A general additive distance with time-reversibility and rate variation among nucleotide sites.

As additivity is a very useful property for a distance measure, a general additive distance is proposed under the stationary time-reversible (SR) model of nucleotide substitution or, more generally, under the stationary, time-reversible, and rate variable (SRV) model, which allows rate variation among nucleotide sites. A method for estimating the mean distance and the sampling variance is developed. In addition, a method is developed for estimating the variance-covariance matrix of distances, which is useful for the statistical test of phylogenies and molecular clocks. Computer simulation shows (i) if the sequences are longer than, say, 1000 bp, the SR method is preferable to simpler methods; (ii) the SR method is robust against deviations from time-reversibility; (iii) when the rate varies among sites, the SRV method is much better than the SR method because the distance is seriously underestimated by the SR method; and (iv) our method for estimating the sampling variance is accurate for sequences longer than 500 bp. Finally, a test is constructed for testing whether DNA evolution follows a general Markovian model.

Climate simulation for 125 kyr BP with a coupled ocean-atmosphere general circulation model

The ECHAM-1 T21/LSG coupled ocean-atmosphere general circulation model (GCM) is used to simulate climatic conditions at the last interglacial maximum (Eemian. 125 kyr BP). The results reflect thc expected surface temperature changes (with respect to the control run) due to the amplification (reduction) of the seasonal cycle of insolation in the Northern (Southern) Hemisphere. A number of simulated features agree with previous results from atmospheric GCM simulations e.g. intensified summer southwest monsoons) except in the Northern Hemisphere poleward of 30 degrees N. where dynamical feedback, in the North Atlantic and North Pacific increase zonal temperatures about 1 degrees C above what would be predicted from simple energy balance considerations. As this is the same area where most of the terrestrial geological data originate, this result suggests that previous estimates of Eemian global average temperature might have been biased by sample distribution. This conclusion is supported by the fact that the estimated global temperature increase of only 0.3 degrees C greater than the control run ha, been previously shown to be consistent a with CLIMAP sea surface temperature estimates. Although the Northern Hemisphere summer monsoon is intensified. globally averaged precipitation over land is within about 1% of the present, contravening some geological inferences bur not the deep-sea delta(13)C estimates of terrestrial carbon storage changes. Winter circulation changes in the northern Arabian Sea. driven by strong cooling on land, are as large as summer circulation changes that are the usual focus of interest, suggesting that interpreting variations in the Arabian Sea. sedimentary record solely in terms of the summer monsoon response could sometimes lead to errors. A small monsoonal response over northern South America suggests that interglacial paleotrends in this region were not just due to El Nino variations.

Combinational circuit synthesis with time and component bo[u]nds /

Bibliography: p. 45.

Short-time stability in linear time-varying systems.

"SFOSR 748."

Has the earth's crust changed with time? : rare earth abundances in ancient sediments /

"May 1967."

Poetical vagaries; containing An ode to We, a hackney'd critick;Low ambition; or, The life and death of Mr. Daw; A reckoning with time; The lady of the wreck; or, Castle Blarneygig; Two persons; or, The tale of a shirt. And Vagaries vindicated; a poem, address'd to the reviewers;

Mode of access: Internet.

Development of Cookstove Emissions and Performance Testing Suite with Time-resolved Particulate Matter Analysis and Excess Air Estimation

Thesis (Master's)--University of Washington, 2016-06

Modelling trickle irrigation: Comparison of analytical and numerical models for estimation of wetting front position with time

Irrigation practices that are profligate in their use of water have come under closer scrutiny by water managers and the public. Trickle irrigation has the propensity to increase water use efficiency but only if the system is designed to meet the soil and plant conditions. Recently we have provided a software tool, WetUp (http://www.clw.csiro.au/products/wetup/), to calculate the wetting patterns from trickle irrigation emitters. WetUp uses an analytical solution to calculate the wetted perimeter for both buried and surface emitters. This analytical solution has a number of assumptions, two of which are that the wetting front is defined by water content at which the hydraulic conductivity (K) is I mm day(-1) and that the flow occurs from a point source. Here we compare the wetting patterns calculated with a 2-dimensional numerical model, HYDRUS2D, for solving the water flow into typical soils with the analytical solution. The results show that the wetting patterns are similar, except when the soil properties result in the assumption of a point source no longer being a good description of the flow regime. Difficulties were also experienced with getting stable solutions with HYDRUS2D for soils with low hydraulic conductivities. (c) 2005 Elsevier Ltd. All rights reserved.

Neural networks for time-varying data

This paper reviews some basic issues and methods involved in using neural networks to respond in a desired fashion to a temporally-varying environment. Some popular network models and training methods are introduced. A speech recognition example is then used to illustrate the central difficulty of temporal data processing: learning to notice and remember relevant contextual information. Feedforward network methods are applicable to cases where this problem is not severe. The application of these methods are explained and applications are discussed in the areas of pure mathematics, chemical and physical systems, and economic systems. A more powerful but less practical algorithm for temporal problems, the moving targets algorithm, is sketched and discussed. For completeness, a few remarks are made on reinforcement learning.

Estimating time-varying risk premia in UK long-term government bonds

Simple models of time-varying risk premia are used to measure the risk premia in long-term UK government bonds. The parameters of the models can be estimated using nonlinear seemingly unrelated regression (NL-SUR), which permits efficient use of information across the entire yield curve and facilitates the testing of various cross-sectional restrictions. The estimated time-varying premia are found to be substantially different to those estimated using models that assume constant risk premia. © 2004 Taylor and Francis Ltd.

Numerical implementation of the coarse step method with a varying differential group delay

The effect of having a fixed differential group delay term in the coarse step method results in a periodic pattern in the inserting a varying DGD term at each integration step, according to a Gaussian distribution. Simulation results are given to illustrate the phenomenon and provide some evidence about its statistical nature.