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Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Carbon fiber and its composites are widely used as structural materials due to their excellent mechanical properties. However, the chemical inertness of carbon fibers restricts their further application. In this paper, we implemented that the modification of carbon fiber via coating aramid nanofibers based on pre-treatment of carbon fiber surface by dopamine. At the same time, the effects of modified fibers on the properties of paper-based materials were investigated. It was found that pre-treatment of carbon fiber contributed to the cationization of the surface of carbon fiber, and further assisted the coating of aramid nanofiber by electrostatic adsorption. The surface morphology, chemical composition, hydrophilic property and mechanical properties of carbon fiber paper-based material were characterized by scanning electron microscopy(SEM), fourier transform infrared spectroscopy(FTIR), contact angle tester and tension tester. The results showed that the best coating effect on carbon fiber was achieved when the concentration of aramid nanofiber is 0.2% the best deposition effect when the 0.2% concentration of nano aramid fiber. The carbon fiber paper-based material modified by aramid nanofiber has good hydrophobic properties(CA=112.4°C) and mechanical properties(6.74 MPa). [ABSTRACT FROM AUTHOR]

In order to improve the quality of image enhancement, a dynamic cloud model encoding algorithm was proposed. First, Gaussian cloud generator was produced to model cloud droplets. Second, cloud model domain was encoded with diversity and importance, and image pixel gray value was mapped the cloud model of cloud droplets, including the space position and the decision variables and dynamic adjustment of control parameters. Last, image pixel background region and the target character were distinguished , the process was given. Experimental simulation shows that dynamic cloud model encoding enhancement is clear, time is less, index is better than other algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Progress in Modern Biomedicine is the property of Publishing House of Progress in Modern Biomedicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Shandong Medical Journal is the property of Shandong Medical Health Newspapers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Animal husbandry greenhouse gas emissions account for 18% of total greenhouse gas emissions of all human activities, and have become one of the most important contributors to global greenhouse gas emissions increase. Using life cycle assessment (LCA) method, animal husbandry carbon emissions in the 31 provinces, municipalities and autonomous regions of China from 2000 to 2014 have been comprehensively measured. Based on logarithmic mean Divisia index (LMDI) method, the changes of animal husbandry carbon emissions were decomposed into the contributions from 5 factors, including animal husbandry production efficiency, agricultural structure adjustment, agricultural productivity gains per agricultural labor, urbanization and total population growth. Using the data of animal husbandry carbon emissions measured by LCA, the driving effects of the 5 factors on animal husbandry carbon emissions change were measured from the spatial and temporal perspective. The results showed: 1) Total amount of animal husbandry carbon emissions in China increased from 137.423 million tons to 150.563 million tons from 2000 to 2014, and its average annual growth rate was 0.654%, of which the carbon emissions from gastrointestinal fermentation of livestock and manure management systems were the 2 key sources, accounting for 65.58%- 73.23% of the total amount of animal husbandry carbon emissions. 2) No matter from spatial or temporal perspective, animal husbandry production efficiency improvement was the most important factor to restrain the sustained growth of the animal husbandry carbon emissions; the increase of agricultural productivity gains per agricultural labor was the most important factor to promote the sustained growth of the animal husbandry carbon emissions, which was particularly outstanding in prairie pasturing areas and pasturing areas in major grain producing areas, however, the effect of the increase of agricultural productivity gains per agricultural labor on animal husbandry carbon emission growth was limited in developed areas. Population growth was another important factor to promote the growth of the animal husbandry carbon emissions, especially to the developed areas with massive population influx and the ethnic minority areas in most western part of China. 3) The increase of urbanization level ranked the second to restrain animal husbandry carbon emissions from 2000 to 2014, while the effect of agricultural structure adjustment on animal husbandry carbon emissions changed from positive to negative, and this characteristic was particularly obvious in eastern-central China with higher animal husbandry efficiency. [ABSTRACT FROM AUTHOR]

The fluctuation of coal-bed methane source parameters in coal mine is very volatile. In order to solve the negative influence of this fluctuation for coal-bed methane liquefaction device, relying on cryogenic liquefaction pilot plant for low concentration coal-bed methane, using the running test of cold box system, this paper theoretically studied the effects in the variation of raw material gas flux and methane concentration to device performance,noting that the recovery rate of methane in LNG product is more sensitive to the raw material gas flux and methane concentration, but the change of raw material gas parameters has little effect on the purity of LNG product. In the design, for the adaptability to the change of raw material gas source,the following measures should be taken into account to ensure the normal operation of the liquefaction device：the refrigerant leakage should be minimized in a mixed refrigerant cycle system；the mixed refrigerant filling system should be perfected to improve the degree of automation and designers should reduce the correlation between the top and bottom temperature regulation of distillation tower. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Water Science / Shuikexue Jinzhan is the property of Editorial Board of Advances in Water Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objectives] The identification method of paddy rice on a regional scale was investigated using the Chinese time series HJ-CCD images with shorter revisiting period, and the spatial-temporal planting characteristics were identified in Yuanjiang City, Hunan Province. [Methods] Based on the particular feature of transplanting and heading stages of rice compared with other crops, the spectral features derived from time series NDVI (normalized difference vegetation index) and reflectance images of early rice,middle rice and late rice in 2010 were firstly analyzed. Then,the coarse rice maps were obtained using the thresholds of NDVI difference images of heading and transplanting stages. Finally, the maps and a total of 18 vegetation indices of two growth stages calculated from the four original bands were layerstacked and input into the See 5.0 decision tree software to form an optimal classification rule set by training samples. Consequently,the fields of three type paddy rice were identified by the NLCD (national land cover dataset) mapping toolset. [Results] The spatial distribution and planting acreage of early rice and late rice were similar and they were primarily planted in the west northern plains of Dongting Lake in Yuanjiang City, while the acreage of middle rice was less and located in the northern part. The acreage of three type rice was 388.7, 6.3 and 358.3 khm2, where the relative errors were 12.1%, 16.7%, and -0.8%, respectively depending on the statistical yearbook. On the other hand, the overall classification accuracy reached 86%, 75% and 80% by referring to the GPS sample points. [Conclusions] The more precise paddy rice pixels can be obtained by time series remote sensing imagery of transplanting and heading stages of rice, which can provide good data support for further analyzing the planting features. [ABSTRACT FROM AUTHOR]

Copyright of Shandong Medical Journal is the property of Shandong Medical Health Newspapers and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)