Search

Purpose The purpose of this study was to evaluate the veracity of a theoretically derived model of health that describes a non-linear trajectory of health from birth to death with available population data sets. Methods The distribution of mortality by age is directly related to health at that age, thus health approximates 1/mortality. The inverse of available all-cause mortality data from various time periods and populations was used as proxy data to compare with the theoretically derived non-linear health model predictions, using both qualitative approaches and quantitative one-sample Kolmogorov- Smirnov analysis with Monte Carlo simulation. Results The mortality data's inverse resembles a log-normal distribution as predicted by the proposed health model. The curves have identical slopes from birth and follow a logarithmic decline from peak health in young adulthood. A majority of the sampled populations had a good to excellent quantitative fit to a log-normal distribution, supporting the underlying model assumptions. Post hoc manipulation showed the model predictions to be stable. Conclusions This is a first theory of health to be validated by proxy data, namely the inverse of all-cause mortality. This non-linear model, derived from the notion of the interaction of physical, environmental, mental, emotional, social and sense-making domains of health, gives physicians a more rigorous basis to direct health care services and resources away from disease-focused elder care towards broad-based biopsychosocial interventions earlier in life. [ABSTRACT FROM AUTHOR]

Abstract: The level crossing and inverse statistics analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, , where is the average waiting time for observing the level again. We estimate the probability , which provides us the probability of observing times of the level with positive slope, in time scale . For analyzed time series, we found that maximum is about . We show that by using the level crossing analysis one can estimate how the DAX and oil time series will develop. We carry out the same analysis for the increments of DAX and oil price log-returns (which is known as inverse statistics), and provide the distribution of waiting times to observe some level for the increments. [Copyright &y& Elsevier]

The effect of branch scars on the initiation and occurrence of red heart in beech ( Fagus sylvatica L.) was studied on 17 trees with red heartwood and 14 trees with no discoloured heartwood, all of which were selected from a 120-year-old high-forest stand in Germany. Logistic regression was used to predict the probability of red heart occurrence for a given tree. The model was based on individual probabilities derived from geometric relationships between scar and knot morphologies, and integrated the diameter at breast height. Using this model, 27 of 31 trees were correctly classified, and the two groups of trees were clearly distinguished by probabilities below 0.25 and above 0.85 (with one exception). Given the constitution of the model, only 17 of 616 scars were found to initiate red heart formation, and the parameters of mechanistic variables were strongly correlated. The results suggest specifying the relationship between scars, knots and red heart, and extending the scope of the model. [ABSTRACT FROM AUTHOR]

ABSTRACT The generation of sinkholes in the Ruhr valley region in Germany is caused by many centuries of coal mining at various depths and, at the least, by residual underground open spaces that do not stay stable with time. Due to the unknown distribution of underground spaces and their undefined, decreasing stability with time, probability calculations provide a somewhat successful approach in order to obtain information about the risks of sinkhole generation and possible relations to structural, geological, mining, and other influences. In this article, we demonstrate procedures and strategies for probabilistic calculations of sinkhole generation. In order to explain the basic steps of data organization and calculation, we provide an application of some of the quantitative methods, using an example from a local data set (sinkholes from a map of the Muddental region) combined with the corresponding structural geological map. This example illustrates the basic methods and clarifies the application of probabilistic methods. Due to the small database available, it was not possible to develop the results further, and thereby provide a final unequivocal classification of the dominant causes to understand the risks of sinkhole occurrences. Nevertheless, should further information be made accessible by the relevant authorities, one will be able to improve and statistically sharpen the arguments given here using the probabilistic methods, and so more clearly define the best possible correlations for estimation and prediction of sinkhole occurrences. The main point made, even with the limited data available to date, is that the methods provide powerful tools to help describe systematically the causes and risks of sinkhole occurrences. Current information from the Ruhr valley region would indicate that preventative methods are not being used on a routine basis; rather, postsinkhole occurrence filling with cement and renovation of badly damaged structures is the norm. It... [ABSTRACT FROM AUTHOR]