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Recent and detailed operating data and practices from 46 worldwide copper converter operations are tabulated and reviewed. A detailed analysis of the information is presented to illustrate the correlation and ranges of key converter operating parameters: temperature, flowrates, slag chemistry, production, etc. Also included are converter refractory practice data. Converter operating indices such as converter production efficiency, are developed to suggest a possible standardized approach to comparing converters of varying size, input, and location. The source of the information for the review is a detailed questionnaire sent to all identified copper smelters in the world.

Background: Community-acquired pneumonia (CAP) is a common childhood infection. Inflammatory markers and radiological features have not previously been found useful in distinguishing bacterial from viral aetiology. Predicting the causative pathogens would help provide targeted management.Aim: To investigate clinical significance of inflammatory markers and radiological features in predicting the aetiology of childhood CAP.Methods: A prospective study of children with CAP seen in hospital in North East England from August 2000 to July 2001. Chest x-rays were reported by Radiologists according to the WHO criteria of lobar, patchy or perihilar infiltrates. Aetiology was decided by definite diagnostic criteria. Inflammatory markers included C-reactive protein (CRP), total white cell count (WCC) and neutrophil count. A discriminate analysis approach was used to classify cases on the basis of age, CRP and WCC for different chest x-ray categories forming the basis of a model for prediction of aetiology.Results: A total of 404 subjects aged 0-15 years were enrolled. Definite infections were 16.6% bacterial, 15.1% viral and 3.5% mixed viral-bacterial. Compared to viral, bacterial infections had higher mean values of CRP (p< 0.001), total WCC (p=0.002) and neutrophil count (p=0.001). The discriminate models using lobar, patchy and perihilar features had a respective accuracy rate of 95.8%, 85.5% and 91% in predicting if CAP is caused by bacterial or viral pathogens when used to reclassify the raw data.Conclusion: Children with bacterial pneumonia had higher inflammatory markers. This discriminate prediction model is a potentially useful tool in clinical management and epidemiological studies of childhood pneumonia.