An example of age dependency in compartmental analysis

Compact analytic solution to distribution theory of nonsteady state model illustrated with biological data - age dependency in compartmental analysi

Stochastic compartmental analysis - Some applications and examples of estimation in a pulse labelled system

Stochastic compartmental analysis with examples of estimation in pulse labelled syste

USING THE CUMULATIVE-SIZE MECHANISTIC MODEL FOR ANALYZING INSECT DATA

Two data sets of aphid abundance are analyzed using a new cumulative-size based mechanistic model. The first data set pertains to the cotton aphid, and its analysis demonstrates the power of the mechanistic model-based approach. The second data set pertains to greenbug populations, and its analysis shows the key role that birth and death rate coefficients may play in predicting the peak and the cumulative population sizes

COMPARISONS OF TWO SYMMETRIC DENSITY FUNCTION SOLUTIONS OF APHID POPULATION GROWTH MODELS

Aphids are among the world\u27s most devastating crop pests, and their population trajectories in field crops are characterized by rapid boom and bust, under the influence of bottom up (host plant) and top down (natural enemy) forces. Theoretical development in aphid growth trajectory modeling has recently advanced quite significantly, and the logistic and normal probability density functions have been found to provide analytical solutions to mechanistic models of the aphid population growth dynamics. The logistic or hyperbolic secant squared model captures a growth trajectory shaped by negative feedback of the aphid population on itself, due to the accumulation of adverse effect on its host plant and the coupling with natural enemies (bottom up as well as top down effect), while the normal model can be derived on the basis of a relationship between intrinsic growth rate and the host plant phenology. In this paper, we fit both models to a large number of observed aphid population trajectors and explore model properties. It is shown that, despite the diverging mechanistic underpinnings of the model, the generated growth curves, as fitted to the data, are very similar, as are characteristics, such as the height of the peak, the time of the peak and the accumulated area under the curve. Both models are useful workhorses for capturing aphid growth dynamics, but fitting one or either model cannot be used as evidence for the underpinning mechanisms, as different underpinning mechanisms result in similar population dynamics

Sensor development and readout prototyping for the STAR Pixel detector

The STAR experiment at the Relativistic Heavy Ion Collider (RHIC) is designing a new vertex detector. The purpose of this upgrade detector is to provide high resolution pointing to allow for the direct topological reconstruction of heavy flavor decays such as the D{sup 0} by finding vertices displaced from the collision vertex by greater than 60 microns. We are using Monolithic Active Pixel Sensor (MAPS) as the sensor technology and have a coupled sensor development and readout system plan that leads to a final detector with a <200 {micro}s integration time, 400 M pixels and a coverage of -1 < {eta} < 1. We present our coupled sensor and readout development plan and the status of the prototyping work that has been accomplished

PREDICTING THE DATE OF FIRST CATCH OF THE CORN EARWORM, HELICOVERPA ZEA, IN CENTRAL U.S.

This paper develops predictive (or correlative) models for the date of first catch of the com earworm, Helicoverpa zea, as a basis for identifying biotic and abiotic factors that influence dispersal and migration. Data described in Goodenough et al. (1988, J. Econ. Entomol.) on the catch of H. zea gathered at over 150 sites predominantly in the central U.S. from 1983 to 1986 are analyzed. The dependent variables, Y1 and Y2, are date of first meaningful catch and date when cumulative catch exceeds 5, respectively; the independent variables are latitude, longitude and elevation of the site. Outstanding among the findings are the following : 1) There is no statistical evidence based on all the data that the slopes of the simple linear regression models of Y2 on latitude differ among the four years. The common slope estimate is 8.11 days/degree, the intercepts differ by as many as 16 days, and the combined model has r2 = 0.69. 2) There is no statistical evidence based on the data in the central U.S. that the partial slopes of the multiple regression models of Y2 on latitude and longitude differ among the four years. The common partial slope estimates are 7.36 and -1.27 days/degree, the intercepts differ by as many as 17 days, and the combined model has R 2= 0.69. Second order terms are not significant . 3) An exploratory analysis using GIS mapping software suggests that elevation is also a significant predictor variable. The suggestion is confirmed in multiple regression models for both Y1 and Y22= 0.71 and 0.72 respectively. The intercepts differ by as many as 20 and 17 days, respectively, over the four years . These results imply that the time of fi!\u27st appearance at any location in the central U.S. could be predicted once the date of first appearance in South Texas is ascertained. They also demonstrate the utility of analyzing residuals using GIS mapping software. Research is in progress to investigate other possible predictor variables including soil moisture, soil temperature and precipitation

Dielectron Cross Section Measurements in Nucleus-Nucleus Reactions at 1.0 A GeV

We present measured dielectron production cross sections for Ca+Ca, C+C, He+Ca, and d+Ca reactions at 1.0 A GeV. Statistical uncertainties and systematic effects are smaller than in previous DLS nucleus-nucleus data. For pair mass < 0.35 GeV/c2 : 1) the Ca+Ca cross section is larger than the previous DLS measurement and current model results, 2) the mass spectra suggest large contributions from pi0 and eta Dalitz decays, and 3) dsigma/dM is proportional to ApAt. For M > 0.5 GeV/c2 the Ca+Ca to C+C cross section ratio is significantly larger than the ratio of ApAt values.Comment: Submitted to Physical Review Letters. Further analysis information will be posted on our web pages -- http://macdls.lbl.gov Figure 1 has been redrawn to make more legible. Text modified to support redrawn figur

Local correlations in a strongly interacting 1D Bose gas

We develop an analytical method for calculating local correlations in strongly interacting 1D Bose gases, based on the exactly solvable Lieb-Liniger model. The results are obtained at zero and finite temperatures. They describe the interaction-induced reduction of local many-body correlation functions and can be used for achieving and identifying the strong-coupling Tonks-Girardeau regime in experiments with cold Bose gases in the 1D regime.Comment: 8 pages, REVTeX4, published in the New Journal of Physic