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.

Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software

In this and a preceding paper, we provide an introduction to the Fujitsu VPP range of vector-parallel supercomputers and to some of the computational chemistry software available for the VPP. Here, we consider the implementation and performance of seven popular chemistry application packages. The codes discussed range from classical molecular dynamics to semiempirical and ab initio quantum chemistry. All have evolved from sequential codes, and have typically been parallelised using a replicated data approach. As such they are well suited to the large-memory/fast-processor architecture of the VPP. For one code, CASTEP, a distributed-memory data-driven parallelisation scheme is presented. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

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.

L-studio/cpfg: A software system for modeling plants

L-studio/cpfg is a plant modeling software system designed for Windows 95/98/NT platforms. Its key components are the L-system-based plant simulator cpfg and the modeling environment called L-studio. We overview version 1.0 of this system from the user's perspective.

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.

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.

Biomimetic in silico devices

We introduce biomimetic in silico devices, and means for validation along with methods for testing and refining them. The devices are constructed from adaptable software components designed to map logically to biological components at multiple levels of resolution. In this report we focus on the liver; the goal is to validate components that mimic features of the lobule (the hepatic primary functional unit) and dynamic aspects of liver behavior, structure, and function. An assembly of lobule-mimetic devices represents an in silico liver. We validate against outflow profiles for sucrose administered as a bolus to isolated, perfused rat livers. Acceptable in silico profiles are experimentally indistinguishable from those of the in situ referent. This new technology is intended to provide powerful Dew tools for challenging our understanding of how biological functional units function in vivo.

Laboratory wear testing of polyurethane elastomers

A dry sand-rubber wheel abrasion test was used to investigate the wear behaviour of polyurethanes. The dry sand-rubber wheel abrasion test (DSRW test) is an approved ASTM test designed primarily for testing metals, therefore, in this study the set of test conditions was optimized for use with polyurethane elastomers. The wear performance of polyurethanes was assessed for the range of Shore hardness 85A to 65D, and a correlation was identified between the wear rate and the sample hardness. Polyurethane elastomers can be separated into three classes according to their hardness and wear performance, and each class shows a different dependence on the specimen temperature. This work has implications for use of the DSRW test for the prediction of field performance of polyurethanes. (C) Elsevier Science S.A.

Testing market efficiency: Evidence from the NFL sports betting market

This article examines the efficiency of the National Football League (NFL) betting market. The standard ordinary least squares (OLS) regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows us to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In-sample tests indicate that probit-based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out-of-sample testing, there is some inconsistency among the remaining out-of-sample predictions. Our results also suggest that widely documented inefficiencies in this market tend to dissipate over time.