LOLAS: an optical turbulence profiler in the atmospheric boundary layer with extreme altitude resolution

We report the development and first results of an instrument called Low Layer SCIDAR (Scintillation Detection and Ranging) (LOLAS) which is aimed at the measurement of optical-turbulence profiles in the atmospheric boundary layer with high altitude resolution. The method is based on the Generalized SCIDAR (GS) concept, but unlike the GS instruments which need a 1-m or larger telescope, LOLAS is implemented on a dedicated 40-cm telescope, making it an independent instrument. The system is designed for widely separated double-star targets, which enables the high altitude resolution. Using a 200-arcsec-separation double star, we have obtained turbulence profiles with unprecedented 12-m resolution. The system incorporates necessary novel algorithms for autoguiding, autofocus and image stabilization. The results presented here were obtained at Mauna Kea Observatory. They show LOLAS capabilities but cannot be considered as representative of the site. A forthcoming paper will be devoted to the site characterization. The instrument was built as part of the Ground Layer Turbulence Monitoring Campaign on Mauna Kea for Gemini Observatory.     

The Durham/ESO SLODAR optical turbulence profiler

An instrument for monitoring of the vertical profile of atmospheric optical turbulence strength, employing the Slope Detection and Ranging (SLODAR) double star technique applied to a small telescope, has been developed by Durham University and the European South Observatory. The system has been deployed at the Cerro Paranal observatory in Chile for statistical characterization of the site. The instrument is configured to sample the turbulence at altitudes below 1.5 km with a vertical resolution of approximately 170 m. The system also functions as a general-purpose seeing monitor, measuring the integrated optical turbulence strength for the whole atmosphere, and hence the seeing width. We give technical details of the prototype and present data to characterize its performance. Comparisons with contemporaneous measurements from a differential image motion monitor (DIMM) and a multi-aperture scintillation sensor (MASS) are discussed. Statistical results for the optical turbulence profile at the Paranal site are presented. We find that, in the median case, 49 per cent of the total optical turbulence strength is associated with the surface layer (below 100 m), 35 per cent with the 'free atmosphere' (above 1500 m) and 16 per cent with the intermediate altitudes (100–1500 m).     

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基于应力腐蚀和腐蚀疲劳的焊缝磁记忆信号分析

为了研究不同腐蚀条件下的焊缝磁记忆特征信号,对20号钢板状焊缝试件进行残余应力腐蚀、35kN恒拉伸应力腐蚀和35kN静载、25kN动载拉拉腐蚀疲劳对比实验,分析焊缝正、反面磁记忆信号的变化规律,获得焊缝腐蚀发展进程中应力腐蚀与腐蚀疲劳各自对应的磁记忆特征信号.结果表明:在应力腐蚀状态下,不同拉伸载荷对应的磁记忆信号特征不同,35kN恒拉伸应力腐蚀与残余应力腐蚀相比,焊缝区磁记忆信号峰峰值及其梯度更大,磁记忆曲线分布的分散度更大;35kN静载、25kN动载拉拉腐蚀疲劳与35kN恒拉伸应力腐蚀相比,焊缝区磁记忆曲线上下波动多,过零点次数多,磁记忆曲线分布的分散度小.这为磁记忆技术在焊缝工程检测的定性与定量分析提供基础数据.     

基于参数空间分布的海洋生态系统模拟

在模拟大尺度海洋生态系统时,由于子区域的生态系统有着各自的特征,导致参数值在空间上存在差异,因此参数在整个研究区域取常数的做法必须改进.基于此,使用气候模式FOAM的气侯态背景场驱动一个简单的三维海洋生态系统模型,并引入参数的空间分布,在全球尺度上通过伴随方法同化SeaWiFS叶绿素资料.引入参数空间分布后,同化结果得到很大改进:浮游植物表层生物量(氮)的平均差从0.155 3减小至0.060 6 mmol·m-3,下降了60.9%,有效地降低了模拟值与观测值在空间上的差异;浮游植物表层生物量平均值也从0.103 1上升至0.125 2 mmol·m-3,更接近SeaWiFS观测.实验结果表明通过引入参数的空间分布来改进海洋生态系统的模拟是可行的.     

Antibiotic resistance of bacteria isolated from shrimp hatcheries and cultural ponds on Donghai Island, China

The resistance of bacteria to 12 different antibiotics was investigated in shrimp farms on Donghai Island, China. Antibiotic-resistant bacteria were found to be widespread in shrimp farms, indicating a high environmental risk. Further, significant differences were found in bacterial strains among farms (ANOVA, p < 0.05), showing resistance to antibiotics such as ampicillin, trimethoprim, compound sinomi, tetracycline, chloramphenicol and cefazolin. No significant differences in antibiotic resistance were found among 6 hatcheries evaluated in this study (ANOVA, p > 0.05), between exalted and traditional shrimp ponds (ANOVA, p > 0.05), and between cultural ponds and corresponding control water source sites (T-test, p > 0.05). In cultural ponds, no significant difference in bacterial resistance to antibiotics was found between water and sediment (T-test, p > 0.05), and antibiotic resistance of bacteria from water showed a significant positive correlation with that from sediment (p < 0.05). Therefore, our study indicates that bacterial multiple antibiotic resistance (MAR) is more widespread in shrimp hatcheries than ponds.     

Conditional nonlinear optimal perturbation: Applications to stability,sensitivity, and predictability

Conditional nonlinear optimal perturbation (CNOP) is a nonlinear generalization of linear singular vector (LSV) and features the largest nonlinear evolution at prediction time for the initial perturbations in a given constraint. It was proposed initially for predicting the limitation of predictability of weather or climate. Then CNOP has been applied to the studies of the problems related to predictability for weather and climate. In this paper, we focus on reviewing the recent advances of CNOP’s applications, which involves the ones of CNOP in problems of ENSO amplitude asymmetry, block onset, and the sensitivity analysis of ecosystem and ocean’s circulations, etc. Especially, CNOP has been primarily used to construct the initial perturbation fields of ensemble forecasting, and to determine the sensitive area of target observation for precipitations. These works extend CNOP’s applications to investigating the nonlinear dynamical behaviors of atmospheric or oceanic systems, even a coupled system, and studying the problem of the transition between the equilibrium states. These contributions not only attack the particular physical problems, but also show the superiority of CNOP to LSV in revealing the effect of nonlinear physical processes. Consequently, CNOP represents the optimal precursors for a weather or climate event; in predictability studies, CNOP stands for the initial error that has the largest negative effect on prediction; and in sensitivity analysis, CNOP is the most unstable (sensitive) mode. In multi-equilibrium state regime, CNOP is the initial perturbation that induces the transition between equilibriums most probably. Furthermore, CNOP has been used to construct ensemble perturbation fields in ensemble forecast studies and to identify sensitive area of target observation. CNOP theory has become more and more substantial. It is expected that CNOP also serves to improve the predictability of the realistic predictions for weather and climate events plays an increasingly important role in exploring the nonlinear dynamics of atmospheric, oceanic and coupled atmosphere-ocean system. Supported by National Basic Research Program of China (Grant Nos. 2006CB403606, 2007CB411800), National Natural Science Foundation of China (Grant Nos. 40830955, 40675030, 40505013), Institute of Atmospheric Physics, Chinese Academy of Sciences (Grant No. IAP07202), and LASG State Key Laboratory Special Fund     

Statistical diagnosis and gross error test for semiparametric linear model

This paper systematically studies the statistical diagnosis and hypothesis testing for the semiparametric linear regression model according to the theories and methods of the statistical diagnosis and hypothesis testing for parametric regression model. Several diagnostic measures and the methods for gross error testing are derived. Especially, the global and local influence analysis of the gross error on the parameter X and the nonparameter s are discussed in detail; at the same time, the paper proves that the data point deletion model is equivalent to the mean shift model for the semiparametric regression model. Finally, with one simulative computing example, some helpful conclusions are drawn.     

纵观近代岩矿测试分析技术

本文就近代岩矿测试分析技术作了较为全面的介绍。文章指出，地矿部从８０年代起，由于引进了大批现代先进仪器设备，使岩矿测试分析技术出现了崭新面貌，形成为多学科相结合的新格局，从而促进地质科学在理论上和实践上均取得显著进步，在某些学科领域已发生了根本性变化，并为地质或其它市场提供了大量信息，为促进科技成果转化为生产力作出了巨大贡献。纵观近代岩矿测试分析技术，文章提出了多机联用、整体分析和拓宽测试分析领域的建议，以更好地为祖国经济主战场服务。