A Hybrid Approach Based on Variational Mode Decomposition for Analyzing and Predicting Urban Travel Speed

Predicting travel speeds on urban road networks is a challenging subject due to its uncertainty stemming from travel demand, geometric condition, traffic signals, and other exogenous factors. This uncertainty appears as nonlinearity, nonstationarity, and volatility in traffic data, and it also creates a spatiotemporal heterogeneity of link travel speed by interacting with neighbor links. In this study, we propose a hybrid model using variational mode decomposition (VMD) to investigate and mitigate the uncertainty of urban travel speeds. The VMD allows the travel speed data to be divided into orthogonal and oscillatory sub-signals, called modes. The regular components are extracted as the low-frequency modes, and the irregular components presenting uncertainty are transformed into a combination of modes, which is more predictable than the original uncertainty. For the prediction, the VMD decomposes the travel speed data into modes, and these modes are predicted and summed to represent the predicted travel speed. The evaluation results on urban road networks show that, the proposed hybrid model outperforms the benchmark models both in the congested and in the overall conditions. The improvement in performance increases significantly over specific link-days, which generally are hard to predict. To explain the significant variance of the prediction performance according to each link and each day, the correlation analysis between the properties of modes and the performance of the model are conducted. The results on correlation analysis show that the more variance of nondaily pattern is explained through the modes, the easier it was to predict the speed. Based on the results, discussions on the interpretation on the correlation analysis and future research are presented. Document type: Articl

Hepatitis C Virus NS5B Protein Is a Membrane-Associated Phosphoprotein with a Predominantly Perinuclear Localization

AbstractHepatitis C virus NS5B protein is an RNA-dependent RNA polymerase. To investigate the properties and function of this protein, we have expressed the NS5B protein in insect and mammalian cells. NS5B was found to be present as fine speckles in the cytoplasm, particularly concentrated in the perinuclear region, suggesting its association with the nuclear membrane, the endoplasmic reticulum, or the Golgi complex. This conclusion was supported by the biochemical demonstration that NS5B was associated with the membranes in the cells. Furthermore, it was shown that NS5B protein is a phosphoprotein. These properties may be related to its function as an RNA polymerase

(E)-1-(4-Bromo­phen­yl)-2-(4-tert-butyl­phen­yl)-1-phenyl­ethene

In the structure of the title compound, C24H23Br, the configuration about the double bond is E. The dihedral angles between the tert-butyl-substituted benzene ring and the unsubstituted and Br-substituted rings are 57.1 (2) and 78.2 (2)°, respectively. The methyl groups are disordered over two positions; the site occupancy factors are ca 0.8 and 0.2

Multiobjective loading pattern optimization by simulated annealing employing discontinuous penalty function and screening technique

The problem of multiobjective fuel loading pattern (LP) optimization employing high-fidelity three-dimensional (3-D) models is resolved by introducing the concepts of discontinuous penalty function, dominance, and two-dimensional (2-D)–based screening into the simulated annealing (SA) algorithm. Each constraint and objective imposed on a reload LP design is transformed into a discontinuous penalty function that involves a jump to a quadratic variation at the point of the limiting value of the corresponding core characteristics parameter. It is shown that with this discontinuous form the sensitivity of the penalty coefficients is quite weak compared to the stochastic effect of SA. The feasible LPs found during SA update the set of candidate LPs through a dominance check that is done by examining multiple objectives altogether. The 2-D–based screening technique uses a precalculated database of the 2-D solution errors and is shown to be very effective in saving the SA computation time by avoiding 3-D evaluations for the unfavorable LPs that are frequently encountered in SA. Realistic applications of the proposed method to a pressurized water reactor reload LP optimization with the dual objectives of maximizing the cycle length and minimizing the radial peaking factor demonstrate that the method works quite well in practice.This work was supported by the project funded by the Ministry of Knowledge Economy of Korea to develop primary design codes for nuclear power plants

Revealing salt-expedited reduction mechanism for hollow silicon microsphere formation in bi-functional halide melts

The thermochemical reduction of silica to silicon using chemical reductants requires high temperature and has a high activation energy, which depends on the melting temperature of the reductant. The addition of bi-functional molten salts with a low melting temperature may reduce the required energy, and several examples using molten salts have been demonstrated. Here we study the mechanism of reduction of silica in the presence of aluminum metal reductant and aluminum chloride as bi-functional molten salts. An aluminum-aluminum chloride complex plays a key role in the reduction mechanism, reacting with the oxygen of the silica surfaces to lower the heat of reaction and subsequently survives a recycling step in the reaction. This experimentally and theoretically validated reaction mechanism may open a new pathway using bi-functional molten salts. Furthermore, the as-synthesized hollow porous silicon microsphere anodes show structural durability on cycling in both half/full cell tests, attributed to the high volume-accommodating ability