An Estimation Procedure for the Joint Distribution of Spatial Direction and Thickness of Flat Bodies Using Vertical Sections. Part II: An application in soil micromorphology

In soil micromorphology fissures are considered in vertical sections. To get information about the properties of the soil the joint distribution of spatial direction and width of these fissures is of interest. The fissures are mathematically generalized to flat bodies which are defined as stationary weighted surface processes with the weight “thickness”. In a typical point of the surface process suitable, joint parametric distributions of direction and thickness are assumed. The parameters have to be estimated from measurements on vertical sections which are taken from the soil. On these sections only a visible thickness and a visible angle can be observed. The joint distribution of these variables can be expressed by the joint distribution of spatial direction and thickness with the same parameters and in this indirect way the parameters can be estimated. The paper describes how to randomize the vertical section and how to measure the visible variables on the sections. The Chi-Square method is proposed for the parameter estimation. Further it is discussed how to derive good starting values for the numerical procedure. All this is demonstrated in a simulation study using the Bingham-Mardia distribution for the direction and the lognormal distribution for the thickness including a way to correlate the mean thickness and the direction. Finally an application in soil micromorphology is demonstrated for one soil horizon.     

Reference values for feeding parameters of isopods (Porcellio scaber,Isopoda, Crustacea)

The advantage of using terrestrial isopods in toxicity studies is that a battery of parameters can be tested at different levels of biological complexity. Feeding parameters for example link organism level response to potential ecological consequences but a problem with using feeding parameters in toxicity tests with terrestrial isopods is their high variability. The aim of our study was to set benchmark values for feeding parameters for isopod Porcellio scaber (Isopoda, Crustacea) in laboratory-controlled experiments. In the work presented here, the daily feeding rate of the central 50% of the control population of Porcellio scaber and a correlation between feeding rate and isopod weight were set. Values outside these ranges need additional evaluation to increase the relevance of test outcomes. We suggest using benchmark values for feeding parameters as well as the coefficient of variation (a) to identify animals with altered feeding parameters with respect to controls, and (b) to assess the data quality in each experiment.     

Estimation of Individual Growth Curves by Empirically Weighted Least Squares

The simultaneous estimation of individual growth curves and a mean growth curve is accomplished by weighted least squares. A polynomial curve is fitted for each individual and the polynomial parameters are linear functions of parameters corresponding to covariates. A simple, computationally efficient variance-covariance estimator is derived. The resultant estimate is used in the weighted least squares estimation. The results are compared to empirical Bayes estimation.     

On Comparing Correlated Means in the Presence of Incomplete Data

Two statistics are proposed for testing the hypothesis of equality of the means of a bivariate normal distribution with unknown common variance and correlation coefficient when observations are missing on both variates. One of the statistics reduces to the one proposed by Bhoj (1978, 1984) when the unpaired observations on the variates are equal. The distributions of the statistics are approximated by well known distributions under the null hypothesis. The empirical powers of the tests are computed and compared with those of some known statistics. The comparison supports the use of one of the statistics proposed in this paper.     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Comparisons of tests for aneuploidy

The fundamental problems that face us in the development of suitable assay systems for the detection of potentially aneugenic (aneuploidy-inducing) chemicals include: (a) the diversity of cellular targets and mechanisms where perturbations of structure and function may give rise to changes in chromosome number, and (b) the phylogenetic differences that exist between species in their mechanism and kinetics of cell division and their metabolic profiles. A diverse range of assay systems have been developed, which have been shown to have potential for use in the detection of either changes in chromosome number or of perturbations of the events which may be causal in the induction of aneuploidy.

Chromosome number changes may be detected cytologically by karyotypic analysis, or by the use of specialised strains in which aneuploid progeny may be observed due to phenotypic differences with aneuploid parental cells or whole organisms. Techniques for the detection of cellular target modifications range from in vitro studies of tubulin polymerisation to observations of the behaviour of various cellular organelles and their fidelity of action during the division cycle.

The diversity of mechanisms which may give rise to aneuploidy and the qualitative relevance of events observed in experimental organisms compared to man make it unlikely that the detection and risk assessment of the aneugenic activity of chemicals will be possible using a single assay system. Optimal screening and assessment procedures will thus be dependent upon the selection of an appropriate battery of predictive tests for the measurement of the potentially damaging effects of aneuploidy induction.     

Sources and inheritance of resistance to leaf curl virus in Lycopersicon

Summary One hundred and twenty-two varieties, lines and wild accessions of Lycopersicon were screened under three different regimes during the autumn/winter season of 1982–83 and 1983–84 for resistance to tomato leaf curl virus (TLCV). L. hirsutum f. glabratum (B6013) and L. hirsutum f. typicum (A1904) proved to be highly resistant to TLCV in all three environments. Various accessions of L. peruvianum were also highly resistant. L. pimpinellifolium (A1921) exhibited no TLCV symptoms within 90 days. Of the cultivated varieties, Acc 99 exhibited the minimim score for susceptibility; AC 142, Collection No. 2, Kalyanpur Angurlata and HS 101 had a low rating for virus incidence. The inheritance of resistance was studied in the interspecific crosses between a TLCV resistant line of L. pimpinellifolium (A1921) and five (HS 101, HS 102, HS 110, Pusa Ruby and Punjab Chhuhara) susceptible cultivars of L. esculentum. Parents, F₁, F₂ and backcross progenies were artificially inoculated with local strains of TLCV using vector the viruliferious whitefly, Bemisia tabaci (Genn.). Data indicated that the resistance of L. pimpinellifolium (A 1921) is monogenic and incompletely dominant over susceptibility.