e-Distance Weighted Support Vector Regression

We propose a novel support vector regression approach called e-Distance Weighted Support Vector Regression (e-DWSVR).e-DWSVR specifically addresses two challenging issues in support vector regression: first, the process of noisy data; second, how to deal with the situation when the distribution of boundary data is different from that of the overall data. The proposed e-DWSVR optimizes the minimum margin and the mean of functional margin simultaneously to tackle these two issues. In addition, we use both dual coordinate descent (CD) and averaged stochastic gradient descent (ASGD) strategies to make e-DWSVR scalable to large scale problems. We report promising results obtained by e-DWSVR in comparison with existing methods on several benchmark datasets

Large Margin Distribution Machine Recursive Feature Elimination

We gratefully thank Dr Teng Zhang and Prof Zhi-Hua Zhou for providing the source code of “LDM” source code and their kind technical assistance. This work is supported by the National Natural Science Foundation of China (Nos. 61472159, 61572227) and Development Project of Jilin Province of China (Nos. 20160204022GX, 2017C033). This work is also partially supported by the 2015 Scottish Crucible Award funded by the Royal Society of Edinburgh and the 2016 PECE bursary provided by the Scottish Informatics & Computer Science Alliance (SICSA).Postprin

Sediment transport near ship shoal for coastal restoration in the Louisiana Shelf: a model estimate of the year 2017-2018

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Liu, H., Xu, K., Ou, Y., Bales, R., Zang, Z., & Xue, Z. G. Sediment transport near ship shoal for coastal restoration in the Louisiana Shelf: a model estimate of the year 2017-2018. Water, 12(8), (2020): 2212, doi:10.3390/w12082212.Ship Shoal has been a high-priority target sand resource for dredging activities to restore the eroding barrier islands in LA, USA. The Caminada and Raccoon Island pits were dredged on and near Ship Shoal, which resulted in a mixed texture environment with the redistribution of cohesive mud and noncohesive sand. However, there is very limited knowledge about the source and transport process of suspended muddy sediments near Ship Shoal. The objective of this study is to apply the Regional Ocean Modeling System (ROMS) model to quantify the sediment sources and relative contribution of fluvial sediments with the estuary and shelf sediments delivered to Ship Shoal. The model results showed that suspended mud from the Atchafalaya River can transport and bypass Ship Shoal. Only a minimal amount of suspended mud from the Atchafalaya River can be delivered to Ship Shoal in a one-year time scale. Additionally, suspended mud from the inner shelf could be transported cross Ship Shoal and generate a thin mud layer, which is also considered as the primary sediment source infilling the dredge pits near Ship Shoal. Two hurricanes and one tropical storm during the year 2017–2018 changed the direction of the sediment transport flux near Ship Shoal and contributed to the pit infilling (less than 10% for this specific period). Our model also captured that the bottom sediment concentration in the Raccoon Island pit was relatively higher than the one in Caminada in the same period. Suspended mud sediment from the river, inner shelf, and bay can bypass or transport and deposit in the Caminada pit and Raccoon Island pit, which showed that the Caminada pit and Raccoon Island pits would not be considered as a renewable borrow area for future sand dredging activities for coastal restoration.Funding for this study was provided by the U.S. Department of the Interior, Bureau of Ocean Energy Management, Coastal Marine Institute, Washington DC, under Cooperative Agreement Numbers M16AC00018 and M17AC00019

The role of sediment-induced light attenuation on primary production during Hurricane Gustav (2008)

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zang, Z., Xue, Z. G., Xu, K., Bentley, S. J., Chen, Q., D'Sa, E. J., Zhang, L., & Ou, Y. The role of sediment-induced light attenuation on primary production during Hurricane Gustav (2008). Biogeosciences, 17(20), (2020): 5043-5055, doi:10.5194/bg-17-5043-2020.We introduced a sediment-induced light attenuation algorithm into a biogeochemical model of the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system. A fully coupled ocean–atmospheric–sediment–biogeochemical simulation was carried out to assess the impact of sediment-induced light attenuation on primary production in the northern Gulf of Mexico during the passage of Hurricane Gustav in 2008. When compared with model results without sediment-induced light attenuation, our new model showed a better agreement with satellite data on both the magnitude of nearshore chlorophyll concentration and the spatial distribution of offshore bloom. When Hurricane Gustav approached, resuspended sediment shifted the inner shelf ecosystem from a nutrient-limited one to a light-limited one. Only 1 week after Hurricane Gustav's landfall, accumulated nutrients and a favorable optical environment induced a posthurricane algal bloom in the top 20 m of the water column, while the productivity in the lower water column was still light-limited due to slow-settling sediment. Corresponding with the elevated offshore NO3 flux (38.71 mmol N m−1 s−1) and decreased chlorophyll flux (43.10 mg m−1 s−1), the outer shelf posthurricane bloom should have resulted from the cross-shelf nutrient supply instead of the lateral dispersed chlorophyll. Sensitivity tests indicated that sediment light attenuation efficiency affected primary production when sediment concentration was moderately high. Model uncertainties due to colored dissolved organic matter and parameterization of sediment-induced light attenuation are also discussed.This research has been supported by the National Science Foundation (grant nos. CCF-1856359, EnvS-1903340, OCE-1635837 and EAR-1427389), NASA (grant no. NNH17ZHA002C), the Louisiana Board of Regents (grant no. NASA/LEQSF(2018-20)-Phase3-11) and the LSU Foundation Billy and Ann Harrison Endowment for Sedimentary Geology

Signaling, Entanglement, and Quantum Evolution Beyond Cauchy Horizons

Consider a bipartite entangled system half of which falls through the event horizon of an evaporating black hole, while the other half remains coherently accessible to experiments in the exterior region. Beyond complete evaporation, the evolution of the quantum state past the Cauchy horizon cannot remain unitary, raising the questions: How can this evolution be described as a quantum map, and how is causality preserved? What are the possible effects of such nonstandard quantum evolution maps on the behavior of the entangled laboratory partner? More generally, the laws of quantum evolution under extreme conditions in remote regions (not just in evaporating black-hole interiors, but possibly near other naked singularities and regions of extreme spacetime structure) remain untested by observation, and might conceivably be non-unitary or even nonlinear, raising the same questions about the evolution of entangled states. The answers to these questions are subtle, and are linked in unexpected ways to the fundamental laws of quantum mechanics. We show that terrestrial experiments can be designed to probe and constrain exactly how the laws of quantum evolution might be altered, either by black-hole evaporation, or by other extreme processes in remote regions possibly governed by unknown physics.Comment: Combined, revised, and expanded version of quant-ph/0312160 and hep-th/0402060; 13 pages, RevTeX, 2 eps figure

Experimental Demonstration of DDoS Mitigation over a Quantum Key Distribution (QKD) Network Using Software Defined Networking (SDN)

We experimentally demonstrate, for the first time, DDoS mitigation of QKD-based networks utilizing a software defined network application. Successful quantum-secured link allocation is achieved after a DDoS attack based on real-time monitoring of quantum parametersComment: Accepted for presentation in OFC 2018 Conference. M2A.

MADNESS: A Multiresolution, Adaptive Numerical Environment for Scientific Simulation

MADNESS (multiresolution adaptive numerical environment for scientific simulation) is a high-level software environment for solving integral and differential equations in many dimensions that uses adaptive and fast harmonic analysis methods with guaranteed precision based on multiresolution analysis and separated representations. Underpinning the numerical capabilities is a powerful petascale parallel programming environment that aims to increase both programmer productivity and code scalability. This paper describes the features and capabilities of MADNESS and briefly discusses some current applications in chemistry and several areas of physics

Adapting Low-Cost Drone Technology to CubeSats for Environmental Monitoring and Management: Harmful Algal Bloom Satellite-1 (HABsat-1)

HABsat-1 is designed to improve our understanding of algal bloom dynamics and their causes on land by addressing several current limiting factors for this application using existing satellites. For example, there is suboptimal imager design for water, insufficient spatial resolution for precise co-registration of surface observations, and too few satellites with such capabilities to defeat cloud cover in maritime, tropical and temperate climates. We will overcome these problems by merging a new low-cost multispectral imaging technology with a low-cost CubeSat bus. CubeSats cost roughly 1/100th to 1/1000th of most current long-life imaging satellites. Such cost decreases are necessary to improve upon the temporal coverage (number of appropriate satellites) and spatial resolution of current imaging satellites, such as Landsat-8, Sentinel-2 and Sentinel-3 (MERIS/OLCI). Numerous low-cost satellites reduce both overall mission cost and individual launch risks associated with large production satellites, such as Landsat, while providing the temporal and spatial resolution necessary for the study of highly dynamic and spatially variable algal blooms. A team of undergraduate aerospace engineers (the UC CubeCats), computer scientists and aerospace and geographic information science faculty have been funded by the Ohio Department of Higher Education and NOAA to adapt low-cost multispectral imagers designed for use on small drones to 3U CubeSats to further reduce the cost of environmental monitoring. This team will create a working on-orbit prototype for a constellation of CubeSat’s for routine drinking water monitoring known as Harmful Algal Bloom Satellite 1 (HABsat-1)