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Increase in the price of oil has stimulated interest in coal-burning engines including the Stirling engines. Applications for large (> 1 MW) coal-burning Stirling engines are foreseen for marine propulsion, stationary power, railway locomotive and the heavy off-highway rubber-tyred equipment used in mining, agriculture, construction and forestry. This paper is directed principally to speculations about large coal-fired Stirling air engines with water lubrication for railway locomotive application, but similar philosophy is applicable in the other applications for large slow running engines. A brief discussion is included about mechanical arrangements and the use of air as a working fluid with water as the lubricant in Stirling engines combined with fluidized bed coal combustors and sodium vapour heat transport systems. The possibilities for railway locomotive application are explored in terms of a large unit designed from the start to utilize Stirling engines and the conversion of existing steam locomotives. Related studies have considered the conversion of diesel-electric locomotives and the designing of a free-piston Stirling engine hydrostatic drive yard locomotive.

Objective: Peripheral neuropathies (PNPs) in HIV-infected patients are highly debilitating because of neuropathic pain and physical disabilities. We defined prevalence and associated predictive variables for PNP subtypes in a cohort of persons living with HIV.Design: Adult persons living with HIV in clinical care were recruited to a longitudinal study examining neurological complications.Methods: Each patient was assessed for symptoms and signs of PNP with demographic, laboratory, and clinical variables. Univariate, multiple logistic regression and machine learning analyses were performed by comparing patients with and without PNP.Results: Three patient groups were identified: PNP (n ¼ 111) that included HIVassociated distal sensory polyneuropathy (n ¼ 90) or mononeuropathy (n ¼ 21), and non-neuropathy (n ¼ 408). Univariate analyses showed multiple variables differed significantly between the non-neuropathy and PNP groups including age, estimated HIV type 1 (HIV-1) duration, education, employment, neuropathic pain, peak viral load, polypharmacy, diabetes, cardiovascular disorders, AIDS, and prior neurotoxic nucleoside antiretroviral drug exposure. Classification algorithms distinguished those with PNP, all with area under the receiver operating characteristic curve values of more than 0.80. Random forest models showed greater accuracy and area under the receiver operating characteristic curve values compared with the multiple logistic regression analysis. Relative importance plots showed that the foremost predictive variables of PNP were HIV-1 duration, peak plasma viral load, age, and low CD4 þ T-cell levels.Conclusion: PNP in HIV-1 infection remains common affecting 21.4% of patients in care. Machine-learning models uncovered variables related to PNP that were undetected by conventional analyses, emphasizing the importance of statistical algorithmic approaches to understanding complex neurological syndromes.

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The object of this paper is to give a better understanding of the CCMC (Committee of Common Market Automobile Constructors) classification system for various automotive engine lubricants.