A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production

Oleaginous microorganisms have potential to be used to produce oils as alternative feedstock for biodiesel production. Microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) were investigated for their ability to produce oil from glucose, xylose and glycerol. Multi-criteria analysis (MCA) using analytic hierarchy process (AHP) and preference ranking organization method for the enrichment of evaluations (PROMETHEE) with graphical analysis for interactive aid (GAIA), was used to rank and select the preferred microorganisms for oil production for biodiesel application. This was based on a number of criteria viz., oil concentration, content, production rate and yield, substrate consumption rate, fatty acids composition, biomass harvesting and nutrient costs. PROMETHEE selected A. oryzae, M. plumbeus and R. mucilaginosa as the most prospective species for oil production. However, further analysis by GAIA Webs identified A. oryzae and M. plumbeus as the best performing microorganisms.

Business process modeling : perceived benefits

The process-centered design of organizations and information systems is globally seen as an appropriate response to the increased economic pressure on organizations. At the methodological core of process-centered management is process modeling. However, business process modeling in large initiatives can be a time-consuming and costly exercise, making it potentially difficult to convince executive management of its benefits. To date, and despite substantial interest and research in the area of process modeling, the understanding of the actual benefits of process modeling in academia and practice is limited. To address this gap, this paper explores the perception of benefits derived from process modeling initiatives, as reported through a global Delphi study. The study incorporates the views of three groups of stakeholders – academics, practitioners and vendors. Our findings lead to the first identification and ranking of 19 unique benefits associated with process modeling. The study in particular found that process modeling benefits vary significantly between practitioners and academics. We argue that these variations may point to a dangerous disconnect between research projects and practical demands.

Who is publishing in the Journal of Sociology? an analysis of author trends 1965–2008

This paper presents the author characteristics of papers published in The Australian Sociological Association (TASA) journal, the Journal of Sociology (formerly the Australian and New Zealand Journal of Sociology) between 1965 and 2008. The aim of the paper is empirically to identify trends in authorship. The review examines all articles published in the period (excluding book reviews). The rationale of the study is to reveal trends in who publishes in the journal in terms of authors’ academic rank, gender, institution, and country. A table of those who have published the greatest number of papers is also presented. Findings show that over time the gap between the proportion of males and females publishing has closed; more PhD students and research fellows are publishing in the journal in recent decades; the highest proportion of authors consistently come from the Australian National University and The University of Queensland; and most authors are located in Australia. Information such as this can inform editorial practices and serve to inform the membership and readership on the nature of the journal.

A fuzzy neural network approach for contractor pre-qualification

Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.

Wear mechanisms and scale effects in two-body abrasion

The ‘particle size effect’ and its manifestation in abrasion still attracts considerable debate as to its origins and the ranking of its likely causes. Experiments have been conducted to study the important contribution that the formation of wear debris can have on the progression of wear. The experiments consist of unlubricated (dry) pin-on-disk tests with silicon carbide coated paper of varying particle size, with different pin material, diameter and loads. It has been observed that the influence of debris formation on wear rate is more pronounced for fine abrasives and soft-wearing materials. Consequently, it is proposed that the particle size effect can be explained in terms of geometrical scaling and the evolution of third-body effects with diminishing particle diameter.

Identification of factors predicting clickthrough in Web searching using neural network analysis

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing

Discrepancies between metabolic activity and DNA content as tool to assess cell proliferation in cancer research

Cell proliferation is a critical and frequently studied feature of molecular biology in cancer research. Therefore, various assays are available using different strategies to measure cell proliferation. Metabolic assays such as AlamarBlue, WST-1, and MTT, which were originally developed to determine cell toxicity, are being used to assess cell numbers. Additionally, proliferative activity can be determined by quantification of DNA content using fluorophores, such as CyQuant and PicoGreen. Referring to data published in high ranking cancer journals, 945 publications applied these assays over the past 14 years to examine the proliferative behaviour of diverse cell types. Within this study, mainly metabolic assays were used to quantify changes in cell growth yet these assays may not accurately reflect cellular proliferation rates due to a miscorrelation of metabolic activity and cell number. Testing this hypothesis, we compared metabolic activity of different cell types, human cancer cells and primary cells, over a time period of 4 days using AlamarBlue and fluorometric assays CyQuant and PicoGreen to determine their DNA content. Our results show certain discrepancies in terms of over-estimation of cell proliferation with respect to the metabolic assay in comparison to DNA binding fluorophores.

Interdisciplinary modelling

This article examines one approach to promoting creative and flexible use of mathematical ideas within an interdisciplinary context in the primary curriculum, namely, through modelling. Three classes of fifth-grade children worked on a modelling problem, The First Fleet (Australia’s settlement), situated within the curriculum domains of science and studies of society and environment. Reported here are the cycles of development displayed by one group of children as they worked the problem, together with the range of models created across the classes. Children developed mathematisation processes that extended beyond their regular curriculum, including identifying and prioritising key problem elements, exploring relationships among elements, quantifying qualitative data, ranking and aggregating data, and creating and working with weighted scores. Aspects of Goldin’s (2000, 2007) affective structures also appeared to play an important role in the children's mathematical developments.

The economics of the FIFA Football World Cup

The expansion of economics to ‘non-market topics’ has received increased attention in recent years. The economics of sports (football) is such a sub-field. This paper reports empirical evidence of team and referee performances in the FIFA World Cup 2002. The results reveal that being a hosting nation has a significant impact on the probability of winning a game. Furthermore, the strength of a team measured with the FIFA World Ranking does not play the important role presumed, which indicates that the element of uncertainty is working. The findings also indicate that the influence of a referee on the game result should not be neglected. Finally, the previous World Cup experiences seem to have the strongest impact on referees' performances during the game.