Mixed Moment Estimation in Hermite Distribution and its Comparison with Other Estimation Procedures from Sample Size Considerations

In this paper (1) expressions (correct to n^?2 terms) for biases, variances, and covariances of the estimators a and b of Hermite distribution with probability generating function Exp[a(t–1) + b(t–1)] are obtained for two mixed moment estimates; (2) for the biases and variance-covariances, approximate regions of the parameter space (a>0, b>0) have been outlined where a sample of size 100 can be considered as “safe” in the sense that contribution of second order terms in them is 5% of that from the first order term; (3) comparison of the biases and variance-covariances of these two sets of estimators are made with those for the moment estimators, maximum likelihood estimates and the even point estimators for a sample of size 100 using the terms up to order n^?2; (4) the comparisons based on n^?2 terms in (3) have not only provided information on the estimation procedures included in the Hermite distribution, but also demonstrated the importance of higher order terms in the sampling properties of the various alternative techniques for the Hermite distribution.     

Elimination ofSitotroga cerealella (Olivier) bySitophilus zeamais Motschulsky from mixed laboratory cultures on maize

This paper describes a series of experiments conducted to determine why Sitophilus zeamaisMots . and Sitotroga cerealella (Oliv. ) could not survive together in maize cultures in the laboratory. The effect of S. zeamais on different developmental stages of S. cerealella was investigated. The presence of adult S. zeamais slightly affected moth copulation, egg laying and moth eggs in a mixed culture, but large numbers of developing moths inside maize grains were killed by the adult weevil through feeding on the grains. The major cause of elimination of S. cerealella by S. zeamais from mixed cultures was therefore found to be damage to the immature moths in grain and such moth mortality increased as the developing moths became bigger in the grains. A weevil: grain ratio of approximately 1.4∶1 was found to be the critical weevil density at which the moth disappeared from the mixed cultures.     

The effect of larval age range on survival of twoTribolium castaneum strains in mixed cultures,through pupal cannibalism

The effect of larval age range on survival of two Tribolium castaneum strains in mixed cultures was studied in an experimental situation in which other selective forces were reduced to a minimum. Increasing the difference in larval age setween the strains by one day resulted in a reduction of survival of the faster-developing mutant strain, because more of its earlier pupae were cannibalized by the larvae. General aspects of the effects of pupal cannibalism by larvae on the outcome of intra-specific competition (sensu lato) in Tribolium are discussed.     

A New Statistical Method for Mixed Variates Analysis in Epidemiological Research

Epidemiologically oriented research often may not do without observational or only partially controlled studies. In many such situations both qualitative characteristics and quantitative ones are observed. In literature there are different methods of handling such problems. The paper presents a method for analyzing dependencies resp. associations between random variates of any kind. The model concerned fullfills the whole field between analysis of variance, analysis of covariance and contingency table analysis. The method is named MIVA or mixed variates analysis, bases on the class of Conditional Gaussian Distributions of the exponential family and results in a unique system of mixed and unmixed measures of association–of pairwise, partial, multiple and global type. These measures are easy to be estimated and tested on significant deviation from zero. They may be used describing or analyzing dependence structures in many epidemiological studies but also in other fields.     

Mixed chemostat cultures of obligately aerobic and fermentative or methanogenic bacteria grown under oxygen-limiting conditions

Abstract Defined mixed cultures of an obligately aerobic Pseudomonas testosteroni and anaerobic Veillonella alcalescens strain were grown under oxygen and lactate limitation in chemostats with different oxygen supply rates. The aerobic and the anaerobic bacteria were shown to coexist and to complete for common substrates over a wide range of oxygen supply rates. Under similar conditions but with formate as the major substrate chemostat enrichments gave rise to undefined mixed cultures of aerobic, fermentative and methanogenic bacteria. The relevance of these observations to natural mineralization processes is discussed.     

Freshwater fishes of northern South America: a need for field guides

The efficient collection of fishes from structurally complex environments (e.g., coral reefs, kelp forests) is difficult because conventional collecting methods generally cannot be used and many of the fishes are mobile and active. We describe the design, operation, and application of a diver-propelled net for efficiently collecting many species of benthic fish that reside on coral reefs and on kelp-forested rocky reefs. The overall size of the net and mesh size of the netting can be adjusted according to the size and behavior of targeted species to minimize drag and damage to specimens. Altering these dimensions combined with proper use of the net can result in a high rate of capture success. This revised version was published online in July 2006 with corrections to the Cover Date.     

A comparative assessment of support vector regression,artificial neural networks,and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape

Soil organic carbon (SOC) is a key indicator of ecosystem health, with a great potential to affect climate change. This study aimed to develop, evaluate, and compare the performance of support vector regression (SVR), artificial neural network (ANN), and random forest (RF) models in predicting and mapping SOC stocks in the Eastern Mau Forest Reserve, Kenya. Auxiliary data, including soil sampling, climatic, topographic, and remotely-sensed data were used for model calibration. The calibrated models were applied to create prediction maps of SOC stocks that were validated using independent testing data. The results showed that the models overestimated SOC stocks. Random forest model with a mean error (ME) of −6.5 Mg C ha⁻¹ had the highest tendency for overestimation, while SVR model with an ME of −4.4 Mg C ha⁻¹ had the lowest tendency. Support vector regression model also had the lowest root mean squared error (RMSE) and the highest R² values (14.9 Mg C ha⁻¹ and 0.6, respectively); hence, it was the best method to predict SOC stocks. Artificial neural network predictions followed closely with RMSE, ME, and R² values of 15.5, −4.7, and 0.6, respectively. The three prediction maps broadly depicted similar spatial patterns of SOC stocks, with an increasing gradient of SOC stocks from east to west. The highest stocks were on the forest-dominated western and north-western parts, while the lowest stocks were on the cropland-dominated eastern part. The most important variable for explaining the observed spatial patterns of SOC stocks was total nitrogen concentration. Based on the close performance of SVR and ANN models, we proposed that both models should be calibrated, and then the best result applied for spatial prediction of target soil properties in other contexts.