Ecology of bottom ice algae: II. Dynamics, distributions and productivity

Spring blooms of bottom ice algae are a common feature of landfast congelation ice in polar regions. Because ice algae are usually associated with a substrate, their population dynamics can be followed with considerable confidence. Although ice algal dynamics are closely related to irradiance, their dynamics and distributions are influenced by other abiotic and biotic factors. Ice algal abundance varies horizontally over all scales examined. Factors such as grazing and nutrient availability may contribute to local and geographic differences. Loss terms for most sea ice assemblages are largely unquantified. Ice algal biomass is most concentrated near the ice-water interface in spring.Environmental factors affecting ice algal abundance and productivity are considered here, emphasizing recent results from several well-studied sites. Biomass accumulation, growth rates and productivity have been documented for spring blooms of bottom interstitial and sub-ice assemblages. On an areal basis biomass accumulation in bottom ice assemblages can be comparable with planktonic systems. At low ambient temperatures and irradiances average specific growth rates (≤ 0.25 d⁻¹) and production rates (≤ 1.0 mg C mg Chl⁻¹ h⁻¹) for ice algae are low. Current methods of measuring productivity are compared. Results are consistently low but variable with little systematic difference among them. At present, apparent differences in productivity between bottom ice assemblages in the Arctic and Antarctic, or among different antarctic assemblages, are so confounded by methodological and other sources of variability that no firm differences can be detected.     

Airline industry deregulation and changes in systematic risk

Deregulation of U.S. Airline Industry may have lowered systematic risk because pricing freedom and route flexibility improved airline management reaction to various economic conditions. Reduced systematic risk offers lower cost of equity capital for the industry as a whole as well as for individual carriers. Previous research has had mixed results in identifying a relationship between deregulation and airline industry cost of capital. This study plots airline industry Beta coefficients across the years 1963 to 1987 and clears up previously conflicting research findings. Beta coefficients had been falling since the fuel crisis of 1974 and continued to fall through 1980. Fluctuations since deregulation have been relatively minor and systematic risk has leveled off at a significantly lower value than before deregulation. Studies which concentrate on the fluctuation in Beta since 1978 are dependent on the exact time period of analysis, and their conclusions that deregulation raised or lowered systematic risk are likewise suspect. A broader view of systematic risk changes in the deregulatory era shows airline Betas peaking from 1971 to 1973 and a gradual decrease as deregulation was being discussed, implemented, and legally mandated. This gradual decline from 1974 to 1980 may be attributed to such factors as fuel prices, interest rates, general inflation as well as deregulation. In any case systematic risk of the U.S. Airline industry has been lower since deregulation than in decades before.     

Creative nodes,logistical networks,and the future of the metropolis

A paradigmatic shift away from traditional quantitative methods towards qualitative dynamic analysis is proposed in order to fully comprehend the future of the metropolis. Over the last millennium the great structural changes of production, location, trade, culture and institutions have most likely been triggered by slow but steady changes to those logistical networks which are responsible for the movement of key factors of production. Nonlinear dynamic methods such as catastrophe theory and synergetics can help to provide the necessary analytical insights. Creativity and accessibility to logistical networks are portrayed as important catalysts of qualitative change. requests for offprints     

基于氯离子分布的氯离子渗透参数计算的新方法

根据混凝土中氯离子的分布对氯离子侵入性能进行评价时,混凝土粉末样品的采集,氯离子含量的测试和表达方式,均可对评价结果产生影响。在干湿循环条件下,以理论上的表面氯离子浓度为主要评价参数对氯离子的渗透性能进行评价的方法不尽合理。通过对暴露26年后的青岛北海船厂码头中大量的混凝土芯样中氯离子分布的分析和计算,结合其它文献中氯离子分布的数据,提出了以扩散区与对流区界面为扩散表面,以界面处的氯离子浓度为扩散表面浓度,评价氯离子侵入性能和进行寿命预测的方法。     

小鼠10号染色体上致聋突变基因hml的精确定位(英文)

目的　定位小鼠致聋基因 ,识别决定其性状的有关突变 ,为人类耳聋基因研究提供动物模型。方法　利用全基因组扫描来定位名为hml可致小鼠听力丧失突变基因。结果　①hml基因定位在小鼠 10号染色体上 ,距中心粒约4 3cM处。根据已知的鼠 人同源同线性特点 ,提示人的同源基因位于 12 q2 2 -q2 4 ;②获得了 2 5个多态性微卫星标记 ,通过高分辨的小鼠图谱将 3个已知人类基因进行了正确排列 ,并将hml侯选基因限定在一个 5 0 0kb的区域内。     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

A fast implementation of MPC-based motion cueing algorithms for mid-size road vehicle motion simulators

The use of dynamic driving simulators is constantly increasing in the automotive community, with applications ranging from vehicle development to rehab and driver training. The effectiveness of such devices is related to their capabilities of well reproducing the driving sensations, hence it is crucial that the motion control strategies generate both realistic and feasible inputs to the platform. Such strategies are called motion cueing algorithms (MCAs). In recent years several MCAs based on model predictive control (MPC) techniques have been proposed. The main drawback associated with the use of MPC is its computational burden, that may limit their application to high performance dynamic simulators. In the paper, a fast, real-time implementation of an MPC-based MCA for 9 DOF, high performance platform is proposed. Effectiveness of the approach in managing the available working area is illustrated by presenting experimental results from an implementation on a real device with a 200?Hz control frequency.     

EXPRESSION CLONING OF A PROTECTIVE LEISHMANIA ANTIGEN

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