The results show a dramatic functional improvement in quality of life and a high overall satisfaction rate of patients undergoing this procedure. Our modification makes this a relatively simple procedure with a predictable outcome.

The aim of the study was to determine the production responses of lambs receiving either creep feed or not while grazing two different pastures. The production of ewes within each treatment was also recorded. The study was conducted at both the Kromme Rhee and Langgewens Research Farms. At Kromme Rhee, sheep grazed kikuyu (Pennisetum clandestinum) pasture under irrigation. Dohne Merino (n = 47) ewes, with their lambs, were randomly allocated to four groups. At Langgewens, the sheep grazed medic (Medicago parrabinga) pastures under dry-land conditions. South African Mutton Merino ewes (n = 89), with their lambs, were randomly divided into four groups. At Langgewens creep feed was provided at 200 g/lamb/day from the start of the study. This was increased by 100 g/lamb/day every week up to a maximum of 600 g/lamb/day. At Kromme Rhee, creep feed was provided at 200 and 300 g/lamb/day for the first and second week, respectively. From week three creep feed was provided ad libitum. At both locations ewes and lambs were weighed once a week. Live weight data of lambs and ewes were analysed by means of a multifactor analysis of variance with treatment (creep feed or no creep feed) and birth status (single and twins) as main factors. Provision a creep feed at Langgewens significantly increased lamb weight, but had no effect on ewe live weight. The provision of creep feed At Kromme Rhee significantly increased lamb weight as well as ewe weight. At both locations, birth status had no effect on the production parameters for ewes or lambs.

This paper investigates an inverse analysis technique to find leaks in water networks and compares different solution strategies. Although a number of strategies have been proposed by different authors to identify leaks on a vast selection of pipe networks, limited research has been done to compare strategies and point out their weakness. Three strategies, a Bayesian Probabilistic Analysis, a Support Vector machine and, an Artificial Neural Network were combined with the inverse analysis technique on different numerical and experimental networks to point out each strategies weakness. Two numerical networks are investigated and one experimental network. It is shown that the Bayesian Probabilistic Analysis struggles to find unique solutions when a few observations are available, while the Support Vector Machine and the Artificial Neural Network struggle when only flow measurements are available. Additionally it is shown that the Artificial Neural Network struggles to estimate unique solutions for leak size and location.

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