The effect of defendant gender on juror decision-making

Research investigating the role of stereotypes in jury decision-making has typically considered stereotypes as acting as peripheral cues in determin ing the credibility of experts or likelihood of guilt of defendants — with counter-stereotypic courtroom participants faring less well. The present study investigated the possibility that the extent to which courtroom participants are stereotypic can alter the mode of information processing. Students (N = 78) read a transcript of a case in which either a male or female allegedly committed an armed robbery. As predicted, the female counter-stereotypic defendant was distracting and effortful processing only occurred when the defendant was male. The male was seen as more guilty and the prosecution's case was more convincing when the prosecution had a strong, but not weak, case. There were no effects of case strength for the female defendant. Results are discussed in terms of the role of stereotypes in the jury decision-making.

Spatial distribution of pink wax scale, Ceroplastes rubens Maskell (Hemiptera: Coccidae), on umbrella trees in south-eastern Queensland: The pattern of outbreaks

The spatial pattern of outbreaks of pink wax scale, Ceroplastes rubens Maskell, within and among umbrella trees, Schefflera actinophylla (Endl.), in southeastern Queensland was investigated. Pink wax scale was common on S. actinophylla, with approximately 84% of trees positive for scale and 14% of bees recording outbreak densities exceeding 0.4 adults per leaflet. Highly aggregated distributions of C. rubens occur within and among umbrella trees. Clumped distributions within trees appear to result from variable birth and death rates and limited movement of first instar crawlers. The patchy distribution of pink wax scale among trees is probably a consequence of variation in dispersal success of scale, host and environmental suitability for establishment and rates of biological control. Pink wax scale was more prevalent on trees in roadside positions and in exposed situations, indicating that such trees are more suitable and/or susceptible to scale colonisation.

Variation in length, fecundity and survival of pink wax scale, Ceroplastes rubens Maskell (Hemiptera: Coccidae), on umbrella trees

We investigated some of the factors that may lead to outbreaks of pink wax scale, Ceroplastes rubens Maskell, on umbrella trees, Schefflera actinophylla (Endl.). Estimates of birth and death rates of pink wax scale were high and variable within and among trees; variation in these rates was not related to scale density. Adult fecundity correlated significantly but weakly with adult test length; mean fecundity was 292 eggs per female with a range of 5-1178. Adult test length and its variance decreased weakly with increasing density. Field experiments showed that mortality of C. rubens is greatest during the first 24 hours after hatching when approximately half disappear. The rate of loss decreases over time with 0.3% of initial motile first-instar nymphs surviving to maturity. Rates of loss varied significantly between trees, indicating that some trees are more suitable for scale colonisation and survival.

Decision-Making Deficits Linked to Real-life Social Dysfunction in Crack Cocaine-Dependent Individuals

Crack cocaine-dependent individuals (CCDI) present abnormalities in both social adjustment and decision making, but few studies have examined this association. This study investigated cognitive and social performance of 30 subjects (CCDI x controls); CCDI were abstinent for 2 weeks. We used the Social Adjustment Scale (SAS), Wisconsin Card Sorting Test (WCST), and Iowa Gambling Task (IGT). Disadvantageous choices on the IGT were associated with higher levels of social dysfunction in CCDI, suggesting the ecological validity of the IGT. Social dysfunction and decision making may be linked to the same underlying prefrontal dysfunction, but the nature of this association should be further investigated. (Am J Addict 2010;00: 1-9).

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.