Mezen Bay—a key area for understanding Weichselian glaciations in northern Russia

Sediment successions in coastal cliffs around Mezen Bay, southeastern White Sea, record an unusually detailed history of former glaciations, interstadial marine and fluvial events from the Weichselian. A regional glaciation model for the Weichselian is based on new data from the Mezen Bay area and previously published data from adjacent areas. Following the Mikulinian (Eemian) interglacial a shelf‐centred glaciation in the Kara Sea is reflected in proglacial conditions at 100–90 ka. A local ice‐cap over the Timan ridge existed between 75 and 65 ka. Renewed glaciation in the Kara Sea spread southwestwards around 60 ka only, interrupted by a marine inundation, before it advanced to its maximum position at about 55–50 ka. After a prolonged ice‐free period, the Scandinavian ice‐sheet invaded the area from the west and terminated east of Mezen Bay about 17 ka. The previously published evidence of a large ice‐dammed lake in the central Arkhangelsk region, Lake Komi, finds no support in this study. Copyright © 2003 John Wiley & Sons, Ltd.     

Low-cost volcano surveillance from space: case studies from Etna, Krafla, Cerro Negro, Fogo, Lascar and Erebus

 Satellite data offer a means of supplementing ground-based monitoring during volcanic eruptions, especially at times or locations where ground-based monitoring is difficult. Being directly and freely available several times a day, data from the advanced very high resolution radiometer (AVHRR) offers great potential for near real-time monitoring of all volcanoes across large (3000×3000 km) areas. Herein we describe techniques to detect and locate activity; estimate lava area, thermal flux, effusion rates and cumulative volume; and distinguish types of activity. Application is demonstrated using data for active lavas at Krafla, Etna, Fogo, Cerro Negro and Erebus; a pyroclastic flow at Lascar; and open vent systems at Etna and Stromboli. Automated near real-time analysis of AVHRR data could be achieved at existing, or cheap to install, receiving stations, offering a supplement to conventional monitoring methods. Received: 21 January 1997 / Accepted: 3 April 1997     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.     

Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

Expression of putative zinc-finger protein lcn61 gene in lymphocystis disease virus China （LCDV-cn） genome

An open reading frame (lcn61) of lymphocystis disease virus China (LCDV-cn), probably responsible for encoding putative zinc-finger proteins was amplified and inserted into pET24a (+) vector. Then it expressed in E. coli BL21 (DE3), and His-tag fusion protein of high yield was obtained. It was found that the fusion protein existed in E. coli mainly as inclusion bodies. The bioinformatics analysis indicates that LCN61 is C2H2 type zinc-finger protein containing four C2H2 zinc-finger motifs. This work provides a theory for functional research of lcn61 gene. Supported by High Technology Research and Development Program of China (863 Program, No. 2006AA100309)     

Models of travel demand with endogenous preference change and heterogeneous agents

In the literatures of regional science, urban economics, and urban development planning, a working assumption is that individuals respond to incentives and regulations, given their preferences. Models for planning and policy analyses are used to consider what might occur if the incentives or regulations were different. In these models, however, preferences are usually assumed to be given and stable, and agents are usually assumed to be homogeneous. This paper focuses on the implications of making preferences in models of policy implementation endogenously determined and time varying heterogeneous agents. We consider first the recent literature on intertemporal choice and preference change, which cuts across many disciplines, and more briefly the literature on norm-regarding behavior. We then elaborate a simple model of transportation demand—from a static to a dynamic orientation, from fixed and exogenously given preferences of strictly self-regarding agents to endogenously determined and policy-induced preferences of heterogeneous agents—and illustrate its characteristics with simple numerical examples.     

Application of saddlepoint approximation in reliability analysis of dynamic systems

The application of the saddlepoint approximation to reliability analysis of dynamic systems is investigated. The failure event in reliability problems is formulated as the exceedance of a single performance variable over a prescribed threshold level. The saddlepoint approximation technique provides a choice to estimate the cumulative distribution function (CDF) of the performance variable. The failure probability is obtained as the value of the complement CDF at a specif ied threshold. The method requires computing the saddlepoint from a simple algebraic equation that depends on the cumulant generating function (CGF) of the performance variable. A method for calculating the saddlepoint using random samples of the performance variable is presented. The applicable region of the saddlepoint approximation is discussed in detail. A 10-story shear building model with white noise excitation illustrates the accuracy and effi ciency of the proposed methodology.