Mutation rates in the dihydrofolate reductase gene of Plasmodium falciparum

A new method has been established to define the limits on a spontaneous mutation rate for a gene in Plasmodium falciparum. The method combines mathematical modelling and large-scale in vitro culturing and calculates the difference in mutant frequencies at 2 separate time-points. We measured the mutation rate at 2 positions in the dihydrofolate reductase (DHFR) gene of 3D7, a pyrimethamine-sensitive line of P. fulciparum. This line was re-cloned and an effectively large population was treated with a selective pyrimethamine concentration of 40 nM. We detected point mutations at codon-46 (TTA to TCA) and codon-108 (ACC to AAC), resulting in serine replacing leucine and asparagine replacing serine respectively in the corresponding gene product. The substitutions caused a decrease in pyrimethamine sensitivity. By mathematical modelling we determined that the mutation rate at a given position in DHFR was low and occurred at less than 2(.)5 x 10(-9) mutations/DHFR gene/replication. This result has important implications for Plasmodium genetic diversity and antimalarial drug therapy by demonstrating that even with lon mutation rates anti-malarial resistance will inevitably arise when mutant alleles are selected under drug pressure.

Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.

A comparison of thermal condition between pilot- and full-scale furnaces for studying slagging and fouling propensity in PF boilers

The Australian Coal Industry Research Laboratory (ACIRL) furnace is scaled to simulate slagging and fouling in operating boilers. This requires that the gas and target temperatures, the heat flux, and the flow pattern be the same as those in real boilers. The gas and target temperatures are maintained by insulating the wall and cooling the target respectively. The flow pattern of a small burner cannot be the same as a large furnace. However, this flow pattern is partially compensated for by placing the slagging panels in three vertical locations. The paper develops the models of radiant heat transfer from the flame to the deposits both in pilot-scale and full-scale furnaces. They are used to compare the effective radiant heat transfer of the pilot- and full-scale furnaces. The experimental data both from the pilot- and full-scale furnaces are used to verify the incident heat flux and temperature profiles in the pilot- and full-scale furnaces. The results showed that the thermal condition in the pilot-scale furnace meets the requirements for studying the slagging regarding the gas temperature and the incident heat flux, particularly for the panel #1. The gas temperature in the convective section also meets the requirement for studying the fouling.

Discrimination of adsorption kinetic models for the description of hydrocarbon adsorption in activated carbon

Five kinetic models for adsorption of hydrocarbons on activated carbon are compared and investigated in this study. These models assume different mass transfer mechanisms within the porous carbon particle. They are: (a) dual pore and surface diffusion (MSD), (b) macropore, surface, and micropore diffusion (MSMD), (c) macropore, surface and finite mass exchange (FK), (d) finite mass exchange (LK), and (e) macropore, micropore diffusion (BM) models. These models are discriminated using the single component kinetic data of ethane and propane as well as the multicomponent kinetics data of their binary mixtures measured on two commercial activated carbon samples (Ajax and Norit) under various conditions. The adsorption energetic heterogeneity is considered for all models to account for the system. It is found that, in general, the models assuming diffusion flux of adsorbed phase along the particle scale give better description of the kinetic data.

Investigating technical and scale efficiencies of Australian universities through data envelopment analysis

Performance indicators in the public sector have often been criticised for being inadequate and not conducive to analysing efficiency. The main objective of this study is to use data envelopment analysis (DEA) to examine the relative efficiency of Australian universities. Three performance models are developed, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments. The findings based on 1995 data show that the university sector was performing well on technical and scale efficiency but there was room for improving performance on fee-paying enrolments. There were also small slacks in input utilisation. More universities were operating at decreasing returns to scale, indicating a potential to downsize. DEA helps in identifying the reference sets for inefficient institutions and objectively determines productivity improvements. As such, it can be a valuable benchmarking tool for educational administrators and assist in more efficient allocation of scarce resources. In the absence of market mechanisms to price educational outputs, which renders traditional production or cost functions inappropriate, universities are particularly obliged to seek alternative efficiency analysis methods such as DEA.

Integrated treatment of shrimp effluent by sedimentation, oyster filtration and macroalgal absorption: a laboratory scale study

Effluent water from shrimp ponds typically contains elevated concentrations of dissolved nutrients and suspended particulates compared to influent water. Attempts to improve effluent water quality using filter feeding bivalves and macroalgae to reduce nutrients have previously been hampered by the high concentration of clay particles typically found in untreated pond effluent. These particles inhibit feeding in bivalves and reduce photosynthesis in macroalgae by increasing effluent turbidity. In a small-scale laboratory study, the effectiveness of a three-stage effluent treatment system was investigated. In the first stage, reduction in particle concentration occurred through natural sedimentation. In the second stage, filtration by the Sydney rock oyster, Saccostrea commercialis (Iredale and Roughley), further reduced the concentration of suspended particulates, including inorganic particles, phytoplankton, bacteria, and their associated nutrients. In the final stage, the macroalga, Gracilaria edulis (Gmelin) Silva, absorbed dissolved nutrients. Pond effluent was collected from a commercial shrimp farm, taken to an indoor culture facility and was left to settle for 24 h. Subsamples of water were then transferred into laboratory tanks stocked with oysters and maintained for 24 h, and then transferred to tanks containing macroalgae for another 24 h. Total suspended solid (TSS), chlorophyll a, total nitrogen (N), total phosphorus (P), NH4+, NO3-, and PO43-, and bacterial numbers were compared before and after each treatment at: 0 h (initial); 24 h (after sedimentation); 48 h (after oyster filtration); 72 h (after macroalgal absorption). The combined effect of the sequential treatments resulted in significant reductions in the concentrations of all parameters measured. High rates of nutrient regeneration were observed in the control tanks, which did not contain oysters or macroalgae. Conversely, significant reductions in nutrients and suspended particulates after sedimentation and biological treatment were observed. Overall, improvements in water quality (final percentage of the initial concentration) were as follows: TSS (12%); total N (28%); total P (14%); NH4+ (76%); NO3- (30%); PO43-(35%); bacteria (30%); and chlorophyll a (0.7%). Despite the probability of considerable differences in sedimentation, filtration and nutrient uptake rates when scaled to farm size, these results demonstrate that integrated treatment has the potential to significantly improve water quality of shrimp farm effluent. (C) 2001 Elsevier Science B.V. All rights reserved.

Psychometric evaluation of the Early/Late Preferences Scale

This paper examines the psychometric quality of the Early/Late Preferences Scale (PS) relative to that of the Composite Morningness Scale (CS). Questionnaires were completed by 670 undergraduate students aged 16-37 years (mean 22.5), of whom 64% were female. Both scales displayed satisfactory inter-item correlations and similar total mean scores to those reported previously, although the CS had higher variability. Principal axis factor analysis produced single-factor solutions for both scales, although loadings for Items 7 and 9 on the PS were low. Internal consistencies for both scales were good (PS=0.86, CS=0.90) with only a small improvement achieved by deleting Items 7 and 9 from the PS. Test-retest reliability over 11 weeks was good for both scales (PS=0.92, CS=0.89). Differences between morning, evening and intermediate groups in self-rated alertness at different times of day, and significant correlations with other indices of morning-evening orientation, provided evidence of validity for both scales. These results indicate that PS is psychometrically comparable with CS. In view of its simpler format and lower cultural specificity, PS may be considered a preferable measure for most applications.

The Alcohol Helplessness Scale and its prediction of depression among problem drinkers

Event-specific scales commonly have greater power than generalized scales in prediction of specific disorders and in testing mediator models for predicting such disorders. Therefore, in a preliminary study, a 6-item Alcohol Helplessness Scale was constructed and found to be reliable for a sample of 98 problem drinkers. Hierarchical multiple regression and its derivative path analysis were used to test whether helplessness and self-efficacy moderate or mediate the link between alcohol dependence and depression, A test of a moderation model was not supported, whereas a test of a mediation model was supported. Helplessness and self-efficacy both significantly and independently mediated between alcohol dependence and depression. Nevertheless, a significant direct effect of alcohol dependence on depression also remained, (C) 2001 John Wiley & Sons, Inc.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

Validation of the Edinburgh Postnatal Depression Scale for men, and comparison of item endorsement with their partners

Background: The Edinburgh Postnatal Depression Scale (EPDS) has been validated and used extensively in screening for depression in new mothers, both in English speaking and non-English speaking communities. While some studies have reported the use of the EPDS with Fathers, none have validated it for this group, and thus the appropriate cut-off score for screening for depression or anxiety caseness for this population is not known. Method: Couples were recruited antenatally and interviewed at six weeks postpartum. EPDS scores and distress caseness (depression or anxiety disorders) for 208 fathers and 230 mothers were determined using the Diagnostic Interview Schedule. Results: Analyses of the EPDS for fathers using distress caseness (depression or anxiety disorders) as the criterion shows that a cut-off of 5/6 has optimum receiver operating characteristics. Furthermore acceptable reliability (split-half and internal consistency) and validity (concurrent) coefficients were obtained. For mothers the optimum cut-off screening value to detect distress caseness was 7/8. Item analysis revealed that fathers endorsed seven of the ten items at lower rates to mothers, with the most significant being that referring to crying. Conclusions: The EPDS is a reliable and valid measure of mood in fathers. Screening for depression or anxiety disorders in fathers requires a two point lower cut-off than screening for depression or anxiety in mothers, and we recommend this cut-off to he 5/6. (C) 2001 Elsevier Science B.V. All rights reserved.

The influence of calcium on granular sludge in a full-scale UASB treating paper mill wastewater

Calcium precipitation can have a number of effects on the performance of high-rate anaerobic performance including cementing of the sludge bed, limiting diffusion, and diluting the active biomass. The aim of this study was to observe the influence of precipitation in a stable full-scale system fed with high-calcium paper factory wastewater. Granules were examined from an upflow anaerobic sludge blanket reactor (volume 1,805 m(3)) at a recycled paper mill with a loading rate of 5.7-6.6 kgCOD.m(-3).d(-1) and influent calcium concentration of 400-700 gCa(.)m(-3). The granules were relatively small (1 mm), with a 200-400 mum core of calcium precipitate as observed with energy dispersive X-ray spectroscopy. Compared to other granules, Methanomicrobiales not Methanobacteriales were the dominant hydrogen or formate utilisers, and putative acidogens were filamentous. The strength of the paper mill fed granules was very high when compared to granules from other full-scale reactors, and a partial linear correlation between granule strength and calcium concentration was identified.