Weathering of hydrocarbons in mangrove sediments: testing the effects of using dispersants to treat oil spills

This field study was a combined chemical and biological investigation of the relative effects of using dispersants to treat oil spills impacting mangrove habitats. The aim of the chemistry was to determine whether dispersant affected the short- or long-term composition of a medium range crude oil (Gippsland) stranded in a tropical mangrove environment in Queensland, Australia. Sediment cores from three replicate plots of each treatment (oil only and oil plus dispersant) were analyzed for total hydrocarbons and for individual molecular markers (alkanes, aromatics, triterpanes, and steranes). Sediments were collected at 2 days, then 1, 7, 13 and 22 months post-spill. Over this time, oil in the six treated plots decreased exponentially from 36.6 +/- 16.5 to 1.2 +/- 0.8 mg/g dry wt. There was no statistical difference in initial oil concentrations, penetration of oil to depth, or in the rates of oil dissipation between oiled or dispersed oil plots. At 13 months, alkanes were >50% degraded, aromatics were similar to 30% degraded based upon ratios of labile to resistant markers. However, there was no change in the triterpane or sterane biomarker signatures of the retained oil. This is of general forensic interest for pollution events. The predominant removal processes were evaporation (less than or equal to 27%) and dissolution (greater than or equal to 56%), with a lag-phase of 1 month before the start of significant microbial degradation (less than or equal to 7%). The most resistant fraction of the oil that remained after 7 months (the higher molecular weight hydrocarbons) correlated with the initial total organic carbon content of the soil. Removal rate in the Queensland mangroves was significantly faster than that observed in the Caribbean and was related to tidal flushing. (C) 1999 Elsevier Science Ltd. All rights reserved.

The influence of supra-optimal root-zone temperatures on growth and stomatal conductance in Capsicum annuum L.

Pepper (Capsicum annuum L.) plants were grown aeroponically in a Singapore greenhouse under natural diurnally fluctuating ambient shoot temperatures, but at two different root-zone temperatures (RZTs): a constant 20 +/- 2 degrees C RZT and a diurnally fluctuating ambient (A) (25-40 degrees C) RZT, Plants grown at 20-RZT had more leaves, greater leaf area and dry weight than A-RZT plants. Reciprocal transfer experiments were conducted between RZTs to investigate the effect on plant growth, stomatal conductance (g(s)) and water relations. Transfer of plants from A-RZT to 20-RZT increased plant dry weight, leaf area, number of leaves, shoot water potential (Psi(shoot)), and g(s); while transfer of plants from 20-RZT to A-RZT decreased these parameters. Root hydraulic conductivity was measured in the latter transfer and decreased by 80% after 23 d at A-RZT. Transfer of plants from 20-RZT to A-RZT had no effect on xylem ABA concentration or xylem nitrate concentration, but reduced xylem sap pH by 0.2 units. At both RZTs, g(s) measured in the youngest fully expanded leaves increased with plant development. In plants with the same number of leaves, A-RZT plants had a higher g(s) than 20-RZT plants, but only under high atmospheric vapour pressure deficit. The roles of chemical signals and hydraulic factors in controlling g(s) of aeroponically grown Capsicum plants at different RZTs are discussed.

Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

A model of specification-based testing of interactive systems

In this paper we present a model of specification-based testing of interactive systems. This model provides the basis for a framework to guide such testing. Interactive systems are traditionally decomposed into a functionality component and a user interface component; this distinction is termed dialogue separation and is the underlying basis for conceptual and architectural models of such systems. Correctness involves both proper behaviour of the user interface and proper computation by the underlying functionality. Specification-based testing is one method used to increase confidence in correctness, but it has had limited application to interactive system development to date.

Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

Modelling socially optimal land allocations for sugar cane growing in North Queensland: a linked mathematical programming and choice modelling study

A modelling framework is developed to determine the joint economic and environmental net benefits of alternative land allocation strategies. Estimates of community preferences for preservation of natural land, derived from a choice modelling study, are used as input to a model of agricultural production in an optimisation framework. The trade-offs between agricultural production and environmental protection are analysed using the sugar industry of the Herbert River district of north Queensland as an example. Spatially-differentiated resource attributes and the opportunity costs of natural land determine the optimal tradeoffs between production and conservation for a range of sugar prices.

Impact of on-site testing for maternal syphilis on treatment delays, treatment rates, and perinatal mortality in rural South Africa: a randomised controlled trial

Background: Syphilis remains a significant cause of preventable perinatal death in developing countries with many women remaining untested and thus untreated. Syphilis testing in the clinic (on-site testing) may be a useful strategy to overcome this. We studied the impact of on-site syphilis testing on treatment delays and rates, and perinatal mortality. Methods: We conducted a cluster randomised controlled trial among seven pairs of primary healthcare clinics in rural South Africa, comparing on-site testing complemented by laboratory confirmation versus laboratory testing alone. Intervention clinics used the on-site test conducted by primary care nurses, with results and treatment available within an hour. Control clinics sent blood samples to the provincial laboratory, with results returned 2 weeks later. Results: Of 7134 women seeking antenatal care with available test results, 793 (11.1%) tested positive for syphilis. Women at intervention clinics completed treatment 16 days sooner on average (95% confidence interval: 11 to 21), though there was no significant difference in the proportion receiving adequate treatment at intervention (64%) and control (69%) clinics. There was also no significant difference in the proportion experiencing perinatal loss (3.3% v 5.1%; adjusted risk difference: -0.9%; 95% Cl -4.4 to 2.7). Conclusions: Despite reducing treatment delays, the addition of on-site syphilis testing to existing laboratory testing services did not lead to higher treatment rates or reduce perinatal mortality. However on-site testing for syphilis may remain an important option for improving antenatal care in settings where laboratory facilities are not available.

Testing hypotheses about the relationship between cannabis use and psychosis

Aim: To model the impact of rising rates of cannabis use on the incidence and prevalence of psychosis under four hypotheses about the relationship between cannabis use and psychosis. Methods: The study modelled the effects on the prevalence of schizophrenia over the lifespan of cannabis in eight birth cohorts: 1940-1944, 1945-1949, 1950-1954, 1955-1959, 1960-1964, 1965-1969, 1970-1974, 1975-1979. It derived predictions as to the number of cases of schizophrenia that would be observed in these birth cohorts, given the following four hypotheses: (1) that there is a causal relationship between cannabis use and schizophrenia; (2) that cannabis use precipitates schizophrenia in vulnerable persons; (3) that cannabis use exacerbates schizophrenia; and (4) that persons with schizophrenia are more liable to become regular cannabis users. Results: There was a steep rise in the prevalence of cannabis use in Australia over the past 30 years and a corresponding decrease in the age of initiation of cannabis use. There was no evidence of a significant increase in the incidence of schizophrenia over the past 30 years. Data on trends the age of onset of schizophrenia did not show a clear pattern. Cannabis use among persons with schizophrenia has consistently been found to be more common than in the general population. Conclusions: Cannabis use does not appear to be causally related to the incidence of schizophrenia, but its use may precipitate disorders in persons who are vulnerable to developing psychosis and worsen the course of the disorder among those who have already developed it. (C) 2003 Elsevier Science Ireland Ltd. All rights reserved.

Debt Maturity: Is Long-Term Debt Optimal?

We model and calibrate the arguments in favor and against short-term and long-term debt. These arguments broadly include: maturity premium, sustainability, and service smoothing. We use a dynamic-equilibrium model with tax distortions and government outlays uncertainty, and model maturity as the fraction of debt that needs to be rolled over every period. In the model, the benefits of defaulting are tempered by higher future interest rates. We then calibrate our artificial economy and solve for the optimal debt maturity for Brazil as an example of a developing country and the US as an example of a mature economy. We obtain that the calibrated costs from defaulting on long-term debt more than offset costs associated with short-term debt. Therefore, short-term debt implies higher welfare levels.

Optimal reserve management and sovereign debt

Most models currently used to determine optimal foreign reserve holdings take the level of international debt as given. However, given the sovereign`s willingness-to-pay incentive problems, reserve accumulation may reduce sustainable debt levels. In addition, assuming constant debt levels does not allow addressing one of the puzzles behind using reserves as a means to avoid the negative effects of crisis: why do not sovereign countries reduce their sovereign debt instead? To study the joint decision of holding sovereign debt and reserves, we construct a stochastic dynamic equilibrium model calibrated to a sample of emerging markets. We obtain that the reserve accumulation does not play a quantitatively important role in this model. In fact, we find the optimal policy is not to hold reserves at all. This finding is robust to considering interest rate shocks, sudden stops, contingent reserves and reserve dependent output costs. (c) 2008 Elsevier B.V. All rights reserved.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.