Study on Vehicle’s Arrival Rule and Relation between Traffic Flow Parameters on Snowy Pavement

There are great difference in traffic flow characteristics between snowy pavement and non-snowy pavement. Ten road sections were investigated and the data of traffic volume, headway, speed and density on snowy and non-snowy pavement were collected. Vehicle’s arrival rules were compared and reasonable distribution was given. The relation between traffic volume and speed, density and traffic volume were compared between snowy pavement and non-snowy pavement. It indicated that negative binominal distribution is more fit to vehicle’s arrival frequency on snowy pavement. Speed decreases for the same traffic volume and traffic volume decreases for the same density on snowy pavement.

Comparison of capture methods for the diagnosis of adult anopheline populations from State of Mato Grosso, Brazil

INTRODUCTION: The present study compares human landing catches of primary malaria vectors with two alternative methods of capture: the Shannon trap and the Mosquito magnet. METHODS: This study used regression models to adjust capture data to a negative binominal distribution. RESULTS: Capture numbers and relative percentages obtained from the three methods vary strongly between species. The highest overall captures were obtained for Anopheles triannulatus with captures for the Shannon trap and the Mosquito magnet measuring more than 330% higher than captures obtained by human landings. For Anopheles darlingi, captures by the Shannon trap and the Mosquito magnet were about 14% and 26% of human landing catches, respectively. Another species with malaria transmission potential that was not sampled by human landing captures weascaptured by the Shannon trap and the Mosquito magnet (Anopheles oswaldoi). Both alternative sampling techniques can predict the human landing of Anopheles triannulatus, but without proportionality. Models for Anopheles darlingi counts, after totaling daily captures, are significant and proportional, but prediction models are more reliable when using the Shannon trap compared with the Mosquito magnet captures. CONCLUSIONS: These alternative capture methods can be partially recommended for the substitution of human landing captures or, at least, as complementary forms of monitoring for malarial mosquitoes.

Transformation of protoplasted yeast cells is directly associated with cell fusion

The frequency of cell fusion during transformation of yeast protoplasts with various yeast plasmids with a chromosome replicon (YRp or YCp) or 2 mu DNA (YEp) was estimated by two methods. In one method, a mixture of protoplasts of two haploid strains with identical mating type and complementary auxotrophic nuclear markers with or without cytoplasmic markers was transformed. When the number of various phenotypic classes of transformants for the nuclear markers was analyzed by equations derived from binominal distribution theory, the frequency of nuclear fusion among the transformants was 42 to 100% in transformations with the YRp or YCp plasmids and 28 to 39% with the YEp plasmids. In another method, a haploid bearing the sir mutation, which allows a diploid (or polyploid) homozygous for the MAT (mating type) locus to sporulate by the expression of the silent mating-type loci HML and HMR, was transformed with the plasmids. Sporulation ability was found in 43 to 95% of the transformants with the YRp or YCp plasmids, and 26 to 31% of the YEp transformants. When cytoplasmic mixing was included with the nuclear fusion, 96 to 100% of the transformants were found to be cell fusants. Based upon these observations, we concluded that transformation of yeast protoplasts is directly associated with cell fusion.

Transformation of protoplasted yeast cells is directly associated with cell fusion.

The frequency of cell fusion during transformation of yeast protoplasts with various yeast plasmids with a chromosome replicon (YRp or YCp) or 2 mu DNA (YEp) was estimated by two methods. In one method, a mixture of protoplasts of two haploid strains with identical mating type and complementary auxotrophic nuclear markers with or without cytoplasmic markers was transformed. When the number of various phenotypic classes of transformants for the nuclear markers was analyzed by equations derived from binominal distribution theory, the frequency of nuclear fusion among the transformants was 42 to 100% in transformations with the YRp or YCp plasmids and 28 to 39% with the YEp plasmids. In another method, a haploid bearing the sir mutation, which allows a diploid (or polyploid) homozygous for the MAT (mating type) locus to sporulate by the expression of the silent mating-type loci HML and HMR, was transformed with the plasmids. Sporulation ability was found in 43 to 95% of the transformants with the YRp or YCp plasmids, and 26 to 31% of the YEp transformants. When cytoplasmic mixing was included with the nuclear fusion, 96 to 100% of the transformants were found to be cell fusants. Based upon these observations, we concluded that transformation of yeast protoplasts is directly associated with cell fusion.

The propensity to cause accidents

Information relating to the expected number of losses is of importance in automobile insurance systems. The distribution of risks by number of losses per year may be based on the following model with λ representing the average number of losses per year. This distribution is the Poisson distribution. Tests of this model versus actual observations often indicate significant deviation. This discrepency can result from the constancy of λ which makes the model appropriate for an individual but would require an isohazardous population when applied to a group of individuals. In reality, however, λ will vary from individual to individual. A model accounting for this spread in λ is given in where z(λ) is a distribution describing the spread of λ. The results of model (2) certainly will depend on the form of z(λ). It has been hypothesized that z(λ) can be represented by (3) which is a Pearson Type III [1, 5, 7]. With this assumption model (2) becomes the negative binominal distribution with a mean of and a variance of If the observed mean is and the observed variance it is possible to determine a and b by solving the above equations for mean and variance. Thus and The results indicate an improved fit to actual observations [1, 5, 6].