Numerical computation for vibration characteristics of long-span bridges with considering vehicle-wind coupling excitations based on finite element and neural network models

CA (Cellular Automaton) model was applied to the simulation of random traffic flow to develop a model considering the randomness of traffic flow and apply it to wind-vehicle-bridge coupling vibration. Finite element and neural network models were adopted respectively to numerically compute the vibration characteristics of bridges under wind and vehicle loads, verify the correctness of model. Subspace iteration method was used for the modal analysis of bridges. Natural frequencies of the top 8 orders were 0.21 Hz, 0.27 Hz, 0.36 Hz, 0.45 Hz, 0.56 Hz, 0.66 Hz, 0.87 Hz and 1.02 Hz respectively. The vibration frequency of the long-span bridge was consistent with the vibration characteristics of large-scale complex structures. Natural modes mainly reflected the torsion and bending of main beam and the swinging vibration of side and main towers. Fluctuation wind time-history presented periodic characteristics. The maximum and minimum values of fluctuation wind were about 20 m/s and –20 m/s respectively. The target and simulation values of power spectral density of wind speed were basically the same in change trend, which indicated that the fluctuation wind time-history computed in this paper was reliable. The model of dense traffic flow based on CA more truly described the running status like accelerating, decelerating and changing lanes of vehicles on the bridge, also contained the density information of vehicles and more truly reflected traffic characteristics. Vibration accelerations of the long-span bridge were symmetrically distributed. Vibration acceleration of central position in the left main span was the largest and near 50 cm/s2; vibration acceleration on the main tower was the smallest. The curve of vibration displacement with considering wind loads presented some fluctuations, while the vibration displacement of bridges without considering wind loads was very smooth. In addition, the amplitude of vibration displacement without considering wind loads moved laterally towards the left compared with that with considering wind loads. Therefore, wind loads must be considered when the vibration characteristics of the long-span bridge were computed. Otherwise, the accuracy of computational results would be reduced. It only took 0.5 hours to use neural network to predict the vibration acceleration of the long-span bridge. In the case of the same computer performance, it took 5 hours to use finite element model to predict the vibration acceleration of the long-span bridge. The advantage of neural network model in predicting the performance of large-scale complex structures like a long-span bridge could be obviously found. In the future, we will consider using neural network model to systematically study and optimize the long-span bridge

Research on the computational method of vibration impact coefficient for the long-span bridge and its application in engineering

To compute vibration impact coefficient at each part of the long-span bridge more accurately, this paper proposed a computational method based on vehicle-bridge coupling vibration. Firstly, the general equations of vehicle-bridge coupling vibration were derived based on the standard fatigue vehicle and multi-scale model of bridges. Secondly, the corresponding program of vehicle-bridge coupling vibration was designed. Thirdly, the computational method of vibration impact coefficient for the long-span bridge was introduced and obtained. The proposed computation method of vibration impact coefficient based on vehicle-bridge coupling vibration was finally verified by the corresponding experiment. They were consistent with each other, and the computational method was reliable and can be used to analyze the bridge. Based on the verified method, a lot of influence factors on vibration impact coefficient were analyzed. As a result, we can obtain a bridge with the smallest vibration impact coefficient. Finally, the remaining life of bridges was computed and evaluated based on the smallest vibration impact coefficient

The effects of large extra dimensions on associated ttˉh0t\bar{t} h^0 production at linear colliders

In the framework of the large extra dimensions (LED) model, the effects of LED on the processes \rrtth and \eetth at future linear colliders are investigated in both polarized and unpolarized collision modes. The results show that the virtual Kaluza-Klein (KK) graviton exchange can significantly modify the standard model expectations for these processes with certain polarizations of initial states. The process \rrtth with $\sqrt{s}=3.5 TeV$ allows the effective scale $\Lambda_T$ to be probed up to 7.8 and 8.6 TeV in the unpolarized and $P_{\gamma} = 0.9$, J=2 polarized $\gamma \gamma$ collision modes, respectively. For the \eetth process with $\sqrt{s}=3.5 TeV$, the upper limits of $\Lambda_T$ to be observed can be 6.7 and 7.0 TeV in the unpolarized and $P_{e^+} = 0.6$, $P_{e^-} = 0.8$, $-+$ polarized $e^+e^-$ collision modes, respectively. We find the \rrtth channel in J=2 polarized photon collision mode provides a possibility to improve the sensitivity to the graviton tower exchange.Comment: To be appeard in Physical Review

Research on the computational method of vibration impact coefficient for the long-span bridge and its application in engineering

To compute vibration impact coefficient at each part of the long-span bridge more accurately, this paper proposed a computational method based on vehicle-bridge coupling vibration. Firstly, the general equations of vehicle-bridge coupling vibration were derived based on the standard fatigue vehicle and multi-scale model of bridges. Secondly, the corresponding program of vehicle-bridge coupling vibration was designed. Thirdly, the computational method of vibration impact coefficient for the long-span bridge was introduced and obtained. The proposed computation method of vibration impact coefficient based on vehicle-bridge coupling vibration was finally verified by the corresponding experiment. They were consistent with each other, and the computational method was reliable and can be used to analyze the bridge. Based on the verified method, a lot of influence factors on vibration impact coefficient were analyzed. As a result, we can obtain a bridge with the smallest vibration impact coefficient. Finally, the remaining life of bridges was computed and evaluated based on the smallest vibration impact coefficient

Micro-patterned TiO2 films for photocatalysis

Titanium dioxide film as a stable material plays an important role in photocatalytic degradation of pollutants. One of the ways to improve photocatalytic efficiency is to increase the active sites on the semiconductor surface. Photolithography is a manufacturing technique for controlling precisely micrographics on surface. Here grating-structured, square-structured and hexagon-structured TiO2 films were prepared by photolithography and the effects of various surface structures on photocatalysis were studied. It was demonstrated that the photocatalytic activity of TiO2 film was not always improved as the surface area increased. The micro-patterned surface would also impede the mass transfer in the process of photocatalysis. (C) 2019 Elsevier B.V. All rights reserved

Sulfated tyrosines 27 and 29 in the N-terminus of human CXCR3 participate in binding native IP-10

Aim: Human CXCR3, a seven-transmembrane segment (7TMS), is predominantly expressed in Th1-mediated responses. Interferon-γ-inducible protein 10 (IP-10) is an important ligand for CXCR3. Their interaction is pivotal for leukocyte migration and activation. Tyrosine sulfation in 7TMS is a posttranslational modification that contributes substantially to ligand binding. We aimed to study the role of tyrosine sulfation of CXCR3 in the protein's binding to IP-10. Methods: Plasmids encoding CXCR3 and its mutants were prepared by PCR and site-directed mutagenesis. HEK 293T cells were transfected with plasmids encoding CXCR3 or its variants using calcium phosphate. Transfected cells were labeled with [35S]-cysteine and methionine or [35S]-Na2SO3 and then analyzed by immunoprecipitation to measure sulfation. Experiments with 125I-labeled IP-10 were carried out to evaluate the affinity of CXCR3 for its ligand. Calcium influx assays were used to measure intercellular signal transduction. Results: Our data show that sulfate moieties are added to tyrosines 27 and 29 of CXCR3. Mutation of these two tyrosines to phenylalanines substantially decreases binding of CXCR3 to IP-10 and appears to eliminate the associated signal transduction. Tyrosine sulfation of CXCR3 is enhanced by tyrosyl protein sulfotransferases (TPSTs), and it is weakened by shRNA constructs. The binding ability of CXCR3 to IP-10 is increased by TPSTs and decreased by shRNAs. Conclusions: This study identifies two sulfated tyrosines in the N-terminus of CXCR3 as part of the binding site for IP-10, and it underscores the fact that tyrosine sulfation in the N-termini of 7TMS receptors is functionally important for ligand interactions. Our study suggests a molecular target for inhibiting this ligand-receptor interaction

The Impacts of Swimming Exercise on Hippocampal Expression of Neurotrophic Factors in Rats Exposed to Chronic Unpredictable Mild Stress

Depression is associated with stress-induced neural atrophy in limbic brain regions, whereas exercise has antidepressant effects as well as increasing hippocampal synaptic plasticity by strengthening neurogenesis, metabolism, and vascular function. A key mechanism mediating these broad benefits of exercise on the brain is induction of neurotrophic factors, which instruct downstream structural and functional changes. To systematically evaluate the potential neurotrophic factors that were involved in the antidepressive effects of exercise, in this study, we assessed the effects of swimming exercise on hippocampal mRNA expression of several classes of the growth factors (BDNF, GDNF, NGF, NT-3, FGF2, VEGF, and IGF-1) and peptides (VGF and NPY) in rats exposed to chronic unpredictable mild stress (CUMS). Our study demonstrated that the swimming training paradigm significantly induced the expression of BDNF and BDNF-regulated peptides (VGF and NPY) and restored their stress-induced downregulation. Additionally, the exercise protocol also increased the antiapoptotic Bcl-xl expression and normalized the CUMS mediated induction of proapoptotic Bax mRNA level. Overall, our data suggest that swimming exercise has antidepressant effects, increasing the resistance to the neural damage caused by CUMS, and both BDNF and its downstream neurotrophic peptides may exert a major function in the exercise related adaptive processes to CUMS

Adenosine A2A Receptors Mediate Anti-Inflammatory Effects of Electroacupuncture on Synovitis in Mice with Collagen-Induced Arthritis

To study the role of adenosine A2A receptor (A2AR) in mediating the anti-inflammatory effect of electroacupuncture (EA) on synovitis in collagen-induced arthritis (CIA), C57BL/6 mice were divided into five treatment groups: Sham-control, CIA-control, CIA-EA, CIA-SCH58261 (A2AR antagonist), and CIA-EA-SCH58261. All mice except those in the Sham-control group were immunized with collagen II for arthritis induction. EA treatment was administered using the stomach 36 and spleen 6 points, and stimulated with a continuous rectangular wave for 30 min daily. EA treatment and SCH58261 were administered daily from days 35 to 49 (n=10). After treatment, X-ray radiography of joint bone morphology was established at day 60 and mouse blood was collected for ELISA determination of tumor necrosis factor alpha (TNF-α) levels. Mice were sacrificed and processed for histological examination of pathological changes of joint tissue, including hematoxylin-eosin staining and immunohistochemistry of A2AR expression. EA treatment resulted in significantly reduced pathological scores, TNF-α concentrations, and bone damage X-ray scores. Importantly, the anti-inflammatory and tissue-protective effect of EA treatment was reversed by coadministration of SCH58261. Thus, EA treatment exerts an anti-inflammatory effect resulting in significant protection of cartilage by activation of A2AR in the synovial tissue of CIA