Ileal digestibility of amino acids in feed ingredients for broilers.

To more precisely formulate feed and predict animal performance, it is important to base both the recommendations and feed formulations on digestible rather than total amino acid contents. Most published data on the digestibility of amino acids in feed ingredients for poultry are based on excreta digestibility. Ileal digestibility is an alternative and preferred approach to estimate amino acid availability in feed ingredients. Both methodologies are described and assessed. In addition, the differences between apparent and standardised (in which corrections are made for basal endogenous losses) digestible amino acid systems are discussed. The concept of a standardised digestibility system as a mean of overcoming the limitations of apparent digestibility estimates is proposed. In this context, different methodologies for the determination of basal endogenous amino acid losses are discussed. Although each methodology suffers from some limitations and published data on endogenous losses at the ileal level in growing poultry are limited, averaged data from repeated experiments using the 'enzymatically hydrolysed casein' method are considered as the best measure of basal losses. Standardised ileal amino acid digestibility values of 17 feed ingredients commonly used in broiler nutrition are presented including grains (barley, corn, sorghum, triticale, wheat), grain by-products (wheat middlings, rice pollard), plant protein sources (soybean meal, canola meal, corn gluten meal, cottonseed meal, lupins, peas/beans, sunflower meal), and animal by-products (feather meal, fish meal, meat and bone meal). This comprehensive set of the ileal amino acid digestibility of feed ingredients in broiler nutrition may serve as a basis for the establishment of the system in broiler feeding and for further research.

Construction of representative transcript and protein sets of human, mouse, and rat as a platform for their transcriptome and proteome analysis

The number of mammalian transcripts identified by full-length cDNA projects and genome sequencing projects is increasing remarkably. Clustering them into a strictly nonredundant and comprehensive set provides a platform for functional analysis of the transcriptome and proteome, but the quality of the clustering and predictive usefulness have previously required manual curation to identify truncated transcripts and inappropriate clustering of closely related sequences. A Representative Transcript and Protein Sets (RTPS) pipeline was previously designed to identify the nonredundant and comprehensive set of mouse transcripts based on clustering of a large mouse full-length cDNA set (FANTOM2). Here we propose an alternative method that is more robust, requires less manual curation, and is applicable to other organisms in addition to mouse. RTPSs of human, mouse, and rat have been produced by this method and used for validation. Their comprehensiveness and quality are discussed by comparison with other clustering approaches. The RTPSs are available at ftp://fantom2.gsc.riken.go.jp/RTPS/. (C). 2004 Elsevier Inc. All rights reserved.

Towards realistic simulations of lava dome growth using the level set method

The level set method has been implemented in a computational volcanology context. New techniques are presented to solve the advection equation and the reinitialisation equation. These techniques are based upon an algorithm developed in the finite difference context, but are modified to take advantage of the robustness of the finite element method. The resulting algorithm is tested on a well documented Rayleigh–Taylor instability benchmark [19], and on an axisymmetric problem where the analytical solution is known. Finally, the algorithm is applied to a basic study of lava dome growth.

Review of recent results on excursion set models

Many images consist of two or more 'phases', where a phase is a collection of homogeneous zones. For example, the phases may represent the presence of different sulphides in an ore sample. Frequently, these phases exhibit very little structure, though all connected components of a given phase may be similar in some sense. As a consequence, random set models are commonly used to model such images. The Boolean model and models derived from the Boolean model are often chosen. An alternative approach to modelling such images is to use the excursion sets of random fields to model each phase. In this paper, the properties of excursion sets will be firstly discussed in terms of modelling binary images. Ways of extending these models to multi-phase images will then be explored. A desirable feature of any model is to be able to fit it to data reasonably well. Different methods for fitting random set models based on excursion sets will be presented and some of the difficulties with these methods will be discussed.

Concepts and tools for comprehensive sustainability assessments for tourism destinations: a comparative review

This paper reviews a wide range of tools for comprehensive sustainability assessments at whole tourism destinations, covering socio-cultural, economic and environmental issues. It considers their strengths, weaknesses and site specific applicability. It is intended to facilitate their selection (and combination where necessary). Tools covered include Sustainability Indicators, Environmental Impact Assessment, Life Cycle Assessment, Environmental Audits, Ecological Footprints, Multi-Criteria Analysis and Adaptive Environmental Assessment. Guidelines for evaluating their suitability for specific sites and situations are given as well as examples of their use.

Using the level set method to model endogenous lava dome growth

Modeling volcanic phenomena is complicated by free-surfaces often supporting large rheological gradients. Analytical solutions and analogue models provide explanations for fundamental characteristics of lava flows. But more sophisticated models are needed, incorporating improved physics and rheology to capture realistic events. To advance our understanding of the flow dynamics of highly viscous lava in Peléean lava dome formation, axi-symmetrical Finite Element Method (FEM) models of generic endogenous dome growth have been developed. We use a novel technique, the level-set method, which tracks a moving interface, leaving the mesh unaltered. The model equations are formulated in an Eulerian framework. In this paper we test the quality of this technique in our numerical scheme by considering existing analytical and experimental models of lava dome growth which assume a constant Newtonian viscosity. We then compare our model against analytical solutions for real lava domes extruded on Soufrière, St. Vincent, W.I. in 1979 and Mount St. Helens, USA in October 1980 using an effective viscosity. The level-set method is found to be computationally light and robust enough to model the free-surface of a growing lava dome. Also, by modeling the extruded lava with a constant pressure head this naturally results in a drop in extrusion rate with increasing dome height, which can explain lava dome growth observables more appropriately than when using a fixed extrusion rate. From the modeling point of view, the level-set method will ultimately provide an opportunity to capture more of the physics while benefiting from the numerical robustness of regular grids.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

A comprehensive study on carbon dioxide reforming of methane over Ni/gamma-Al2O3 catalysts

Carbon dioxide reforming of methane into syngas over Ni/gamma-Al2O3 catalysts was systematically studied. Effects of reaction parameters on catalytic activity and carbon deposition over Ni/gamma-Al2O3 catalysts were investigated. It is found that reduced NiA1204, metal nickel, and active species of carbon deposited were the active sites for this reaction. Carbon deposition on Ni/gamma Al2O3 varied depending on the nickel loading and reaction temperature and is the major cause of catalyst deactivation. Higher nickel loading produced more coke on the catalysts, resulting in rapid deactivation and plugging of the reactor. At 5 wt % Ni/gamma-Al2O3 catalyst exhibited high activity and much lesser magnitude of deactivation in 140 h. Characterization of carbon deposits on the catalyst surface revealed that there are two kinds of carbon species (oxidized and -C-C-) formed during the reaction and they showed different reactivities toward hydrogenation and oxidation. Kinetic studies showed that the activation energy for CO production in this reaction amounted to 80 kJ/mol and the rate of CO production could be described by a Langmuir-Hinshelwood model.

An "openable," high-strength gradient set for orthopedic MRI

A novel three-axis gradient set and RF resonator for orthopedic MRT has been designed and constructed. The set is openable and may be wrapped around injured joints. The design methodology used was the minimization of magnetic field spherical harmonics by simulated annealing. Splitting of the longitudinal coil presents the major design challenge to a fully openable gradient set and in order to efficiently design such coils, we have developed a new fast algorithm for determining the magnetic field spherical harmonics generated by an are of multiturn wire. The algorithm allows a realistic impression of the effect of split longitudinal designs. A prototype set was constructed based on the new designs and tested in a 2-T clinical research system. The set generated 12 mT/m/A with a linear region of 12 cm and a switching time of 100 mu s, conforming closely with theoretical predictions. Preliminary images from the set are presented. (C) 1999 Academic Press.

Designs for an asymmetric gradient set and a compact superconducting magnet for neural magnetic resonance imaging

Imaging of the head and neck is the most commonly performed clinical magnetic resonance imaging (MRI) examination [R. G. Evans and J. R. G. Evans, AJR 157, 603 (1991)]. This is usually undertaken in a generalist MRI instrument containing superconducting magnet system capable of imaging all organs. These generalist instruments are large, typically having a bore of 0.9-1.0 m and a length of 1.7-2.5 m and therefore are expensive to site, somewhat claustrophobic to the patient, and offer little access by attending physicians. In this article, we present the design of a compact, superconducting MRI magnet for head and neck imaging that is less than 0.8 m in length and discuss in detail the design of an asymmetric gradient coil set, tailored to the magnet profile. In particular, the introduction of a radio-frequency FM modulation scheme in concert with a gradient sequence allows the epoch of the linear region of the gradient set to be much closer to the end of the gradient structure than was previously possible. Images from a prototype gradient set demonstrate the effectiveness of the designs. (C) 1999 American Institute of Physics. [S0034-6748(99)04910-2].