Fractal effects on the measurement of the specific surface areas of single-walled carbon nanotubes

The specific surface area (SSA) of single-walled carbon nanotubes (SWNTs) has been measured by different groups. Fujiwara et al. measured the SSA of SWNT bundles by using nitrogen and oxygen as adsorbates, and found that the SSA from O2-adsorption was 6.6% larger than that from N2-adsorption for the same SWNT sample [1]. Also Wei et al. [2] measured the SSA of HiPco SWNTs by using O2, N2 and Ar, and found that, for the same samples, Vm(Ar) > Vm(O2) > Vm(N2), here Vm is the monolayer adsorption capacity at the standard conditions of temperature and pressure (STP). Those research results indicate that, for the same SWNT sample, its measured surface area depends on the employed adsorbate.

Modelling knowledge production performance of research centres with a focus on triple bottom line benchmarking

We demonstrate a portable process for developing a triple bottom line model to measure the knowledge production performance of individual research centres. For the first time, this study also empirically illustrates how a fully units-invariant model of Data Envelopment Analysis (DEA) can be used to measure the relative efficiency of research centres by capturing the interaction amongst a common set of multiple inputs and outputs. This study is particularly timely given the increasing transparency required by governments and industries that fund research activities. The process highlights the links between organisational objectives, desired outcomes and outputs while the emerging performance model represents an executive managerial view. This study brings consistency to current measures that often rely on ratios and univariate analyses that are not otherwise conducive to relative performance analysis.

Animal production potential of some new Leucaena accessions in the Markham valley, Papua New Guinea

Signal grass pastures were oversown with four Leucaena spp. planted in hedgerows and evaluated for their agronomic productivity and ability to support steer liveweight gains. Each Leucaena sp. (L. leucocephala, L. pallida, L colli. nst. i., L. trichandra) was planted as seedlings into two I ha paddocks in rows 5 m apart, with I m spacing between trees. Cattle were rotationally grazed on the 2 replicates of each species, as well as on two I ha paddocks of a signal grass on y (Brachiaria decumbens) control, over a 243-day period at a stocking rate of 3 steers/ha. Mean presentation yield and herbage allowance of the Leucaena accessions over the grazing period were highest for L pallida (1100 kg/ha and 0.8 kg DM/kg LW, respectively), followed by L. leucocephala (700 kg/ha and 0.5 kg DM/kg LW), L. collinsii (700 kg/ha and 0.4 kg DM/kg LW) and L. trichandra (300 kg/ha and 0.2 kg DM/kg LW). Despite only moderate presentation yields and herbage allowances, steers grazing L. leucocephala and L. collinsii accessions produced the highest mean liveweight gains (LWG) of 0. and 0.56 kg/hd/d, respectively. While L. pallida produced the highest DM yields, it supported the lowest LWG of 0.36 kg/hd/d. The mean LWGs of steers grazing L. trichandra and the control (grass only) treatments were similar at 0.48 kg/ hd/d. The possible reasons for the differences in steer performance on the different Leucaena accessions are discussed.

Method for the synthesis of highly pure vaccines using the lipid core peptide system

Traditional vaccines consisting of whole attenuated microorganisms, killed microorganisms, or microbial components, administered with an adjuvant (e.g. alum), have been proved to be extremely successful. However, to develop new vaccines, or to improve upon current vaccines, new vaccine development techniques are required. Peptide vaccines offer the capacity to administer only the minimal microbial components necessary to elicit appropriate immune responses, minimizing the risk of vaccination associated adverse effects, and focusing the immune response toward important antigens. Peptide vaccines, however, are generally poorly immunogenic, necessitating administration with powerful, and potentially toxic adjuvants. The attachment of lipids to peptide antigens has been demonstrated as a potentially safe method for adjuvanting peptide epitopes. The lipid core peptide (LCP) system, which incorporates a lipidic adjuvant, carrier, and peptide epitopes into a single molecular entity, has been demonstrated to boost immunogenicity of attached peptide epitopes without the need for additional adjuvants. The synthesis of LCP systems normally yields a product that cannot be purified to homogeneity. The current study describes the development of methods for the synthesis of highly pure LCP analogs using native chemical ligation. Because of the highly lipophilic nature of the LCP lipid adjuvant, difficulties (e.g. poor solubility) were experienced with the ligation reactions. The addition of organic solvents to the ligation buffer solubilized lipidic species, but did not result in successful ligation reactions. In comparison, the addition of approximately 1% (w/v) sodium dodecyl sulfate (SDS) proved successful, enabling the synthesis of two highly pure, tri-epitopic Streptococcus pyogenes LCP analogs. Subcutaneous immunization of B10.BR (H-2(k)) mice with one of these vaccines, without the addition of any adjuvant, elicited high levels of systemic IgG antibodies against each of the incorporated peptides. Copyright (c) 2006 European Peptide Society and John Wiley & Sons, Ltd.

The effective management of geological risk in long-term production scheduling of open pit mines

Investment in mining projects, like most business investment, is susceptible to risk and uncertainty. The ability to effectively identify, assess and manage risk may enable strategic investments to be sheltered and operations to perform closer to their potential. In mining, geological uncertainty is seen as the major contributor to not meeting project expectations. The need to assess and manage geological risk for project valuation and decision-making translates to the need to assess and manage risk in any pertinent parameter of open pit design and production scheduling. This is achieved by taking geological uncertainty into account in the mine optimisation process. This thesis develops methods that enable geological uncertainty to be effectively modelled and the resulting risk in long-term production scheduling to be quantified and managed. One of the main accomplishments of this thesis is the development of a new, risk-based method for the optimisation of long-term production scheduling. In addition to maximising economic returns, the new method minimises the risk of deviating from production forecasts, given the understanding of the orebody. This ability represents a major advance in the risk management of open pit mining.

EM optimization of latent-variable density models

There is currently considerable interest in developing general non-linear density models based on latent, or hidden, variables. Such models have the ability to discover the presence of a relatively small number of underlying `causes' which, acting in combination, give rise to the apparent complexity of the observed data set. Unfortunately, to train such models generally requires large computational effort. In this paper we introduce a novel latent variable algorithm which retains the general non-linear capabilities of previous models but which uses a training procedure based on the EM algorithm. We demonstrate the performance of the model on a toy problem and on data from flow diagnostics for a multi-phase oil pipeline.