5 resultados para Multiple-line insurance

em Deakin Research Online - Australia


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Finding ways to effectively support students while on placement remains a continuing endeavour for those who teach in professional education programmes. In The present paper, the multiple challenges and learning opportunities that social work students encounter during practicum learning will be discussed. Next, drawing from constructivist pedagogy and using authentic examples from an online discussion board, ways to supplement the support and educational input provided to students on placement will be demonstrated. Finally, some of the risks and limitations in engaging with on-line delivery are examined with the view to understanding how e-learning can be facilitated most effectively for students during the practicum.

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Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.


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This paper describes an experimental study of the Fuzzy ARTMAP (FAM) neural network as an autonomous learning system for pattern classification tasks. A benchmark database of radar signals from ionosphere has been employed for the system to classify arbitrary sequences of pattern into distinct categories. A number of simulations have been conducted systematically to evaluate the applicability and usefulness of FAM in this context. First, we identify the 'optimum' parameter settings of FAM for the problem at hand, and investigate the effects of different training schemes and learning rules on classification results, using an off-line learning methodology. We then examine a voting strategy to improve classification accuracy by combining results from multiple FAM classifiers. In addition to off-line learning, we evaluate the prospect of using FAM as an autonomously learning pattern classification system for on-line, non-stationary environments. The performance of FAM is comparable with other reported results, but with the added advantage of on-line and incremental learning.

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Background:
Dichloroacetate (DCA), through the inhibition of aerobic glycolysis (the ‘Warburg effect’) and promotion of pyruvate oxidation, induces growth reduction in many tumours and is now undergoing several clinical trials. If aerobic glycolysis is active in multiple myeloma (MM) cells, it can be potentially targeted by DCA to induce myeloma growth inhibition.

Methods:
Representative multiple myeloma cell lines and a myeloma-bearing mice were treated with DCA, alone and in combination with bortezomib.

Results:
We found that aerobic glycolysis occurs in approximately half of MM cell lines examined, producing on average 1.86-fold more lactate than phorbol myristate acetate stimulated-peripheral blood mononuclear cells and is associated with low-oxidative capacity. Lower doses of DCA (5–10 mM) suppressed aerobic glycolysis and improved cellular respiration that was associated with activation of the pyruvate dehydrogenase complex. Higher doses of DCA (10–25 mM) induced superoxide production, apoptosis, suppressed proliferation with a G0/1 and G2M phase arrest in MM cell lines. In addition, DCA increased MM cell line sensitivity to bortezomib, and combinatorial treatment of both agents improved the survival of myeloma-bearing mice.

Conclusion:
Myeloma cells display aerobic glycolysis and DCA may complement clinically used MM therapies to inhibit disease progression.

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To compare treatment persistence between two dosages of interferon β-1a in a large observational multiple sclerosis registry and assess disease outcomes of first line MS treatment at these dosages using propensity scoring to adjust for baseline imbalance in disease characteristics. Treatment discontinuations were evaluated in all patients within the MSBase registry who commenced interferon β-1a SC thrice weekly (n = 4678). Furthermore, we assessed 2-year clinical outcomes in 1220 patients treated with interferon β-1a in either dosage (22 µg or 44 µg) as their first disease modifying agent, matched on propensity score calculated from pre-treatment demographic and clinical variables. A subgroup analysis was performed on 456 matched patients who also had baseline MRI variables recorded. Overall, 4054 treatment discontinuations were recorded in 3059 patients. The patients receiving the lower interferon dosage were more likely to discontinue treatment than those with the higher dosage (25% vs. 20% annual probability of discontinuation, respectively). This was seen in discontinuations with reasons recorded as “lack of efficacy” (3.3% vs. 1.7%), “scheduled stop” (2.2% vs. 1.3%) or without the reason recorded (16.7% vs. 13.3% annual discontinuation rate, 22 µg vs. 44 µg dosage, respectively). Propensity score was determined by treating centre and disability (score without MRI parameters) or centre, sex and number of contrast-enhancing lesions (score including MRI parameters). No differences in clinical outcomes at two years (relapse rate, time relapse-free and disability) were observed between the matched patients treated with either of the interferon dosages. Treatment discontinuations were more common in interferon β-1a 22 µg SC thrice weekly. However, 2-year clinical outcomes did not differ between patients receiving the different dosages, thus replicating in a registry dataset derived from “real-world” database the results of the pivotal randomised trial. Propensity score matching effectively minimised baseline covariate imbalance between two directly compared sub-populations from a large observational registry.