Low-Density Arrays of Circulant Matrices: Rank and Row-Redundancy Analysis, and Quasi-Cyclic LDPC Codes

This paper is concerned with general analysis on the rank and row-redundancy of an array of circulants whose null space defines a QC-LDPC code. Based on the Fourier transform and the properties of conjugacy classes and Hadamard products of matrices, we derive tight upper bounds on rank and row-redundancy for general array of circulants, which make it possible to consider row-redundancy in constructions of QC-LDPC codes to achieve better performance. We further investigate the rank of two types of construction of QC-LDPC codes: constructions based on Vandermonde Matrices and Latin Squares and give combinatorial expression of the exact rank in some specific cases, which demonstrates the tightness of the bound we derive. Moreover, several types of new construction of QC-LDPC codes with large row-redundancy are presented and analyzed.Comment: arXiv admin note: text overlap with arXiv:1004.118

MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video

The past few years have witnessed great success in applying deep learning to enhance the quality of compressed image/video. The existing approaches mainly focus on enhancing the quality of a single frame, not considering the similarity between consecutive frames. Since heavy fluctuation exists across compressed video frames as investigated in this paper, frame similarity can be utilized for quality enhancement of low-quality frames given their neighboring high-quality frames. This task is Multi-Frame Quality Enhancement (MFQE). Accordingly, this paper proposes an MFQE approach for compressed video, as the first attempt in this direction. In our approach, we firstly develop a Bidirectional Long Short-Term Memory (BiLSTM) based detector to locate Peak Quality Frames (PQFs) in compressed video. Then, a novel Multi-Frame Convolutional Neural Network (MF-CNN) is designed to enhance the quality of compressed video, in which the non-PQF and its nearest two PQFs are the input. In MF-CNN, motion between the non-PQF and PQFs is compensated by a motion compensation subnet. Subsequently, a quality enhancement subnet fuses the non-PQF and compensated PQFs, and then reduces the compression artifacts of the non-PQF. Also, PQF quality is enhanced in the same way. Finally, experiments validate the effectiveness and generalization ability of our MFQE approach in advancing the state-of-the-art quality enhancement of compressed video. The code is available at https://github.com/RyanXingQL/MFQEv2.0.git.Comment: Accepted to TPAMI in September, 2019. v6 updates: correct units in Fig. 11; correct author info; delete bio photos. arXiv admin note: text overlap with arXiv:1803.0468

Concentrations and sources of polycyclic aromatic hydrocarbons in surface coastal sediments of the northern Gulf of Mexico

Zucheng Wang is with the Department of Geography, Northeast Normal University, Changchun, China. -- Zucheng Wang and Zhanfei Liu are with the Marine Science Institute, The University of Texas at Austin, Port Aransas, TX, USA. -- Kehui Xu is with the Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA, USA – and – the Coastal Studies Institute, Louisiana State University, Baton Rouge, LA, USA. -- Lawrence M Mayer is with the School of Marine Sciences, University of Maine, Walpole, ME, USA. -- Zulin Zhang is with The James Hutton Institute, Aberdeen, UK. -- Alexander S. Kolker is with Louisiana Universities Marine Consortium, Chauvin, LA, USA. -- Wei Wu is with the Department of Coastal Sciences, Gulf Coast Research Laboratory, The University of Southern Mississippi, Ocean Springs, MS, USA.Background: Coastal sediments in the northern Gulf of Mexico have a high potential of being contaminated by petroleum hydrocarbons, such as polycyclic aromatic hydrocarbons (PAHs), due to extensive petroleum exploration and transportation activities. In this study we evaluated the spatial distribution and contamination sources of PAHs, as well as the bioavailable fraction in the bulk PAH pool, in surface marsh and shelf sediments (top 5 cm) of the northern Gulf of Mexico. Results: PAH concentrations in this region ranged from 100 to 856 ng g−1, with the highest concentrations in Mississippi River mouth sediments followed by marsh sediments and then the lowest concentrations in shelf sediments. The PAH concentrations correlated positively with atomic C/N ratios of sedimentary organic matter (OM), suggesting that terrestrial OM preferentially sorbs PAHs relative to marine OM. PAHs with 2 rings were more abundant than those with 5–6 rings in continental shelf sediments, while the opposite was found in marsh sediments. This distribution pattern suggests different contamination sources between shelf and marsh sediments. Based on diagnostic ratios of PAH isomers and principal component analysis, shelf sediment PAHs were petrogenic and those from marsh sediments were pyrogenic. The proportions of bioavailable PAHs in total PAHs were low, ranging from 0.02% to 0.06%, with higher fractions found in marsh than shelf sediments. Conclusion: PAH distribution and composition differences between marsh and shelf sediments were influenced by grain size, contamination sources, and the types of organic matter associated with PAHs. Concentrations of PAHs in the study area were below effects low-range, suggesting a low risk to organisms and limited transfer of PAHs into food web. From the source analysis, PAHs in shelf sediments mainly originated from direct petroleum contamination, while those in marsh sediments were from combustion of fossil fuels.Marine [email protected]

Microplastics provide new microbial niches in aquatic environments

Microplastics in the biosphere are currently of great environmental concern because of their potential toxicity for aquatic biota and human health and association with pathogenic microbiota. Microplastics can occur in high abundance in all aquatic environments, including oceans, rivers and lakes. Recent findings have highlighted the role of microplastics as important vectors for microorganisms, which can form fully developed biofilms on this artificial substrate. Microplastics therefore provide new microbial niches in the aquatic environment, and the developing biofilms may significantly differ in microbial composition compared to natural free-living or particle-associated microbial populations in the surrounding water. In this article, we discuss the composition and ecological function of the microbial communities found in microplastic biofilms. The potential factors that influence the richness and diversity of such microbial microplastic communities are also evaluated. Microbe-microbe and microbe-substrate interactions in microplastic biofilms have been little studied and are not well understood. Multiomics tools together with morphological, physiological and biochemical analyses should be combined to provide a more comprehensive overview on the ecological role of microplastic biofilms. These new microbial niches have so far unknown consequences for microbial ecology and environmental processes in aquatic ecosystems. More knowledge is required on the microbial community composition of microplastic biofilms and their ecological functions in order to better evaluate consequences for the environment and animal health, including humans, especially since the worldwide abundance of microplastics is predicted to dramatically increase

Physiological responses and transcriptome analyses of upland rice following exposure to arsenite and arsenate

Acknowledgements This research was financially supported by the National Natural Science Foundation of China (No.41471274) and the Scottish Government’s Rural and Environment Science and Analytical Service Division (RESAS).Peer reviewedPostprin

Cubature Information SMC-PHD for Multi-Target Tracking

In multi-target tracking, the key problem lies in estimating the number and states of individual targets, in which the challenge is the time-varying multi-target numbers and states. Recently, several multi-target tracking approaches, based on the sequential Monte Carlo probability hypothesis density (SMC-PHD) filter, have been presented to solve such a problem. However, most of these approaches select the transition density as the importance sampling (IS) function, which is inefficient in a nonlinear scenario. To enhance the performance of the conventional SMC-PHD filter, we propose in this paper two approaches using the cubature information filter (CIF) for multi-target tracking. More specifically, we first apply the posterior intensity as the IS function. Then, we propose to utilize the CIF algorithm with a gating method to calculate the IS function, namely CISMC-PHD approach. Meanwhile, a fast implementation of the CISMC-PHD approach is proposed, which clusters the particles into several groups according to the Gaussian mixture components. With the constructed components, the IS function is approximated instead of particles. As a result, the computational complexity of the CISMC-PHD approach can be significantly reduced. The simulation results demonstrate the effectiveness of our approaches

Distribution behavior of superparamagnetic carbon nanotubes in an aqueous system

This study investigates the distribution behavior of superparamagnetic multiwalled carbon nanotubes (SPM-MWCNTs) in an aqueous system containing Lake Tai sediment. Specifically, the effects of dissolved organic matter (DOM) and sediment on SPM-MWCNTs under various conditions and the interaction forms between them were evaluated through a modified mathematical model and characterization. The results showed that DOM can stabilize SPM-MWCNTs by providing sterically and electrostatically stable surfaces, even under high sodium concentrations. The fitting accuracy of the Freundlich adsorption isotherm is higher than that of the Langmuir adsorption isotherm. Therefore, the adsorption of SPM-MWCNT on the sediment should proceed through a multiple, complex and heterogeneous adsorption mechanism. Characterization analyses indicated that DOM may serve as a bridge for the inorganic adsorption between SPM-MWCNTs and sediment. This study is the first to investigate the distribution behavior of magnetite coated carbon nanotubes (CNTs), which simplified the separation and quantification considerably. The findings of this study will serve as a valuable reference for future studies of magnetic CNTs

Hydraulic Features of Flow Through Local Non- Submerged Rigid Vegetation in the Y-shaped Confluence Channel

A laboratory measurement with acoustic Doppler velocimeter (ADV) was used to investigate the flow through a Y-shaped confluence channel partially covered with rigid vegetation on its inner bank. In this study, the flow velocities in cases with and without vegetation were measured by the ADV in a Y-shaped confluence channel. The results clearly showed that the existence of non-submerged rigid plants has changed the internal flow structure. The velocity in the non-vegetated area is greater than in the vegetated area. There is a large exchange of mass and momentum between the vegetated and non-vegetated areas. In addition, due to the presence of vegetation, the high-velocity area moved rapidly to the middle of the non-vegetated area in the vicinity of tributaries, and the secondary flow phenomenon disappeared. The presence of vegetation made the flow in non-vegetated areas more intense. The turbulent kinetic energy of the non-vegetated area was smaller than that of the vegetated area