has some development prospects

Regression predictive modeling of high-speed motorized spindle using POA-LSTM

With the increasing importance of motorized spindles in high-end machining, the accuracy requirements for motorized spindles have been increasing. Therefore, the accuracy problem caused by thermal deformation of the motor spindle during machining has become a prominent and current topic of interest. The problem of thermal deformation of the spindle is due to the fact that a large amount of heat is accumulated inside the spindle during the high-speed rotation of the electric spindle, which has no timely temperature compensation measures and can only rely on the conditions of heat conduction, heat convection and heat radiation to transfer the heat to the outside world, which leads to the thermal expansion of the spindle. Aiming at this problem, this paper takes the A02 electric spindle as the research object, and collects and analyzes the temperature information of the current temperature rise of the key parts of the electric spindle and the thermal elongation of the spindle by constructing the experimental platform for thermal simulation and analysis; and then through the COMSOL steady-state simulation cloud diagram combined with the K-means clustering and gray correlation analysis, it filters out the four temperature points with the highest correlation degree of the temperature data, and constructs the POA-LSTM thermal error model to predict the thermal elongation of the spindle at different rotational speeds, and compared the accuracy of SSA-LSTM and LSTM thermal error models, at a high rotational speed of 10,000 r/min, the accuracies of Early LSTM, SSA-LSTM, and LSTM were 97.44 %, 90.27 %, and 86.66 %, respectively, and the model accuracy of POA-LSTM was about 98.257 %; thus the POA-LSTM thermal error model has high prediction accuracy and robustness

Simulation analysis model of high-speed motorized spindle structure based on thermal load optimization

High-end CNC machine tools' primary transmission mechanism is a high-speed electric spindle. Thermal displacement of the spindle occurs as a result of heat created inside the spindle during transmission, which has an impact on the machining precision of high-end CNC machine tools. Establishing a high-precision motorized spindle simulation model is crucial because it serves as a foundation for optimizing and testing the motorized spindle's construction and material, adjusting for thermal errors, and estimating its life. The thermal-solid coupling model of the motorized spindle is created by Ansys based on the experimental data of temperature and thermal displacement of the A02 motorized spindle and in accordance with the boundary conditions. The accuracy of front and rear bearings is 93.42% and 90.52%, respectively, when compared to experimental data, and the accuracy of axial thermal displacement is 95.16%. Finally, the motorized spindle is optimized to extend its service life after the thermal displacement, stress, and strain of the bearing are model

CYP1B1: A Novel Molecular Biomarker Predicts Molecular Subtype, Tumor Microenvironment, and Immune Response in 33 Cancers

Background: Cytochrome P450 Family 1 Subfamily B Member 1 (CYP1B1) is a critical metabolic enzyme of melatonin. Although melatonin has been identified to exhibit tumor suppressing activity, the role and mechanism of the clinical and immunological characteristics of CYP1B1 in cancer remain unclear. Methods: In this study, RNA expression and clinical data were obtained from The Cancer Genome Atlas (TCGA) across 33 solid tumors. The expression, survival, immune subtype, molecular subtype, tumor mutation burden (TMB), microsatellite instability (MSI), biological pathways, and function in vitro and vivo were evaluated. The predictive value of CYP1B1 in immune cohorts was further explored. Results: We found the dysregulated expression of CYP1B1 was associated with the clinical stage and tumor grade. Immunological correlation analysis showed CYP1B1 was positively correlated with the infiltration of lymphocyte, immunomodulator, chemokine, receptor, and cancer-associated fibroblasts (CAFs) in most cancer. Meanwhile, CYP1B1 was involved in immune subtype and molecular subtype, and was connected with TMB, MSI, neoantigen, the activation of multiple melatonergic and immune-related pathways, and therapeutic resistance. Conclusions: Together, this study comprehensively revealed the role and mechanism of CYP1B1 and explored the significant association between CYP1B1 expression and immune activity. These findings provide a promising predictor and molecular target for clinical immune treatment

Effects of genus Epimedium in the treatment of osteoarthritis and relevant signaling pathways

Abstract Osteoarthritis (OA) is a common chronic degenerative joint disease in clinical practice with a high prevalence, especially in the elderly. Traditional Chinese Medicine (TCM) believes that OA belongs to the category of “Bi syndrome” and the “bone Bi syndrome”. The etiology and pathogenesis lie in the deficiency of the liver and kidney, the deficiency of Qi and blood, and external exposure to wind, cold, and dampness. Epimedium is a yang-reinforcing herb in TCM, which can tonify the liver and kidney, strengthen muscles and bones, dispel wind, cold and dampness, and can treat both the symptoms and the root cause of “bone Bi syndrome”. In addition, Epimedium contains a large number of ingredients. Through modern science and technology, more than 270 compounds have been found in Epimedium, among which flavonoids are the main active ingredients. Therefore, our study will review the effects and mechanisms of genus Epimedium in treating OA from two aspects: (1) Introduction of Epimedium and its main active ingredients; (2) Effects of Epimedium and its active ingredients in treating OA and relevant signaling pathways, in order to provide more ideas for OA treatment

Study on the Synergistic Effect of Primary Support and Surrounding Rock of Large Buried Depth Tunnel in Soft and Fractured Strata

The soft and fractured strata can cause significant deformation of surrounding rock during tunnel excavation. This study analyzes field monitoring test results and compares numerical simulations from the third bid project of the Dali I section construction within the water diversion project in central Yunnan to address the issue of significant deformation following tunnel excavation in soft and fractured strata. It proposes an optimized support scheme consisting of a densified steel arch and enhanced initial support strength and stiffness. In addition, the research investigates support effectiveness considering varying support strengths and steel arch ring spacing. The study findings indicated the following: (1) The tunnel traverses soft and fractured strata, causing unevenly distributed vertical convergence deformation around the cavern. The maximum settlement occurs at the crown, showing pronounced nonlinearity. (2) The maximum stress in the steel arch is concentrated at the arch crown, measuring −19.02 MPa. The arch remains compressed, with stress decreasing from the crown to the waist. (3) The axial force in the anchor bolt reduces from the crown to the arch’s waist on both sides. As the depth of the rock mass increases, the axial force in each anchor bolt decreases and the tension state is maintained. The maximum axial force reaches 46.57 kN. (4) The maximum displacement decreases from 4.21 to 0.15 cm after the optimized support structure is implemented, demonstrating the optimization scheme’s effectiveness. Future constructions can refer to this scheme and make necessary adjustments based on various terrain conditions to ensure safety

Combined Radar Quality Index for Quantitative Precipitation Estimation of Heavy Rainfall Events

For quantitative precipitation estimation (QPE) based on polarimetric radar (PR) and rain gauges (RGs), the quality of the radar data is crucial for estimation accuracy. This paper proposes a combined radar quality index (CRQI) to represent the quality of the radar data used for QPE and an algorithm that uses CRQI to improve the QPE performance. Nine heavy rainfall events that occurred in Guangdong Province, China, were used to evaluate the QPE performance in five contrast tests. The QPE performance was evaluated in terms of the overall statistics, spatial distribution, near real-time statistics, and microphysics. CRQI was used to identify good-quality data pairs (i.e., PR-based QPE and RG observation) for correcting estimators (i.e., relationships between the rainfall rate and the PR parameters) in real-time. The PR-based QPE performance was improved because estimators were corrected according to variations in the drop size distribution, especially for data corresponding to 1.1 mm < average Dm < 1.4 mm, and 4 < average log10Nw < 4.5. Some underestimations caused by the beam broadening effect, excessive beam height, and partial beam blockages, which could not be mitigated by traditional algorithms, were significantly mitigated by the proposed algorithm using CRQI. The proposed algorithm reduced the root mean square error by 17.5% for all heavy rainfall events, which included three precipitation types: convective precipitation (very heavy rainfall), squall line (huge raindrops), and stratocumulus precipitation (small but dense raindrops). Although the best QPE performance was observed for stratocumulus precipitation, the biggest improvement in performance with the proposed algorithm was observed for the squall line

Research on Interference Mechanism of 25 Hz Phase Sensitive Track Equipment from Unbalanced Current

In a 25-Hz phase-sensitive track circuit, traction backflow is unevenly distributed in the two rails, resulting in interference caused by the 50 Hz unbalanced current, which leads to misoperation of relays and other equipment in the circuit. Focusing on the mechanism of unbalanced current generation, this paper probes the causes of track circuit equipment interference and innovatively analyzes the mechanism of the choke transformer and relay affected, in order to find a method to suppress the interference of the 25 Hz phase-sensitive track equipment. Firstly, the mechanism of unbalanced current generation is explained, and the influence of the unbalanced impulse current on the choke transformer and binary two-bit relay is analyzed. Secondly, the DC magnetic bias, the second side voltage of the choke transformer and the excitation current, flux density, core loss of choke transformer and relay under a different unbalance impulse current are simulated. Then, the unbalanced current simulation test, unbalanced current test during driving and grounding wire test are carried out. Finally, it is concluded that the unbalanced impulse current causes magnetic saturation of the choke transformer, then affects voltage sag of the relay coil, resulting in misoperation of equipment. The conclusions of this paper can play an important guiding role in studying the influence of unbalanced current and restraining the interference of the 25 Hz phase-sensitive track circuit