The effect of statistics anxiety on students’ predicted and actual test scores

This study investigated the effect of statistics anxiety and attitudes on first year psychology students’ predicted and actual statistics class test scores. A total of 52 students completed the Statistics Anxiety Rating Scale and estimated their class test scores one week before their test at the end of first year. Regression models were conducted with the six attitude and anxiety subscales as predictors and the predicted and actual test scores as criterion variables. The results showed that computation self concept and fear of asking for help accounted for 37% of the variance in predicted test scores. However, when actual test scores were analysed the significant predictors were worth of statistics and interpretation anxiety, which accounted for 20% of the variance. These results suggested that while statistics anxiety does influence students’ perceptions of their competence it appears to have less effect on their actual performance. Results also suggested that students were unaware of their own statistical competence. Remedial action is required to address the level of statistics anxiety experienced by first year undergraduate psychology students, as it appears to result in unrealistic assessments of their ability and has detrimental effects on their statistics self-efficacy.

Short, medium and long term load forecasting model and virtual load forecaster based on radial basis neural networks

Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

Computer simulating a trial of a load-bearing implant: example of an intramedullary prosthesis

Computational modelling is becoming ever more important for obtaining regulatory approval for new medical devices. An accepted approach is to infer performance in a population from an analysis conducted for an idealised or ‘average’ patient; we present here a method for predicting the performance of an orthopaedic implant when released into a population—effectively simulating a clinical trial. Specifically we hypothesise that an analysis based on a method for predicting the performance in a population will lead to different conclusions than an analysis based on an idealised or ‘average’ patient. To test this hypothesis we use a finite element model of an intramedullary implant in a bone whose size and remodelling activity is different for each individual in the population. We compare the performance of a low Young’s modulus implant (View the MathML source) to one with a higher Young’s modulus (200 GPa). Cyclic loading is applied and failure is assumed when the migration of the implant relative to the bone exceeds a threshold magnitude. The analysis for an idealised of ‘average’ patient predicts that the lower modulus device survives longer whereas the analysis simulating a clinical trial predicts no statistically-significant tendency (p=0.77) for the low modulus device to perform better. It is concluded that population-based simulations of implant performance–simulating a clinical trial–present a very valuable opportunity for more realistic computational pre-clinical testing of medical devices.

The effect of construction pattern and unit interlock on the structural behaviour of block pavements

The maintenance or even replacement of cracked pavements requires considerable financial resources and puts a large burden on the budgets of local councils. In addition to these costs, local councils also face liability claims arising from uneven or cracked pedestrian pavements. These currently cost the Manchester City Council and Preston City Council around £6 million a year each. Design procedures are empirical. A better understanding of the interaction between paving blocks, bedding sand and subbase was necessary in order to determine the mode of failure of pavements under load. Increasing applied stress was found to mobilise ‘‘rotational interlock’’, providing increased pavement stiffness and thus increased load dissipation resulting in lower transmitted stress on the subgrade. The indications from the literature
review were that pavements are designed to fail by excessive deformation and that paving blocks remained uncracked at failure. This was confirmed with experimental data which was obtained from tests on segments of pavements that were laid/constructed in a purpose built test frame in the laboratory.

Effects of elevated temperatures on bolted moment-connections between cold-formed steel members

Experimental investigations at ambient temperature into the behaviour of bolted moment-connections between cold-formed steel members have previously been described. Full-scale joint tests have demonstrated that the channel-sections being connected are susceptible to premature failure, the result of web buckling caused by the concentration of load transfer from the bolts. The results of tests on bolted lap joints have been used to propose design recommendations for the shear strength in bearing of the bolt-hole. For both types of test, the results of non-linear elasto-plastic finite element analyses have been shown to have good agreement. No consideration, however, has been given to the behaviour of such connections at elevated temperatures. This paper describes non-linear elasto-plastic finite element parametric studies into the effects of elevated temperatures on bolted moment-connections between cold-formed steel members. Two issues at elevated temperatures are investigated:

The buffering effect of hope on clinicians' behavior:A test in pediatric primary care

Although trait hope is thought to motivate goal-directed actions in the face of impediments, few studies have directly examined hope's role in overcoming obstacles, and none have done so while accounting for related goal constructs. We describe a study of 127 pediatric primary care providers who over the course of a year were asked to identify new cases of asthma and confirm previously diagnosed active disease by completing for each of their patients a brief survey validated for this purpose. These clinicians also completed measures of hope, self-efficacy, conscientiousness, and perceived obstacles to implementing a pediatric asthma management program. As predicted by hope theory, the agency component of hope buffered clinicians from perceived obstacles by facilitating the identification of asthma cases among high-hope clinicians in the face of obstacles. This buffering effect remained after controlling for self-efficacy and conscientiousness. We discuss the study findings in terms of current theories of goal-directed behavior and implications for delivering hope-related interventions, and we offer a testable hypothesis regarding when agency and pathways thinking facilitate goal-related behavior.