一种从航天器VLBI观测记录中获取航天器速度信息的方法

介绍一种对航天器的VLBI原始电压观测记录中提取多普勒频移量的方法，并用于对lunarprospector的较左VLBI观测记录的分析中，同时得到航天器的VLBI和多普勒观测数据，有利于对航天器空间位置和速度信息的同时获取。     

Spin Effects in Collisions of Electrons with Atoms and Molecules

IntroductionThedynamicsofelectron-atomandelectron-moleculecollisionshasbeenthefocusofmuchinterestinthepastbecauseofitsrelevanceingasdischargesandplasmas,includinggaslasers,orastrophysicalproblemsofpracticalinterest.Avarietyofinvestigationshavebeenperformedtostudysuchprocessesinsomedetail.Moresophisticatedexperimentalmethodsincludepolarization-correlationmeasurementstoobtaingeneralizedSTUparameters,spinasymmetrieswithpolarizedtargets(alsosuperelasticscatteringfromlaserexcitedtarget),opticalpar…     

Redundant and unique roles of coronin proteins in <Emphasis Type="Italic">Dictyostelium</Emphasis>

Dictyostelium discoideum harbors a short (CRN12) and a long coronin (CRN7) composed of one and two beta-propellers, respectively. They are primarily present in the cell cortex and cells lacking CRN12 (corA ⁻) or CRN7 (corB ⁻) have defects in actin driven processes. We compared the characteristics of a mutant cell line (corA ⁻ /corB ⁻) lacking CRN12 and CRN7 with the single mutants focusing on cytokinesis, phagocytosis, chemotaxis and development. Cytokinesis, uptake of small particles, and developmental defects were not enhanced in the corA ⁻ /corB ⁻ strain as compared to the single mutants, whereas motility and phagocytosis of yeast particles were more severely impaired. It appears that although both proteins affect the same processes they do not act in a redundant manner. Rather, they often act antagonistically, which is in accordance with their proposed roles in the actin cytoskeleton where CRN12 acts in actin disassembly whereas CRN7 stabilizes actin filaments and protects them from disassembly.     

Neuere Anschauungen über die Meteorologie und Klimatologie des Föhns

Summary The results of new researches about the föhn in the Swiss Alps in connection with the theory ofH. von Ficker show that the energy of the cyclonic föhn has two sources: the pressure gradient and the baroclinic field. This is caused by the isobaric differences of temperature between the Alps and the free atmosphere in the lee. The result is a current with a descending component in the lee. At the beginning, the descent of the föhn is due to the outstreaming of the cold air on the ground. In its further development the energy of the föhn increases so much as to sweep the cold air off the valleys.The development of föhn in an anticyclonic system ist also explained. Furthermore the two kinds of föhn are discussed in regard to their climatological influences.

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Physikalisch-Meteorologisches Observatorium Davos.     

Forecasting value‐at‐risk with a parsimonious portfolio spillover GARCH (PS‐GARCH) model

Accurate modelling of volatility (or risk) is important in finance, particularly as it relates to the modelling and forecasting of value‐at‐risk (VaR) thresholds. As financial applications typically deal with a portfolio of assets and risk, there are several multivariate GARCH models which specify the risk of one asset as depending on its own past as well as the past behaviour of other assets. Multivariate effects, whereby the risk of a given asset depends on the previous risk of any other asset, are termed spillover effects. In this paper we analyse the importance of considering spillover effects when forecasting financial volatility. The forecasting performance of the VARMA‐GARCH model of Ling and McAleer (2003), which includes spillover effects from all assets, the CCC model of Bollerslev (1990), which includes no spillovers, and a new Portfolio Spillover GARCH (PS‐GARCH) model, which accommodates aggregate spillovers parsimoniously and hence avoids the so‐called curse of dimensionality, are compared using a VaR example for a portfolio containing four international stock market indices. The empirical results suggest that spillover effects are statistically significant. However, the VaR threshold forecasts are generally found to be insensitive to the inclusion of spillover effects in any of the multivariate models considered. Copyright © 2008 John Wiley & Sons, Ltd.