Recognition memory effects in event-based prospective memory

Prospective memory (ProM) is the memory for future actions. It requires retrieving content of anaction in response to an ambiguous cue. Currently, it is unclear if ProM is a distinct form of memory, or merely a variant of retrospective memory (RetM). While content retrieval in ProM appears analogous to conventional RetM, less is known about the process of cue detection. Using a modified version of the standard ProM paradigm, three experiments manipulated stimulus characteristics known to influence RetM, in order to examine their effects on ProM performance. Experiment 1 (N — 80) demonstrated that low frequency stimuli elicited significantly higher hit rates and lower false alarm rates than high frequency stimuli, comparable to the mirror effect in RetM. Experiment 2 (N = 80) replicated these results, and showed that repetition of distracters during the test phase significantly increased false alarm rates to second and subsequent presentations of low frequency distracters. Building on these results. Experiment 3 (AT = 40) showed that when the study list was strengthened, the repeated presentation of targets and distracters did not significantly affect response rates. These experiments demonstrate more overlap between ProM and RetM than has previously been acknowledged. The implications for theories of ProM are considered.

Model-Driven safety evaluation with state-event-based component failure annotations

Over the past years, the paradigm of component-based software engineering has been established in the construction of complex mission-critical systems. Due to this trend, there is a practical need for techniques that evaluate critical properties (such as safety, reliability, availability or performance) of these systems. In this paper, we review several high-level techniques for the evaluation of safety properties for component-based systems and we propose a new evaluation model (State Event Fault Trees) that extends safety analysis towards a lower abstraction level. This model possesses a state-event semantics and strong encapsulation, which is especially useful for the evaluation of component-based software systems. Finally, we compare the techniques and give suggestions for their combined usage

Seizure detection algorithm for neonates based on wave-sequence analysis

Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

Formal analysis of human-computer interaction using model checking

Experiments with simulators allow psychologists to better understand the causes of human errors and build models of cognitive processes to be used in human reliability assessment (HRA). This paper investigates an approach to task failure analysis based on patterns of behaviour, by contrast to more traditional event-based approaches. It considers, as a case study, a formal model of an air traffic control (ATC) system which incorporates controller behaviour. The cognitive model is formalised in the CSP process algebra. Patterns of behaviour are expressed as temporal logic properties. Then a model-checking technique is used to verify whether the decomposition of the operator's behaviour into patterns is sound and complete with respect to the cognitive model. The decomposition is shown to be incomplete and a new behavioural pattern is identified, which appears to have been overlooked in the analysis of the data provided by the experiments with the simulator. This illustrates how formal analysis of operator models can yield fresh insights into how failures may arise in interactive systems.

Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations

Background From the mid-1980s to mid-1990s, the WHO MONICA Project monitored coronary events and classic risk factors for coronary heart disease (CHD) in 38 populations from 21 countries. We assessed the extent to which changes in these risk factors explain the variation in the trends in coronary-event rates across the populations. Methods In men and women aged 35-64 years, non-fatal myocardial infarction and coronary deaths were registered continuously to assess trends in rates of coronary events. We carried out population surveys to estimate trends in risk factors. Trends in event rates were regressed on trends in risk score and in individual risk factors. Findings Smoking rates decreased in most male populations but trends were mixed in women; mean blood pressures and cholesterol concentrations decreased, body-mass index increased, and overall risk scores and coronary-event rates decreased. The model of trends in 10-year coronary-event rates against risk scores and single risk factors showed a poor fit, but this was improved with a 4-year time lag for coronary events. The explanatory power of the analyses was limited by imprecision of the estimates and homogeneity of trends in the study populations. Interpretation Changes in the classic risk factors seem to partly explain the variation in population trends in CHD. Residual variance is attributable to difficulties in measurement and analysis, including time lag, and to factors that were not included, such as medical interventions. The results support prevention policies based on the classic risk factors but suggest potential for prevention beyond these.

Case fatality after an acute cardiac event: the effect of smoking and alcohol consumption

The objective of this study was to use a population-based register of acute cardiac events to investigate the association between survival after an acute event and history of smoking and alcohol consumption. The population was all residents of the Lower Hunter Region of Australia aged 25 to 69 years who suffered myocardial infarction or sudden cardiac death between 1986 and 1994. Among 10,170 events, 2504 resulted in death within 28 days. After adjusting for sex, age and medical history, current smokers had a similar risk of dying after an acute cardiac event to never-smokers [odds ratio (OR)=1.10, 95% confidence interval (CI) 0.94-1.29]. People who consumed more than 8 alcoholic drinks per day on more than 2 days per week (OR=1.93, 95% CI 1.39-2.69) and former moderate to heavy drinkers (OR=4.59, 95% CI 3.65-5.76) were more likely to die than people who were nondrinkers. The results of this large community study, suggesting no effect of smoking on case fatality and an increased risk of death after an acute cardiac event for heavy drinkers and former moderate to heavy drinkers, highlight the importance of a population view of case fatality. These results can also shed some light on reasons for the paradoxical results from clinical trials. (C) 2001 Elsevier Science Inc. All rights reserved.

Nuclear PTEN expression and clinicopathologic features in a population-based series of primary cutaneous melanoma

Germline mutations of the PTEN tumor-suppressor gene, on 10q23, cause Cowden syndrome, an inherited hamartoma syndrome with a high risk of breast, thyroid and endometrial carcinomas and, some suggest, melanoma. To date, most studies which strongly implicate PTEN in the etiology of sporadic melanomas have depended on cell lines, short-term tumor cultures and noncultured metastatic melanomas. The only study which reports PTEN protein expression in melanoma focuses on cytoplasmic expression, mainly in metastatic samples. To determine how PTEN contributes to the etiology or the progression of primary cutaneous melanoma, we examined cytoplasmic and nuclear PTEN expression against clinical and pathologic features in a population-based sample of 150 individuals with incident primary cutaneous melanoma. Among 92 evaluable samples, 30 had no or decreased cytoplasmic PTEN protein expression and the remaining 62 had normal PTEN expression. In contrast, 84 tumors had no or decreased nuclear expression and 8 had normal nuclear PTEN expression. None of the clinical features studied, such as Clark's level and Breslow thickness or sun exposure, were associated with cytoplasmic PTEN expressional levels. An association with loss of nuclear PTEN expression was indicated for anatomical site (p = 0.06) and mitotic index (p = 0.02). There was also an association for melanomas to either not express nuclear PTEN or to express p53 alone, rather than both simultaneously (p = 0.02). In contrast with metastatic melanoma, where we have shown previously that almost two-thirds of tumors have some PTEN inactivation, only one-third of primary melanomas had PTEN silencing. This suggests that PTEN inactivation is a late event likely related to melanoma progression rather than initiation. Taken together with our previous observations in thyroid and islet cell tumors, our data suggest that nuclear-cytoplasmic partitioning of PTEN might also play a role in melanoma progression. (C) 2002 Wiley-Liss, Inc.

The beliefs of nurses who were involved in a whistleblowing event

Background. Nursing codes of ethics bind nurses to the role of patient advocate and compel them to take action when the rights or safety of a patient are jeopardized. Reporting misconduct is known as whistleblowing and studies indicate that there are personal and professional risks involved in blowing the whistle. Aim. The aim of this study was to explore the beliefs of nurses who wrestled with this ethical dilemma. Design. A descriptive survey design was used to examine the beliefs of nurses in Western Australia who reported misconduct (whistleblowers) and of those who did not report misconduct (nonwhistleblowers). Methods. The instrument listed statements from current ethical codes, statements from traditional views on nursing and statements of beliefs related to the participant's whistleblowing experience. Respondents were asked to rate each item on a five-point Likert format which ranged from strongly agree to strongly disagree. Data were analysed using a Pearson's correlation matrix and one-way ANOVA. To further explore the data, a factor analysis was run with varimax rotation. Results. Results indicated that whistleblowers supported the beliefs inherent in patient advocacy, while nonwhistleblowers retained a belief in the traditional role of nursing. Participants who reported misconduct (whistleblowers) supported the belief that nurses were primarily responsible to the patient and should protect a patient from incompetent or unethical people. Participants who did not report misconduct (nonwhistleblowers) supported the belief that nurses are obligated to follow a physician's order at all times and that nurses are equally responsible to the patient, the physician and the employer. Conclusion. These findings indicate that nurses may respond to ethical dilemmas based on different belief systems.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care?

Background: Hospital performance reports based on administrative data should distinguish differences in quality of care between hospitals from case mix related variation and random error effects. A study was undertaken to determine which of 12 diagnosis-outcome indicators measured across all hospitals in one state had significant risk adjusted systematic ( or special cause) variation (SV) suggesting differences in quality of care. For those that did, we determined whether SV persists within hospital peer groups, whether indicator results correlate at the individual hospital level, and how many adverse outcomes would be avoided if all hospitals achieved indicator values equal to the best performing 20% of hospitals. Methods: All patients admitted during a 12 month period to 180 acute care hospitals in Queensland, Australia with heart failure (n = 5745), acute myocardial infarction ( AMI) ( n = 3427), or stroke ( n = 2955) were entered into the study. Outcomes comprised in-hospital deaths, long hospital stays, and 30 day readmissions. Regression models produced standardised, risk adjusted diagnosis specific outcome event ratios for each hospital. Systematic and random variation in ratio distributions for each indicator were then apportioned using hierarchical statistical models. Results: Only five of 12 (42%) diagnosis-outcome indicators showed significant SV across all hospitals ( long stays and same diagnosis readmissions for heart failure; in-hospital deaths and same diagnosis readmissions for AMI; and in-hospital deaths for stroke). Significant SV was only seen for two indicators within hospital peer groups ( same diagnosis readmissions for heart failure in tertiary hospitals and inhospital mortality for AMI in community hospitals). Only two pairs of indicators showed significant correlation. If all hospitals emulated the best performers, at least 20% of AMI and stroke deaths, heart failure long stays, and heart failure and AMI readmissions could be avoided. Conclusions: Diagnosis-outcome indicators based on administrative data require validation as markers of significant risk adjusted SV. Validated indicators allow quantification of realisable outcome benefits if all hospitals achieved best performer levels. The overall level of quality of care within single institutions cannot be inferred from the results of one or a few indicators.

Genetic influences on cognitive processes associated with distraction: An event-related potential study of the slow wave

The efficiency of inhibitory control processes has been proposed as a mechanism constraining working-memory capacity. In order to investigate genetic influences on processes that may reflect interference control, event-related potential (ER-P) activity recorded at frontal sites, during distracting and nondistracting conditions of a working-memory task, in a sample of 509 twin pairs was examined. The ERP component of interest was the slow wave (SW). Considerable overlap in source of genetic influence was found, with a common genetic factor accounting for 37 - 45% of SW variance irrespective of condition. However, 3 - 8 % of SW variance in the distracting condition was influenced by an independent genetic source. These results suggest that neural responses to irrelevant and distracting information, that may disrupt working-memory performance, differ in a fundamental way from perceptual and memory-based processing in a working-memory task. Furthermore, the results are consistent with the view that cognition is a complex genetic trait influenced by numerous genes of small influence.

Electronic commerce investments, the resource-based view of the firm, and firm market value

Firms have embraced electronic commerce as a means of doing business, either because they see it as a way to improve efficiency, grow market share, expand into new markets, or because they view it as essential for survival. Recent research in the United States provides some evidence that the market does value investments in electronic commerce. Following research that suggests that, in certain circumstances, the market values noninnovative investments as well as innovative investments in new products, we partition electronic commerce investment project announcements into innovative and noninnovative to determine whether there are excess returns associated with these types of announcements. Apart from our overall results being consistent with the United States findings that the market values investments in electronic commerce projects, we also find that noninnovative investments are perceived as more valuable to the firm than innovative investments. On average, the market expects innovative investments to earn a return commensurate with their risk. We conclude that innovative electronic commerce projects are most likely seen by the capital market as easily replicable, and consequently have little, if any, competitive advantage period. On the other hand, we conclude from the noninnovative investment results that these types of investments are seen as being compatible with a firm's assets-in-place, in particular, its information technology capabilities, a view consistent with the resource-based view of the firm.