22 resultados para Intelligent Environments


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Aims: To assess the diversity of antibiotic-resistant bacteria and their resistance genes in typical maricultural environments. Methods nand Results: Multidrug-resistant bacteria and resistance genes from a mariculture farm of China were analysed via cultivation and polymerase chain reaction (PCR) methods. Oxytetracycline (OTC)-resistant bacteria were abundant in both abalone and turbot rearing waters, accounting for 3.7% and 9.9% of the culturable microbes. Multidrug resistance was common, with simultaneous resistance to OTC, chloramphenicol and ampicillin the most common resistance phenotype. 16S rDNA sequence analyses indicate that the typical resistant isolates belonged to marine Vibrio, Pseudoalteromonas or Alteromonas species, with resistance most common in Vibrio splendidus isolates. For OTC resistance, tet(A), tet(B) and tet(M) genes were detected in some multidrug-resistant isolates, with tet(D) being the most common molecular determinant. For chloramphenicol resistance, cat II was common, and floR was also detected, especially in marine Pseudoalteromonas strains. Conclusions: There is the risk of multidrug-resistant bacteria contamination in mariculture environments and marine Vibrio and Pseudoalteromonas species serve as reservoirs of specific antibiotic resistance determinants. Significance and Impact of the Study: This paper and similar findings from Korea and Japan indicate the potential for widespread distribution of antibiotic resistance genes in mariculture environments from the East Asian region of the world.

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Based on analyses of more than 600 surface sediment samples together with large amounts of previous sedimentologic and hydrologic data, the characteristics of modern sedimentary environments and dynamic depositional systems in the southern Yellow Sea (SYS) are expounded, and the controversial formation mechanism of muddy sediments is also discussed. The southern Yellow Sea shelf can be divided into low-energy sedimentary environment and high-energy sedimentary environment; the low-energy sedimentary environment can be further divided into cyclonic and anticyclonic ones, and the high-energy environment is subdivided into high-energy depositional and eroded environments. In the shelf low-energy environments, there developed muddy depositional system. In the central part of the southern Yellow Sea, there deposited the cold eddy sediments under the actions of a meso-scale cyclonic eddy (cold eddy), and in the southeast of the southern Yellow Sea, an anticyclonic eddy muddy depositional system (warm eddy sediment) was formed. These two types of sediments showed evident differences in grain size, sedimentation rate, sediment thickness and mineralogical characteristics. The high-energy environments were covered with sandy sediments on seabed; they appeared mainly in the west, south and northeast of the southern Yellow Sea. In the high-energy eroded environment, large amounts of sandstone gravels were distributed on seabed. In the high-energy depositional environment, the originally deposited fine materials (including clay and fine silt) were gradually re-suspended and then transported to a low-energy area to deposit again. In this paper, the sedimentation model of cyclonic and anticyclonic types of muddy sediments is established, and a systematic interpretation for the formation cause of muddy depositional systems in the southern Yellow Sea is given.

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In this paper, the spatial distribution and source of the PCBs in surface sediments of the Southern Yellow Sea (SYS) and influencing factors, such as the sediment characteristics (components, relative proportions and total organic carbon contents), and hydrodynamic conditions were analyzed. PCB concentrations in the surface sediments ranged from 518-5848 pg/g, with average values of 1715 pg/g decreasing sharply compared to last year. In the study area, the PCB pollution level in the middle area was the highest, followed by that of the east coast and the west coast, respectively. Although the PCB level in the coastal areas was lower than that in the middle areas, it was proven in our study that the Yellow Sea obtained PCBs by virtue of river inputs. There was a positive and pertinent correlation between the clay proportion and PCB concentrations, and the increase of the PCB concentrations was directly proportional to the increase of TOC contents, with r = 0.61, but it was contrary to the sediment grain size. Consequently, the factors controlling PCB distribution had direct or indirect relationships with sediment grain size; moreover, the hydrodynamic conditions determined the sediment components and grain size. In conclusion, hydrodynamic conditions of the Yellow Sea were the most important influencing factors effecting the distribution of PCBs in the surface sediments of the SYS. (C) 2007 Elsevier Ltd. All rights reserved.

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本文基于栅格地图和滚动视窗的控制方法 ,提出了一种提取机器人局部障碍物群环境特征的数据融合新方法 .该方法在多个级别对原始数据进行不同程度的抽象和压缩 ,减少机器人内部模块之间或机器人之间、机器人与控制中心进行通讯的数据量 ,提高系统的动态性能 .同时 ,该方法对复杂环境具有良好的自适应性和实时性 .本文分别列举了仿真实验和物理实验结果 ,表明了机器人采用障碍物群的环境特征提取方法可以成功地完成躲避障碍物和路径规划的任务

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提出了一种新的最优模糊PID控制器,它由两部分组成,即在线模糊推理机构和带有不完全微分的常规PID控制器,在模糊推理机构中,引入了三个可调节因子xp,xi和xd,其作用是进一步修改和优化模糊推理的结果,以使控制器对一个给定对象具有最优的控制效果,可调节因子的最优值采用ITAE准则及Nelder和Mead提出的柔性多面体最优搜索算法加以确定,这种PID控制器被用来控制由作者设计的智能人工腿中的一个直流电机,仿真结果表明该控制器的设计是非常有效的,它可被用于控制各种不同的对象和过程。