Calculating animal performance from limited liveweight measurements of the population

We consider the problem of estimating the distribution of carcass weights in a flock of animals from estimates made on a truncated sample. This arises when a farmer chooses the heaviest lambs for slaughter and then measurements are made by the meat processor. This enables a farmer to answer two questions: what proportion of the animals remaining exceed a nominated carcass weight, and/or what carcass weight is exceeded by a nominated proportion of the population? Estimates of these statistics and their uncertainties are derived and are exact if the animal weights are normally distributed. These calculations can be the basis of decisions about future feeding and drafting strategies, important for farmers producing animals on contracts for future delivery. An example is given based on 1000 lambs using a cut-off weight of 15.5 kg with mean of this upper group of 16 kg. Using a realistic estimate of a standard deviation (of the weighing scales) of 0.3 kg, this gives an estimated mean of 14.6± 0.04 kg, with a standard deviation of 0.94±0.044 kg, and that 75% of the lambs in the population exceed 13.9±0.07 kg. The proportion of lambs that exceed 14.5 kg is then between 51.3% and 55.7%

Natural Boundaries for Solutions to a Certain Class of Functional Differential Equations

AbstractThis paper is concerned with a generalization of a functional differential equation known as the pantograph equation. The pantograph equation contains a linear functional argument. In this paper we generalize this functional argument to include nonlinear polynomials. In contrast to the entire solutions generated by the pantograph equation for the retarded case, we show that in the nonlinear case natural boundaries occur. These boundaries are linked to the Julia set of the polynomial functional argument

The evolution of language: a comparative review

For many years the evolution of language has been seen as a disreputable topic, mired in fanciful "just so stories" about language origins. However, in the last decade a new synthesis of modern linguistics, cognitive neuroscience and neo-Darwinian evolutionary theory has begun to make important contributions to our understanding of the biology and evolution of language. I review some of this recent progress, focusing on the value of the comparative method, which uses data from animal species to draw inferences about language evolution. Discussing speech first, I show how data concerning a wide variety of species, from monkeys to birds, can increase our understanding of the anatomical and neural mechanisms underlying human spoken language, and how bird and whale song provide insights into the ultimate evolutionary function of language. I discuss the ‘‘descended larynx’ ’ of humans, a peculiar adaptation for speech that has received much attention in the past, which despite earlier claims is not uniquely human. Then I will turn to the neural mechanisms underlying spoken language, pointing out the difficulties animals apparently experience in perceiving hierarchical structure in sounds, and stressing the importance of vocal imitation in the evolution of a spoken language. Turning to ultimate function, I suggest that communication among kin (especially between parents and offspring) played a crucial but neglected role in driving language evolution. Finally, I briefly discuss phylogeny, discussing hypotheses that offer plausible routes to human language from a non-linguistic chimp-like ancestor. I conclude that comparative data from living animals will be key to developing a richer, more interdisciplinary understanding of our most distinctively human trait: language

Steady state optimal insulin infusion for hyperglycemic ICU patients

Invited publication/contribution full paper review CD-ROM proceedingsClose control of blood glucose levels significantly reduces vascular complications in diabetes, as well as having beneficial effect for cardiac and other critical care patients. Recent studies have shown that tight regulation of blood glucose level in intensive care unit patients can reduce mortality by as much as 45%. This paper presents an optimal insulin infusion algorithm to tightly regulate blood glucose for ICU and other critical care patients when the glucose input is known. Results show an ideal, flat blood glucose response when subjected to a typical ICU glucose input as well as for a far more extreme case

Active insulin infusion using optimal and derivative weighted control

Close control of blood glucose levels significantly reduces vascular complications in Type I diabetes. A control method for the automation of insulin infusion that utilizes emerging technologies in blood glucose biosensors is presented. The controller developed provides tighter, more optimal control of blood glucose levels, while accounting for variation in patient response, insulin employed and sensor bandwidth. Particular emphasis is placed on controller simplicity and robustness necessary for medical devices and implants

Minimal haemodynamic system model including ventricular interaction and valve dynamics

doi:10.1016/j.medengphy.2003.10.001Characterising circulatory dysfunction and choosing a suitable treatment is often difficult and time consuming, and can result in a deterioration in patient condition, or unsuitable therapy choices. A stable minimal model of the human cardiovascular system (CVS) is developed with the ultimate specific aim of assisting medical staff for rapid, on site modelling to assist in diagnosis and treatment. Models found in the literature simulate specific areas of the CVS with limited direct usefulness to medical staff. Others model the full CVS as a closed loop system, but models were found to be very complex, difficult to solve, or unstable. This paper develops a model that uses a minimal number of governing equations with the primary goal of accurately capturing trends in the CVS dynamics in a simple, easily solved, robust model. The model is shown to have long term stability and consistency with non-specific initial conditions as a result. An “open on pressure close on flow” valve law is created to capture the effects of inertia and the resulting dynamics of blood flow through the cardiac valves. An accurate, stable solution is performed using a method that varies the number of states in the model depending on the specific phase of the cardiac cycle, better matching the real physiological conditions. Examples of results include a 9% drop in cardiac output when increasing the thoracic pressure from -4mmHg to 0mmHg, and an increase in blood pressure from 120/80mmHg to 165/130mmHg when the systemic resistance is doubled. These results show that the model adequately provides appropriate magnitudes and trends that are in agreement with existing data for a variety of physiologically verified test cases simulating human CVS functio