Forecasting the Real US/DEM Exchange Rate: TAR vs. AR

The out-of-sample forecasting performances of two univariate time series presentations for the USD/DEM real exchange rate are compared using quarterly data for the period 1957Q1-1998Q4. The linear AR process is frequently fitted to real exchange rate series because it is sufficient for capturing the reported slow mean reversion in real exchange rates and it has some predictive ability for the long run. A simple nonlinear alternative, the threshold autoregressive (TAR) model, allows for the possibility that there is a band of slow or no convergence around the purchasing power parity level in the real exchange rate, due to transportation costs or other market frictions that create barriers to arbitrage. The TAR model is theoretically and empirically appealing, and it has been fitted to real exchange rates in many recent papers. However, the ultimate test of its usefulness is its out-of-sample forecasting accuracy. We compare the TAR model to its simple linear AR alternative in terms of out-of-sample forecast accuracy. Preliminary results using the RMSE criterion indicate that TAR forecasts are more sensitive to the estimation period and that they involve considerably more uncertainty at long horizons, as compared with the simple AR model.real exchange rate; TAR model; forecast accuracy

A measurement of complex viscosity with large amplitudes

In order to study the viscoelastic properties of polymer solutions and greases, a dynamic apparatus was built for making measurements of complex viscosity. Characteristic impedance was measured by a force transducer, an accelerometer and a phase meter. Large amplitudes to 0.5 inch can be obtained with this apparatus. The largest amplitude used was 1.27 x10⁻¹ cm. The frequency range was 30 Hz - 1500Hz. The lowest dynamic viscosity to be measured was 0.5 poise. In order to determine the capabilities of the instrument, complex viscosities of polymer solutions and greases were measured. The polymer solutions studied were polyisobutylene (PIB) L-80, PIB L-200, and polydimethyl siloxane (SR) 130. Comparisons of results for NLGI System A grease and Mobilgrease 24 showed that at the same level of dynamic viscosity the NLGI grease had twice the elastic response of Mobilgrease. For NLGI grease about 60% of the total energy input was dissipated under the experimental conditions. About 80% of the total energy input was dissipated for Mobilgrease 24. Comparing the shapes of curves for the steady shear viscosity vs. shear rate with the dynamic viscosity vs. frequency for FIB L-80 (3 g/dl and 5 g/dl), there was a trend toward agreement of η and η\u27 at vanishingly small values of γ and Ω. For 17% solution of NLGI grease and a 25% solution of Mobilgrease 24, η\u27 and η only have similar shapes. η\u27 and η can be shifted into coincidence along the γ - Ω axis with shift factor of 2. The dependence of complex viscosity on amplitude was investigated for the 5 g/dl PIB L-80 solution. Both η\u27 and η decrease with increasing amplitude when amplitude is beyond a limit; the η was more sensitive to amplitude. That means the dynamic storage modulus data are more critical than dynamic viscosity data in determining the limitation on amplitude for linear viscoelasticity. For instance, when shear wave length equaled 1.5 cm, the limitation on shear strain for linear viscoelasticity was 9.5% for the PIB L-80 solution --Abstract, pages ii-iii

Interaction between graphene and SiO2 surface

With first-principles DFT calculations, the interaction between graphene and SiO2 surface has been analyzed by constructing the different configurations based on {\alpha}-quartz and cristobalite structures. The single layer graphene can stay stably on SiO2 surface is explained based on the general consideration of configuration structures of SiO2 surface. It is also found that the oxygen defect in SiO2 surface can shift the Fermi level of graphene down which opens out the mechanism of hole-doping effect of graphene absorbed on SiO2 surface observed in experiments.Comment: 17 pages, 7 figure

Plant-mPLoc: A Top-Down Strategy to Augment the Power for Predicting Plant Protein Subcellular Localization

One of the fundamental goals in proteomics and cell biology is to identify the functions of proteins in various cellular organelles and pathways. Information of subcellular locations of proteins can provide useful insights for revealing their functions and understanding how they interact with each other in cellular network systems. Most of the existing methods in predicting plant protein subcellular localization can only cover three or four location sites, and none of them can be used to deal with multiplex plant proteins that can simultaneously exist at two, or move between, two or more different location sites. Actually, such multiplex proteins might have special biological functions worthy of particular notice. The present study was devoted to improve the existing plant protein subcellular location predictors from the aforementioned two aspects. A new predictor called “Plant-mPLoc” is developed by integrating the gene ontology information, functional domain information, and sequential evolutionary information through three different modes of pseudo amino acid composition. It can be used to identify plant proteins among the following 12 location sites: (1) cell membrane, (2) cell wall, (3) chloroplast, (4) cytoplasm, (5) endoplasmic reticulum, (6) extracellular, (7) Golgi apparatus, (8) mitochondrion, (9) nucleus, (10) peroxisome, (11) plastid, and (12) vacuole. Compared with the existing methods for predicting plant protein subcellular localization, the new predictor is much more powerful and flexible. Particularly, it also has the capacity to deal with multiple-location proteins, which is beyond the reach of any existing predictors specialized for identifying plant protein subcellular localization. As a user-friendly web-server, Plant-mPLoc is freely accessible at http://www.csbio.sjtu.edu.cn/bioinf/plant-multi/. Moreover, for the convenience of the vast majority of experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results. It is anticipated that the Plant-mPLoc predictor as presented in this paper will become a very useful tool in plant science as well as all the relevant areas