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The full-field responses and high-resolution mode shapes are of paramount importance in the detection of bridge damage and finite element model updating. As enlightened by the Fourier series expansion of the mode shapes for a bridge, this study proposes an approach for compressive sensing-based reconstruction of the full-field responses and identification of high-resolution mode shapes, in which a general basis matrix is newly formulated, with particular application to beam-like continuous or non-uniform bridges. The merits of the proposed approach are model-free, output-only, and easy to implement, especially the need of a few sensors. The effectiveness of the approach is validated through both numerical and experimental examples by considering various bridge boundary conditions and non-uniform cross-sections, from which the potential application of this general approach is foreseeable. [ABSTRACT FROM AUTHOR]

As the frequency variation in a moving mass-plate system is seldom discussed in the previous work, this study first formulates the semi-analytical solutions of a system consisting of a moving mass on a square plate. Based on the moving mass-plate system, several finite element models with designed plate-type bridges are established to further investigate the effect of moving mass on a plate, the influence of bridge local modes, and the influence of moving loads on a bridge. The numerical results have shown that the frequency variation of a plate-type bridge can reach 30% for the first three modes. The unique phenomenon of wave propagation is exhibited in the acceleration responses of the plate-type bridge, while it is uncommon for a beam-type bridge. For design purpose, the following are remarked: (1) The use of Rayleigh damping on the stiffened bridge can effectively suppress the influence of local modes on the bridge deck. (2) The high stiffness in the moving load can be served as the damper to reduce the dynamic responses of a vehicle. (3) In the design stage of a plate-type bridge subjected to moving loads, the moving force is the most conservative one among the three moving loads. [ABSTRACT FROM AUTHOR]

In this study, a meshfree framework based on the reproducing kernel collocation method is proposed for incrementaliterative analysis of double-diffusive natural convection in a porous enclosure, in which the forward difference method is adopted for temporal discretization, and the two-step version of Newton-Raphson method is used for iteration. As the double-diffusive convection problem is composed of multi phases and is influenced by both material and geometric parameters, the resulting system is highly nonlinear and complicated. From the numerical investigation, the partially heated boundary with different buoyancy ratios can yield monocellular flow problems with opposite phenomena depending on the contribution of thermal/solute buoyancy force. For the domains with burrowing inside, the key feature is the contour of stream function, which is separated into two vortexes by the hole in the simply connected domain while the two vortexes are not separated completely in the multiply connected domain due to the geometric compression of two holes. It is further shown that the framework is capable of solving various double-diffusive convection problems with satisfactory accuracy and efficiency by uniform discretization as well as few source points in the approximation. [ABSTRACT FROM AUTHOR]

Early and accurate identification of almond [Prunus dulcis (Mill.) D.A. Webb] cultivars is critical to commercial growers and nurseries. Previously published simple sequence repeat loci were examined for their ability to distinguish commonly grown almond cultivars. Twelve highly polymorphic loci were selected for their ability to uniquely identify a set of 18 almond cultivars commonly grown in California, many of which are closely related. These markers also allow an accurate assessment of parent/progeny relationships among cultivars. This system can reliably identify at an early stage of development all major California almond cultivars in current production.

In the vehicle scanning method, using the amplifier as the tuned mass damper in the vehicle–bridge system has been shown to be able to scan the higher bridge frequencies clearly in the amplifier spectrum recently. To design a test vehicle enhanced by one or two amplifiers in practice, the analytical approach undoubtedly serves as the guideline. For this purpose, this study is aimed at deriving the analytical formulation for one amplifier-enhanced vehicle–bridge system and the semi-analytical formulation for two amplifier-enhanced vehicle–bridge system, while a miniature three-mass vehicle model is adopted. The correctness of the analytical formulations is verified by the finite element formulations through the dynamic responses of the amplifier, vehicle body, and bridge; good agreement is observed for all responses. The amplifier spectra are further provided to show the distinctly scanned bridge frequencies. [ABSTRACT FROM AUTHOR]

The spatial-varying frequency of a vehicle-bridge interaction (VBI) system subjected to a moving mass is theoretically derived and numerically investigated through a three-dimensional VBI model, in which the effects of moving mass are introduced through the inertial force and centrifugal force in the equation of motion of the bridge. For a large vehicle-to-bridge mass ratio, it has been known that the frequency of a VBI system could change with respect to the location of a moving vehicle. As such, this study derives the analytical solution based on a moving mass-beam system to account for frequency variation and further builds the numerical model with detailed implementation for practical applications. The numerical results show the following findings: (1) The frequency of a VBI system is a function of velocity and location of a moving vehicle. (2) The reduction of spatial-varying frequency ratio for a particular mode decreases with respect to the mode of higher order. (3) The maximum reduction of spatial-varying frequency ratio of the first mode in a moving mass-beam system occurs in the location where the bridge has the maximum deflection as a result of local mode excitation. (4) For the VBI system with high suspension stiffness and large vehicle-to-bridge mass ratio, the absolute variation of spatial-varying frequency ratio of the first mode can be up to 30–40%. [ABSTRACT FROM AUTHOR]

This study explores changes in wage inequality in Vietnam during a prolonged period of economic transformation. We found that wage inequality increased in the earlier period of 1998–2010, but declined considerably in the following period of 2010–2020. The change in economic structure and increased supply of higher educated workforce have substantially contributed to changing wage inequality. Overall changes in increasing wage inequality over the former period was mainly due to changes in labor market, job and workers' observed characteristics. In the latter period, however, the decline in wage inequality was related to changes in the returns to job and workers' observed characteristics. A rapid rise in supply of higher educated workers, which exceeded the demand for skilled labor, in the later stage of economic transformation also contributed to declining returns to education and the decline in wage inequality. [ABSTRACT FROM AUTHOR]

Time-history responses of the bridge induced by the moving vehicle provide crucial information for bridge design, operation, maintenance, etc. As inspired by this, this work attempts to provide a new paradigm for vehicle–bridge interaction (VBI) by highlighting the comparison of different deep learning algorithms applied to the prediction of time-history responses of the bridge under vehicular loads. Particularly, three deep learning architectures with few and measurable input features developed by using fully-connected feedforward neural network, long short-term memory (LSTM) network, and convolutional neural network (CNN) are proposed on the basis of the governing equation of bridge vibrations. Three VBI systems with various vehicle models are developed and further validated to produce reliable training data. To examine the accuracy of the predictive models, two advanced metrics are exploited for time-history estimate. Moreover, the proposed deep learning models are comprehensively investigated through a parametric study on the influential factors associated with the VBI system and network architecture. The results show that deep feedforward neural network (DFNN), LSTM network, and CNN can be applied in VBI analysis to estimate the bridge time-history response. The three neural networks have comparable prediction accuracies. When considering the irregularity excitation, CNN is found to be the most efficient predictive model, while DFNN needs the least training time under perfect bridge surface condition. [ABSTRACT FROM AUTHOR]