The influence of polyphenolics on the nutritive value of browse: A summary of research conducted at ILCA

Summarises ILCA's findings over several years of research on the nutritive value of browse plants. Discusses nitrogen metabolism in ruminants and tannin chemistry. Examines the effect of browse on animals, i.e., feed intake, growth, digestion of fibre fractions and utilisation of nitrogen. Discusses factors affecting the use of browse. Presents data on the contents of soluble phenolics and insoluble proanthocyanidins, browse and roughage intakes and growth rate in sheep, digestibility of organic matter, neutral detergent fibre & acid-detergent lignin for sheep. Also examines digestibility of dry matter, rumen ammonia and plasma urea nitrogen concentrations and daily urinary nitrogen loss, and nitrogen digestibility and contents of soluble phenolics and insoluble proanthocyanidines

Estimating the nutritive value of cereal crop residues: Implications for developing feeding standards for draught animals

Reviews analytical methods for the determination of the nutritive value of crop residues. Gives example on the accuracy of different methods in determining digestibility and of the factors affecting it. Highlights different management practices for feeding cereal crop residues to draught animals

Effect of diet restriction on work performance and weight loss of local Zebu and Friesian X Boran crossbred oxen

Reports results of an experiment conducted to determine the effect of diet restriction on work performance and body weight in crossbred and local oxen worked as singles in farmers' fields around Debre Zeit, Ethiopia, during the normal cultivation season

High performance reliability analysis of phased mission systems

Systems often operate over a set of time periods, known as phases, in which their reliability structure varies and many include both repairable and nonrepairable components. Success for such systems is defined as the completion of all phases, known as a phased mission, without failure. An example of such a system is an aircraft landing gear system during a flight. The Binary Decision Diagram (BDD) method provides the most efficient solution to the unreliability of non-repairable systems whilst for repairable systems Markov or other state-space based methods have been most widely applied. For systems containing both repairable and non-repairable components the repairable modelling methods are normally used, despite having far higher computational expense than the non-repairable methods, since only they are able to handle the dependencies involved. This paper introduces improvements to the BDD method for analysing non-repairable systems as well as an entirely new method that utilises a new modelling technique involving both BDD and Markov techniques

Open String Star as a Continuous Moyal Product

We establish that the open string star product in the zero momentum sector can be described as a continuous tensor product of mutually commuting two dimensional Moyal star products. Let the continuous variable $\kappa \in [~0,\infty)$ parametrize the eigenvalues of the Neumann matrices; then the noncommutativity parameter is given by $\theta(\kappa) =2\tanh(\pi\kappa/4)$. For each $\kappa$, the Moyal coordinates are a linear combination of even position modes, and the Fourier transform of a linear combination of odd position modes. The commuting coordinate at $\kappa=0$ is identified as the momentum carried by half the string. We discuss the relation to Bars' work, and attempt to write the string field action as a noncommutative field theory.Comment: 30 pages, LaTeX. One reference adde

A reliability analysis method using binary decision diagrams in phased mission planning

The use of autonomous systems is becoming increasingly common in many fields. A significant example of this is the ambition to deploy unmanned aerial vehicles (UAVs) for both civil and military applications. In order for autonomous systems such as these to operate effectively, they must be capable of making decisions regarding the appropriate future course of their mission responding to changes in circumstance in as short a time as possible. The systems will typically perform phased missions and, owing to the uncertain nature of the environments in which the systems operate, the mission objectives may be subject to change at short notice. The ability to evaluate the different possible mission configurations is crucial in making the right decision about the mission tasks that should be performed in order to give the highest possible probability of mission success. Because binary decision diagrams (BDDs) may be quickly and accurately quantified to give measures of the system reliability it is anticipated that they are the most appropriate analysis tools to form the basis of a reliability-based prognostics methodology. The current paper presents a new BDD-based approach for phased mission analysis, which seeks to take advantage of the proven fast analysis characteristics of the BDD and enhance it in ways that are suited to the demands of a decision-making capability for autonomous systems. The BDD approach presented allows BDDs representing the failure causes in the different phases of a mission to be constructed quickly by treating component failures in different phases of the mission as separate variables. This allows flexibility when building mission phase failure BDDs because a global variable ordering scheme is not required. An alternative representation of component states in time intervals allows the dependencies to be efficiently dealt with during the quantification process. Nodes in the BDD can represent components with any number of failure modes or factors external to the system that could affect its behaviour, such as the weather. Path simplification rules and quantification rules are developed that allow the calculation of phase failure probabilities for this new BDD approach. The proposed method provides a phased mission analysis technique that allows the rapid construction of reliability models for phased missions and, with the use of BDDs, rapid quantification

Tunneling times with covariant measurements

We consider the time delay of massive, non-relativistic, one-dimensional particles due to a tunneling potential. In this setting the well-known Hartman effect asserts that often the sub-ensemble of particles going through the tunnel seems to cross the tunnel region instantaneously. An obstacle to the utilization of this effect for getting faster signals is the exponential damping by the tunnel, so there seems to be a trade-off between speedup and intensity. In this paper we prove that this trade-off is never in favor of faster signals: the probability for a signal to reach its destination before some deadline is always reduced by the tunnel, for arbitrary incoming states, arbitrary positive and compactly supported tunnel potentials, and arbitrary detectors. More specifically, we show this for several different ways to define ``the same incoming state'' and ''the same detector'' when comparing the settings with and without tunnel potential. The arrival time measurements are expressed in the time-covariant approach, but we also allow the detection to be a localization measurement at a later time.Comment: 12 pages, 2 figure

Modelling service support system reliability

Functional Products, where the customer pays for the function and availability of a product instead of the product itself, are increasingly popular in capital intensive industries such as aerospace. Such products are integrated systems involving the combination of hardware and service support systems. The reliability prediction and optimisation of the service system that supports the hardware availability is essential to the feasibility of the product. These systems consist of maintenance procedures and resource provisions. Simulation based techniques are presented in this paper to analyse the reliability of support systems and their application is demonstrated through a simple example

Modelling and simulation of functional product system availability and support costs

Functional Products (FP), total offers or product service systems that comprise of both Hardware (HW) and Support Services (SS) sold as an integrated offering under an availability guarantee are becoming increasing popular in industry. This paper addresses, through modelling and simulation the challenge faced by suppliers in developing an integrated HW and SS design to produce an FP which meets contracted availability. A recently published framework specified how an integrated model hardware and service support system model could be used to obtain functional availability predictions and perform simulation driven functional product development. This paper presents the first example of an integrated functional product model. It uses fault tree, Petri net and discrete event simulation techniques to enable the prediction of functional product availability and support costs. Such predictions are used here to evaluate and compare different service support system designs