Lifetimes Of Individuals Research Articles

The Effects of Diseases, Drugs, and Chemicals on the Creativity and Productivity of Famous Sculptors, Classic Painters, Classic Music Composers, and Authors

Many myths, theories, and speculations exist as to the exact etiology of the diseases, drugs, and chemicals that affected the creativity and productivity of famous sculptors, classic painters, classic music composers, and authors. To emphasize the importance of a modern clinical chemistry laboratory and hematology coagulation laboratory in interpreting the basis for the creativity and productivity of various artists. This investigation analyzed the lives of famous artists, including classical sculptor Benvenuto Cellini; classical sculptor and painter Michelangelo Buonarroti; classic painters Ivar Arosenius, Edvard Munch, and Vincent Van Gogh; classic music composer Louis Hector Berlioz; and English essayist Thomas De Quincey. The analysis includes their illnesses, their famous artistic works, and the modern clinical chemistry, toxicology, and hematology coagulation tests that would have been important in the diagnosis and treatment of their diseases. The associations between illness and art may be close and many because of both the actual physical limitations of the artists and their mental adaptation to disease. Although they were ill, many continued to be productive. If modern clinical chemistry, toxicology, and hematology coagulation laboratories had existed during the lifetimes of these various well-known individuals, clinical laboratories might have unraveled the mysteries of their afflictions. The illnesses these people endured probably could have been ascertained and perhaps treated. Diseases, drugs, and chemicals may have influenced their creativity and productivity.

A morphological approach for relating decapod crustacean cephalothorax shape with distribution in the water column

Cephalothorax profiles for individuals of 18 decapod crustacean species were obtained from pictures of specimens captured using various experimental bottom trawls in the Mediterranean basin, at depths ranging from 200 to 4000 m in 2000 and 2002. Profiles were compared using the shape (outline) of the entire cephalothorax (including and excluding the rostrum). Principal component analysis (PCA) of the profiles, rostrum included, yielded two large species groupings related to rostrum size, species having a long rostrum being clustered on the positive portion of the first axis and species having a short rostrum being clustered on the negative portion of this same axis (the F1 axis explained 72.17% of the total variance). The PCA separated pelagic and endobenthic animals (with short rostrums) from nektobenthic animals (with long rostrums). Only the two deepest-dwelling species (dwelling at depths below 2000 m) were distanced from their respective groups. The pelagic shrimp Acanthephyra pelagica was clearly grouped with the nektobenthic species despite being reported to have a pelagic habitat. The nektobenthic deep-sea species Nematocarcinus exilis has a relatively medium-size rostrum and was placed among the pelagic–endobenthic species. The endobenthic and pelagic groups remained stable even when rostral morphometrics were excluded from the PCA analysis. The hypothesis that predation and diet are the fundamental determining factors for all habitats throughout most of the lifetimes of individuals and hence that species will evolve specialised phenotypes to adapt to local environmental conditions is considered in the discussion.

Emergence of species and punctuated equilibrium in the Tangle Nature model of biological evolution

We consider an individual-based model of evolution. Species emergence as segregation of the population on to discrete positions in a hyper-cubical genotype space. The model emphasises interaction between coexisting genotypes. Although the rate of the micro-dynamics, consisting of reproduction and killing of individuals is essentially constant, the macro-dynamics is punctuated. The macro-evolution consists of the creation and annihilation of configurations in genotype space equivalent to sequences of different ecosystems. We review the definition of the model and results concerning distribution lifetimes of individuals, genotypes and configurations. We discuss the non-stationarity of the model and how this agrees with the fossil record. Finally, we describe how the model is able to produce species abundance distributions of a form qualitatively in agreement with observation on real ecosystems.

Enhancing the capacity of food consumption surveys of short duration to estimate long term consumer-only intakes by combination with a qualitative food frequency questionnaire

In principle, a proper risk assessment for a food chemical requires that the time-frame for food chemical intake estimates matches the time-frame for the toxicological assessments upon which the safety statements (ADI, PTW I, etc.) are based. For food additives, the toxicological assessments are based on exposure over a lifetime. While food consumption data cannot be collected over the lifetimes of individuals, the information should reflect habitual intakes as closely as possible. This study investigated the possibility of combining a 3-day food diary with a food frequency questionnaire to estimate mean consumer-only food intakes comparable to estimates based on a 14-day diary. The study population consisted of 948 teenagers and analysis was based on 32 clearly defined foods. For 47% of the foods, the difference was ≤ 1g/day. When expressed as portion sizes, 56% of the foods showed differences representing <5% of an average portion and no food showed a difference >14% of an average portion. When between-method differences (portions/day) were plotted against the mean of the methods, the mean between-method difference was 0.02 (± 0.06) portions/ day with limits of agreement of -0.10 to 0.14. This preliminary investigation suggests that the combined 3-day diary and FFQ method provides comparable estimates of mean consumer only intakes to a 14-day diary. Therefore, a qualitative FFQ may be a useful adjunct to a food consumption survey of short duration if estimates of longer term food intakes are required.

Discrete-continuous structural optimization with distributed evolution strategies

This paper describes the development and application of distributed Evolution Strategies (ES) in the field of mixed-discrete structural optimization. ES are direct, probabilistic optimization methods based on the use of the three evolution operators recombination, mutation and selection in an evolving population of competing individuals in the design space. Advanced features of the employed ES include self-adaption of strategy parameters to achieve on-line tuning of the optimization process and a flexible selection scheme that allows scalable lifetimes of individuals The property of using a population of coexisting but independent individuals allows the efficient realization in distributed computing environments. This approach results in a drastic reduction of response time and an improved applicability for large scale problems

Semi‐parametric estimation of covariate effects using the positive stable frailty model

AbstractMany biological and medical studies have as a response of interest the time to occurrence of some event, such as the occurrence of a particular symptom or disease, remission, relapse, death due to some specific disease, or simply death. In this paper we study the problem of assessing the effect of potential risk factors on the outcome event of interest through a parametric or semi‐parametric frailty model where the lifetimes have a reason to be considered dependent. This dependence may arise because of multiple endpoints within the same individual or because, when studying a single endpoint, there are natural groupings between study subjects. The objective of this paper is to extend both parametric and semi‐parametric approaches to regression analysis in which the lifetimes of individuals in a group are effected by the same random frailty which follows a positive stable distribution. Some comparisons of the properties of this frailty distribution with other frailty distributions are made and an example which assesses the effect of a treatment in a litter‐matched tumorigenesis study is presented.

Phenotypic plasticity of a transplanted population of dwarf cisco,Coregonus artedii

A population of dwarf cisco in Minnesota was studied in native and transplant environments. Life history characters were recorded and the stability of meristics and morphometrics of the population over a two year period in three different environments was assessed with univariate and multivariate statistics. Transplanted cisco lived longer and grew larger than they did in their native lake, yet retained distinctive pigmentation patterns and an unusually early spawning season. Meristic characters of dwarf fish remained within ranges reported forCoregonus artedii during the lifetimes of individuals in their new environments, but morphometric measures underwent significant size- and shape-related changes. Incubation and rearing studies show egg incubation time and behavior of larvae were identical of those of non-dwarf cisco. Comparisons with non-dwarf cisco populations illustrate the ecophenotypic plasticity of adult fish of this population of North American cisco.

Effect of Selection on the Failure Rate Function

Effect of selection procedures such as truncation and genotypic selection, are studied using selection differentials. These studies are mainly restricted to the study of mean or percentiles of the characteristics of interest. However, in situations where improvement on longetivity is itself of interest, in addition to studying mean or percentiles, one may study the reliability characteristics such as Failure Rate, Mean Residual Life etc., of the lifetimes of individuals. In this paper, we study the effect of genotypic selection when the distribution function of the lifetime is governed by a single locus with 2 alleles. We compute the difference in the failure rate function from one generation to the next generation for different values of n, the number of generations. We also obtain the limiting values of the failure rate function as n and compute the number of generations required for the failure rate to reach a value close enough to the limiting failure rate function. We also consider an example in a two-loci case and study the effect of selection on the failure rate function.

EDUCATION AND THE NATIONAL WEALTH OF THE UNITED STATES*

Human capital theory has motivated a great many empirical investigations into the relationship between education and earnings potential. These studies test refinements of the theory, but do not attempt to value education for the economy as a whole. This study develops series which track human wealth and its educational components for the United States from 1946 to 1980. Three related educational time sequences emerge: (1) schooling wealth, the present value of the current and future contributions of the existing schooling stock to national income; (2) net change in schooling wealth, the amount added to present value in that year; and (3) schooling investment, the present value of the future contributions of the new schooling conducted in that year.One important lesson of this exercise is that the last two series can be quite different as a result of the pattern of appreciation and depreciation of human wealth over the lifetimes of individuals. Moreover, education increases the age of peak human wealth and thus should shorten the period during which individuals save for retirement. This phenomenon may induce a demographic cycle in the nation's savings rate, especially evidenced with the aging of the baby‐boom cohort.The magnitudes of the human and schooling wealth estimates are large when compared to financial wealth. For a 4 percent rate, the period‐wide average for human wealth is five times‐and schooling wealth 2.6 times‐the Federal Reserve Board's measure of household net worth. These estimates are naturally sensitive to the discount rate chosen, but show that the gap between human and financial wealth has been widening and that the value of schooling provided in any year greatly exceeds its cost. Schooling represents a form of saving whose value is several times the conventional measure of saving.

Entropy and the life table.

The life table of a population gives information about differences in age at death between the members of the population. These differences arise from the relative effects of genetic and environmental factors. The shape of the life table may provide information about the genetic variability in the population, the range of environmental factors that impinge on the population or the incidence of random events in the lifetimes of different individuals. A problem of some interest to population biologists is the evaluation of the relative effects of genetic and environmental components on the evolution of the life table. The resolution of this problem requires, first of all, determining some measure of the shape of the life table as a function of the age-specific mortality and fertility of the population. The analysis of the life table which this note describes is based on a new demographic parameter, the entropy of a population, introduced in population biology [1]. This parameter is a measure of the convexity of the life table. We observe that the three theoretical life-history curves [2, 3] can be characterized in terms of the maximization of our entropy parameter subject to simple constraints on the stable age distribution. This note is not concerned with the evolution of the life table. To do this we need to make some hypothesis concerning the genetic and environmental mechanisms that operate to determine the life history of a population. This aspect is discussed in a companion article [4]. An interesting application of our entropy parameter to the study of male-female mortality patterns is given in [5]. Let l(x) be the probability that an individual born at age zero survives to age x and let re(x) denote the age-specific fecundity. The net reproductive rate R o is given by