Investigate the interaction between dark matter and dark energy

In this paper we investigate the interaction between dark matter and dark energy by considering two different interacting scenarios, i.e. the cases of constant interaction function and variable interaction function. By fitting the current observational data to constrain the interacting models, it is found that the interacting strength is non-vanishing, but weak for the case of constant interaction function, and the interaction is not obvious for the case of variable interaction function. In addition, for seeing the influence from interaction we also investigate the evolutions of interaction function, effective state parameter for dark energy and energy density of dark matter. At last some geometrical quantities in the interacting scenarios are discussed.Comment: 14 pages, 6 figure

Methyl mercury concentrations in seafood collected from Zhoushan Islands, Zhejiang, China, and their potential health risk for the fishing community

Seafood is an important exposure route for mercury, especially methyl mercury (MeHg). Therefore, we quantified MeHg concentrations in 69 species of seafood including fish, crustaceans and mollusks collected from Zhoushan Islands, China. MeHg concentrations ranged from 1. The daily dietary intake and hazard quotient for MeHg were calculated to estimate exposure and health risk through seafood consumption by local inhabitants. The calculated HQ was lower than 1, thus indicating that the exposure was below the risk threshold of related chronic diseases. However, higher MeHg concentrations in fish species such as Scoliodon sorrakowah and Auxis thazard are concerning and may pose health risk through continuous consumption by local inhabitants.China Spark Program (2015GA700094); Medical Health Science Foundation Program of the Health Department of Zhejiang Province (2020RC137); Science and technology Program of Zhoushan City (2017C32089); Medical Health Science Foundation Program of the Health Department of Zhoushan City (2018G02)) and the Chinese Academy of Sciences Fellowships under the Chinese Academy of Sciences President's International Fellowship for Visiting Scientists (2018VCC0002).info:eu-repo/semantics/publishedVersio

Exposure Test on Two Surface Anticorrosion Technologies for Marine Concrete Structure

This paper is to study the effect of surface coating and silane hydrophobic agents for high performance concrete durability in a marine environment of tidal zone and splash zone by exposure test in JiaoZhou Bay. The results indicated that surface coating had good protection and coating quality after a 5-year period and the adhesive strength with concrete surface was more than 2.5 MPa. Surface coating can effectively improve chloride ion penetration resistance of concrete structures. The substrate concrete of specimen treated with silane had some chloride ion penetration, but compared with untreated concrete, chloride content of silane-treated concrete within 10 mm depth from surface was reduced by 43 and 67% in the tidal zone and the splash zone, respectively. Two surface anticorrosion measures technologies were effective in reducing the chloride erosion and improved the service life of marine concrete structure

Strengthening of Rural Bridges using Rapid-Installation FRP Technology: Route 63 Bridge No. H356, Phelps County

This report presents the use of externally bonded fiber reinforced polymers (FRP) laminates for the flexural strengthening of a concrete bridge. The bridge selected for this project is a two-span simply supported reinforced concrete slab with no transverse steel reinforcement located in Phelps County, MO. The original construction combined with the presence of very rigid parapets caused the formation of a 1-inch wide longitudinal crack, which resulted in the slab to behave as two separate elements. The structural behavior was verified using a finite element model (FEM) of the bridge. The bridge analysis was performed for maximum loads determined in accordance with AASHTO 4th edition. The strengthening scheme was designed in compliance with the ACI 440.2R-08 design guide for externally bonded FRP materials, to avoid further cracking and such that the transverse flexural capacity be higher than the cracking moment. The FRP strengthening technique was rapidly implemented. After the strengthening, a load test was performed to validate the bridge model and evaluate the structural behavior according to the AASHTO specifications. The bridge deck was retrofitted after the longitudinal crack was injected with epoxy to allow continuity in the cross section

Accurate Single Stage Detector Using Recurrent Rolling Convolution

Most of the recent successful methods in accurate object detection and localization used some variants of R-CNN style two stage Convolutional Neural Networks (CNN) where plausible regions were proposed in the first stage then followed by a second stage for decision refinement. Despite the simplicity of training and the efficiency in deployment, the single stage detection methods have not been as competitive when evaluated in benchmarks consider mAP for high IoU thresholds. In this paper, we proposed a novel single stage end-to-end trainable object detection network to overcome this limitation. We achieved this by introducing Recurrent Rolling Convolution (RRC) architecture over multi-scale feature maps to construct object classifiers and bounding box regressors which are "deep in context". We evaluated our method in the challenging KITTI dataset which measures methods under IoU threshold of 0.7. We showed that with RRC, a single reduced VGG-16 based model already significantly outperformed all the previously published results. At the time this paper was written our models ranked the first in KITTI car detection (the hard level), the first in cyclist detection and the second in pedestrian detection. These results were not reached by the previous single stage methods. The code is publicly available.Comment: CVPR 201

Protein Coding Sequence Identification by Simultaneously Characterizing the Periodic and Random Features of DNA Sequences

Most codon indices used today are based on highly biased nonrandom usage of codons in coding regions. The background of a coding or noncoding DNA sequence, however, is fairly random, and can be characterized as a random fractal. When a gene-finding algorithm incorporates multiple sources of information about coding regions, it becomes more successful. It is thus highly desirable to develop new and efficient codon indices by simultaneously characterizing the fractal and periodic features of a DNA sequence. In this paper, we describe a novel way of achieving this goal. The efficiency of the new codon index is evaluated by studying all of the 16 yeast chromosomes. In particular, we show that the method automatically and correctly identifies which of the three reading frames is the one that contains a gene

Logging identification of the Longmaxi mud shale reservoir in the Jiaoshiba area, Sichuan Basin

AbstractCompared with conventional gas reservoirs, shale gas reservoirs are not sensitive to petrophysical properties, making it much difficult to identify this kind of reservoirs with well logging technologies. Therefore, through a comparison of the logging curves of the Lower Silurian Longmaxi marine shale in the Jiaoshiba area, Sichuan Basin, it is found that the mud shale on conventional log curves generally features high gamma ray, high uranium, low thorium, low kalium, relative high resistivity, high interval transit time, low neutron, low density and low photoelectric absorption cross section index, while on elements logging curves, it features an increase of silicon content and a decrease of aluminum and iron content. Based on the logging response characteristics of mud shale, the logging curves most sensitive to shale, gamma ray, neutron and density logging were selected and overlaid to identify mud shale effectively. On the basis of qualitative identification, the density logging value can identify the non-organic-rich mud shale from organic-rich mud shale, because the former has a density of 2.61–2.70 g/cm3, while the latter has a density of less than 2.61 g/cm3. The identification results agree well with the results of field gas content test, TOC experiment, and gas logging, so this study can provide reference for the logging interpretation