Impact of multichannel river network on the plume dynamics in the Pearl River estuary

Author Posting. © American Geophysical Union, 2015. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 120 (2015): 5766–5789, doi:10.1002/2014JC010490.Impacts of the multichannel river network on plume dynamics in the Pearl River estuary were examined using a high-resolution 3-D circulation model. The results showed that during the dry season the plume was a distinct feature along the western coast of the estuary. The plume was defined as three water masses: (a) riverine water (22 psu), respectively. A significant amount of low-salinity water from Hengmen and Hongqimen was transported through a narrow channel between the QiAo Island and the mainland of the Pearl River delta during the ebb tide and formed a local salinity-gradient feature (hereafter referred to as a discharge plume). This discharge plume was a typical small-scale river plume with a Kelvin number K = 0.24 and a strong frontal boundary on its offshore side. With evidence of a significant impact on the distribution and variability of the salinity and flow over the West Shoal, this plume was thought to be a major feature of the Pearl River plume during the dry season. The upstream multichannel river network not only were the freshwater discharge sources but also played a role in establishing an estuarine-scale subtidal pressure gradient. This pressure gradient was one of the key dynamical processes controlling the water exchange between discharge and river plumes in the Pearl River estuary. This study clearly showed the role of the river network and estuary interaction on river plume dynamics.The research work was supported by the National Natural Science Foundation of China (grant 41206005), the Ocean Public Welfare Scientific Research Project, State Oceanic Administration of the People's Republic of China (grant 201305019-3) and the CAS Strategic Pilot Science and Technology (XDA11020205). Changsheng Chen's participation was supported by the International Center for Marine Studies, Shanghai Ocean University.2016-02-2

Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis

Multivariate Time Series (MTS) widely exists in real-word complex systems, such as traffic and energy systems, making their forecasting crucial for understanding and influencing these systems. Recently, deep learning-based approaches have gained much popularity for effectively modeling temporal and spatial dependencies in MTS, specifically in Long-term Time Series Forecasting (LTSF) and Spatial-Temporal Forecasting (STF). However, the fair benchmarking issue and the choice of technical approaches have been hotly debated in related work. Such controversies significantly hinder our understanding of progress in this field. Thus, this paper aims to address these controversies to present insights into advancements achieved. To resolve benchmarking issues, we introduce BasicTS, a benchmark designed for fair comparisons in MTS forecasting. BasicTS establishes a unified training pipeline and reasonable evaluation settings, enabling an unbiased evaluation of over 30 popular MTS forecasting models on more than 18 datasets. Furthermore, we highlight the heterogeneity among MTS datasets and classify them based on temporal and spatial characteristics. We further prove that neglecting heterogeneity is the primary reason for generating controversies in technical approaches. Moreover, based on the proposed BasicTS and rich heterogeneous MTS datasets, we conduct an exhaustive and reproducible performance and efficiency comparison of popular models, providing insights for researchers in selecting and designing MTS forecasting models

Efficient and tunable liquid crystal random laser based on plasmonic-enhanced FRET

Random lasers (RLs), which possess peculiar advantages (e.g., emission and coherence tunable) over traditional lasers with optical resonators, have witnessed rapid development in the past decades. However, it is still a challenge to tune the lasing peak of an RL over a wide range. Here, a temperature-dependent Förster resonance energy transfer (FRET) RL is demonstrated in pyrromethene 597 (PM597, “donor”) and Nile blue (NB, “acceptor”) doped chiral liquid crystals. By changing the temperature that drives the liquid crystal bandgap shift, our RL device exhibits a lasing output change from 560 nm (yellow) to 700 nm (red). While the intrinsic FRET efficiency between PM597 and NB is relatively low, the red lasing is weak. By introducing gold nanorods (GNRs) into these RL devices and utilizing GNRs’ localized surface plasmon resonance (LSPR) effect, the efficiency of FRET transfer is increased by 68.9%, thereby reducing the threshold of the RL devices. By tuning the longitudinal LSPR to match the emission wavelength of NB, the best 200-fold lasing intensity enhancement is recorded. Our findings open a pathway toward realizing LSPR-enhanced FRET tunable RLs and broaden the range of their possible exploration in photonics research and technologies

Evaluation Method for the Liquefaction Potential Using the Standard Penetration Test Value Based on the CPTU Soil Behavior Type Index

Taking the project of the Su-xin highway treated by using the resonant compaction method as the reference, a new method for the evaluation of liquefaction potential is proposed based on the piezocone penetration test (CPTU) and the standard penetration test (SPT). The soil behavior type index (Ic) obtained from CPTUs and the standard penetration test index (N63.5), obtained from SPTs, are analyzed for saturated silty sand and silt. The analysis result reveals a linear relationship between N63.5 and Ic, given by N63.5=−18.8Ic+52.0. The larger the value of Ic is, the greater the viscosity of soil is, and the smaller the value of N63.5 is. According to the method, liquefaction assessment of saturated silty sand and silt foundation can be conducted by using N63.5 based on the Code of Seismic Design of Building. N63.5 is expressed by a single Ic, which is calculated from the CPTU data. Compared with existing evaluation methods, this method can provide continuous standard penetration test values, moreover, this method involves a simple calculation, and the results obtained using the method are reliable

STG-GAN: A spatiotemporal graph generative adversarial networks for short-term passenger flow prediction in urban rail transit systems

Short-term passenger flow prediction is an important but challenging task for better managing urban rail transit (URT) systems. Some emerging deep learning models provide good insights to improve short-term prediction accuracy. However, there exist many complex spatiotemporal dependencies in URT systems. Most previous methods only consider the absolute error between ground truth and predictions as the optimization objective, which fails to account for spatial and temporal constraints on the predictions. Furthermore, a large number of existing prediction models introduce complex neural network layers to improve accuracy while ignoring their training efficiency and memory occupancy, decreasing the chances to be applied to the real world. To overcome these limitations, we propose a novel deep learning-based spatiotemporal graph generative adversarial network (STG-GAN) model with higher prediction accuracy, higher efficiency, and lower memory occupancy to predict short-term passenger flows of the URT network. Our model consists of two major parts, which are optimized in an adversarial learning manner: (1) a generator network including gated temporal conventional networks (TCN) and weight sharing graph convolution networks (GCN) to capture structural spatiotemporal dependencies and generate predictions with a relatively small computational burden; (2) a discriminator network including a spatial discriminator and a temporal discriminator to enhance the spatial and temporal constraints of the predictions. The STG-GAN is evaluated on two large-scale real-world datasets from Beijing Subway. A comparison with those of several state-of-the-art models illustrates its superiority and robustness. This study can provide critical experience in conducting short-term passenger flow predictions, especially from the perspective of real-world applications.Comment: 13 pages, 10 figures, 5 table

Comparison of alternative remediation technologies for recycled gravel contaminated with heavy metals

To evaluate the effects of different remediation methods on heavy metals contaminated recycled gravel, three immobilization agents (monopotassium phosphate, lime, nano-iron) and two mobilization agents (glyphosate, humic acid (HA)) were studied and compared. Results indicated that nano-iron powder was found to be more effective to immobilize Zn, Cu, Pb and Cd. Meanwhile, glyphosate presents a higher mobilization effect than HA with removal rates of about 66.7% for Cd, more than 80% for Cr, Cu and Zn, and the highest removal percentage of 85.9% for Cr. After the mobilization by glyphosate, the leaching rates of Zn, Cu and Cr were about 0.8%, and below 0.2% for Pb and Cd. The leaching rates after nano-iron powder treatment were 1.18% for Zn, 0.96% for Cr, 0.61% for Cu, 0.45% for Pb and Cd not detected. The formation and disappearance of metal (Zn/Cu/Cr/Pb/Cd) compounds were firmly confirmed through X-ray diffraction and scanning electron microscopy analyses on crystalline phases and morphological surface structures

Palladium Supported on Titanium Carbide: A Highly Efficient, Durable, and Recyclable Bifunctional Catalyst for the Transformation of 4-Chlorophenol and 4-Nitrophenol

Developing highly efficient and recyclable catalysts for the transformation of toxic organic contaminates still remains a challenge. Herein, Titanium Carbide (Ti3C2) MXene modified by alkali treatment process was selected as a support (designated as alk-Ti3C2X2, where X represents the surface terminations) for the synthesis of Pd/alk-Ti3C2X2. Results show that the alkali treatment leads to the increase of surface area and surface oxygen-containing groups of Ti3C2X2, thereby facilitating the dispersion and stabilization of Pd species on the surface of alk-Ti3C2X2. The Pd/alk-Ti3C2X2 catalyst shows excellent catalytic activity for the hydrodechlorination of 4-chlorophenol and the hydrogenation of 4-nitrophenol in aqueous solution at 25 °C and hydrogen balloon pressure. High initial reaction rates of 216.6 and 126.3 min−1· g pd − 1 are observed for the hydrodechlorination of 4-chlorophenol and hydrogenation of 4-nitrophenol, respectively. Most importantly, Pd/alk-Ti3C2X2 exhibits excellent stability and recyclability in both reactions without any promoters. The superior property of Pd/alk-Ti3C2X2 makes it as a potential material for practical applications