A unified model of the electrical power network

Traditionally, the different infrastructure layers, technologies and management activities associated with the design, control and protection operation of the Electrical Power Systems have been supported by numerous independent models of the real world network. As a result of increasing competition in this sector, however, the integration of technologies in the network and the coordination of complex management processes have become of vital importance for all electrical power companies. The aim of the research outlined in this paper is to develop a single network model which will unify the generation, transmission and distribution infrastructure layers and the various alternative implementation technologies. This 'unified model' approach can support ,for example, network fault, reliability and performance analysis. This paper introduces the basic network structures, describes an object-oriented modelling approach and outlines possible applications of the unified model

Power system fault prediction using artificial neural networks

The medium term goal of the research reported in this paper was the development of a major in-house suite of strategic computer aided network simulation and decision support tools to improve the management of power systems. This paper describes a preliminary research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. To achieve this goal, an AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector only requires external measurements taken from the input and output nodes of the power system. The AI detection system is capable of rapidly predicting a malfunction within the system . Simulation will normally take place using equivalent circuit representation. Artificial Neural Networks (ANNs) are used to construct a hierarchical feed-forward structure which is the most important component in the fault detector. Simulation of a transmission line (2-port circuit ) has already been carried out and preliminary results using this system are promising. This approach provided satisfactory results with accuracy of 95% or higher

Update of an early warning fault detection method using artificial intelligence techniques

This presentation describes a research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. An AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector for this early warning fault detection device only requires external measurements taken from the input and output nodes of the power system. The AI detection system is capable of rapidly predicting a malfunction within the system. Artificial Neural Networks (ANNs) are being used as the core of the fault detector. In an earlier paper [11], a computer simulated medium length transmission line has been tested by the detector and the results clearly demonstrate the capability of the detector. Today’s presentation considers a case study illustrating the suitability of this AI Technique when applied to a distribution transformer. Furthermore, an evolutionary optimisation strategy to train ANNs is also briefly discussed in this presentation, together with a ‘crystal ball’ view of future developments in the operation and monitoring of transmission systems in the next millennium

Early warning fault detection using artificial intelligent methods

This paper describes a research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. An AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector for this early warning fault detection device only requires external measurements taken from the input and output nodes of the power system. The AI detection system is capable of rapidly predicting a malfunction within the system. Artificial Neural Networks (ANNs) are being used as the core of the fault detector. A simulated medium length transmission line has been tested by the detector and the results demonstrate the capability of the detector. Furthermore, comments on an evolutionary technique as the optimisation strategy for ANNs are included in this paper

Digital measurement of lightning impulse parameters using curving fitting algorithms

This paper describes the application of curve fitting algorithms to aid the evaluation of lightning impulse parameters. A number of popular curve fitting algorithms have been evaluated and compared. Investigations using the genetic algorithm and other optimisation methods for the purpose of curve fitting have also been carried out and will be described

The Apollo Virtual Microscope Collection: Lunar Mineralogy and Petrology of Apollo 11, 12, 14, 15 and 16 Rocks

We report on the new Virtual Microscopes on Apollo 16 lunar samples in our Apollo Virtual Microscope collection

Immunological responses in human papillomavirus 16 E6/E7-transgenic mice to E7 protein correlate with the presence of skin disease

The human papillomavirus (HPV) oncogenes, E6 and E7, are believed to contribute to the development of cervical cancers in women infected with certain HPV genotypes, most notably HPV-16 and HPV-18. Given their expression in tumor tissue, E6 and E7 have been implicated as potential tumor-specific antigens. We have examined an HPV-16 E6- and E7-transgenic mouse lineage for immune responses to these viral oncoproteins. Mice in this lineage express the HPV-16 E6 and E7 genes in their skin and eyes, and on aging, these mice frequently develop squamous cell carcinomas and lenticular tumors. Young transgenic mice, which had measurable E7 protein in the eye but not in the skin, were immunologically naive to E7 protein. They mounted an immune response to E7 on immunization comparable to that of nontransgenic controls, suggesting a lack of immune tolerance to this protein. Older line 19 mice, which are susceptible to skin disease associated with transcription of the E6 and E7 open reading frames, had measurable E7 protein in their skin. These older transgenic mice spontaneously developed antibody responses to endogenous E7 protein, particularly in association with skin disease. Also detected in older mice were delayed-type hypersensitivity responses to E7. These finding parallel the humoral immune response to E7 protein in patients with HPV-associated cervical cancer and suggest that line 19 mice may provide a model for studying the immunobiology of HPV-associated cancers

Fidelity monitoring across the seven studies in the Consortium of Hospitals Advancing Research on Tobacco (CHART)

Background This paper describes fidelity monitoring (treatment differentiation, training, delivery, receipt and enactment) across the seven National Institutes of Health-supported Consortium of Hospitals Advancing Research on Tobacco (CHART) studies. The objectives of the study were to describe approaches to monitoring fidelity including treatment differentiation (lack of crossover), provider training, provider delivery of treatment, patient receipt of treatment, and patient enactment (behavior) and provide examples of application of these principles. Methods Conducted between 2010 and 2014 and collectively enrolling over 9500 inpatient cigarette smokers, the CHART studies tested different smoking cessation interventions (counseling, medications, and follow-up calls) shown to be efficacious in Cochrane Collaborative Reviews. The CHART studies compared their unique treatment arm(s) to usual care, used common core measures at baseline and 6-month follow-up, but varied in their approaches to monitoring the fidelity with which the interventions were implemented. Results Treatment differentiation strategies included the use of a quasi-experimental design and monitoring of both the intervention and control group. Almost all of the studies had extensive training for personnel and used a checklist to monitor the intervention components, but the items on these checklists varied widely and were based on unique aspects of the interventions, US Public Health Service and Joint Commission smoking cessation standards, or counselor rapport. Delivery of medications ranged from 31 to 100 % across the studies, with higher levels from studies that gave away free medications and lower levels from studies that sought to obtain prescriptions for the patient in real world systems. Treatment delivery was highest among those studies that used automated (interactive voice response and website) systems, but this did not automatically translate into treatment receipt and enactment. Some studies measured treatment enactment in two ways (e.g., counselor or automated system report versus patient report) showing concurrence or discordance between the two measures. Conclusions While fidelity monitoring can be challenging especially in dissemination trials, the seven CHART studies used a variety of methods to enhance fidelity with consideration for feasibility and sustainability. Trial registration - Dissemination of Tobacco Tactics for hospitalized smokers. Clinical Trials Registration No. NCT01309217. - Smoking cessation in hospitalized smokers. Clinical Trials Registration No. NCT01289275. - Using “warm handoffs” to link hospitalized smokers with tobacco treatment after discharge: study protocol of a randomized controlled trial. Clinical Trials Registration No. NCT01305928. - Web-based smoking cessation intervention that transitions from inpatient to outpatient. Clinical Trials Registration No. NCT01277250. - Effectiveness of smoking-cessation interventions for urban hospital patients. Clinical Trials Registration No. NCT01363245. - Comparative effectiveness of post-discharge interventions for hospitalized smokers. Clinical Trials Registration No. NCT01177176. - Health and economic effects from linking bedside and outpatient tobacco cessation services for hospitalized smokers in two large hospitals. Clinical Trials Registration No. NCT01236079

Optimism may moderate screening mammogram frequency in Medicare: A longitudinal study

Higher trait optimism and/or lower cynical hostility are associated with healthier behaviors and lower risk of morbidity and mortality, yet their association with health care utilization has been understudied. Whether these psychological attitudes are associated with breast cancer screening behavior is unknown. To assess the association of optimism and cynical hostility with screening mammography in older women and whether sociodemographic factors acted as mediators of these relationships, we used Women\u27s Health Initiative (WHI) observational cohort survey data linked to Medicare claims. The sample includes WHI participants without history of breast cancer who were enrolled in Medicare Parts A and B for \u3e /=2 years from 2005-2010, and who completed WHI baseline attitudinal questionnaires (n = 48,291). We used survival modeling to examine whether screening frequency varied by psychological attitudes (measured at study baseline) after adjusting for sociodemographic characteristics, health conditions, and healthcare-related variables. Psychological attitudes included trait optimism (Life Orientation Test-Revised) and cynical hostility (Cook Medley subscale), which were self-reported at study baseline. Sociodemographic, health conditions, and healthcare variables were self-reported at baseline and updated through 2005 as available. Contrary to our hypotheses, repeated events survival models showed that women with the lowest optimism scores (i.e., more pessimistic tendencies) received 5% more frequent screenings after complete covariate adjustment (p \u3c .01) compared to the most optimistic group, and showed no association between cynical hostility and frequency of screening mammograms. Sociodemographic factors did not appear to mediate the relationship between optimism and screenings. However, higher levels of education and higher levels of income were associated with more frequent screenings (both p \u3c .01). We also found that results for optimism were primarily driven by women who were aged 75 or older after January 2009, when changes to clinical guidelines lead to uncertainty about risks and benefits of screening in this age group. The study demonstrated that lower optimism, higher education, and higher income were all associated with more frequent screening mammograms in this sample after repeated events survival modeling and covariate adjustment

What influences aggression and foraging activity in social birds? Measuring individual, group and environmental characteristics

This is the final version. Available from Wiley via the DOI in this record.For specialised feeders, accessing food resources may impact on the performance of appetitive foraging and social behaviours at individual and population levels. Flamingos are excellent examples of social species with complex, species‐specific feeding strategies. As attainment of coloured plumage depends upon intake of dietary carotenoids, and as study of free‐ranging flamingos shows that foraging is disrupted by aggression from other birds, we investigated the effect of four feeding styles on foraging and aggression in captive lesser flamingos. We evaluated individual and group differences in foraging and aggression when birds consumed bespoke “flamingo pellet” from a bowl, an indoor feeding pool and an outdoor feeding section of their pool. Natural foraging (when birds were feeding irrespective of the presence of pellet) was recorded for comparison with artificial feeding styles. One‐minute long video footage of the birds' activities in these different locations, recorded between 2013 and 2016, was used to evaluate behaviour. Total number of seconds engaged in feeding and in aggression was recorded by continuous sampling. The colour of individual birds was scored from 1 (mainly white) to 4 (mainly pink). For natural filter feeding in the outdoor pool, maximum foraging was twice as much as bowl feeding, whilst aggression was less than half as much as other feeding methods. Overall, a more restricted feeding style significantly predicted aggression, along with increasing group size. Plumage colour significantly influenced aggression (brightest flamingos were more aggressive) and showed a non‐significant trend with foraging (brighter birds fed less than paler birds). No sex effect on feeding or aggression was found. This study enhances our understanding of husbandry and species' biology impacts on captive behaviour and provides data‐based evidence to improve food presentation. For flamingos, implementation of spacious outdoor feeding areas can encourage natural foraging patterns by reducing excess aggression and enhances welfare by improving flock social stability