Percutaneous coronary intervention with drug-eluting stents or coronary artery bypass surgery in subjects with type 2 diabetes : evaluation of: Farkouth ME, Domanski M, Sleeper LA, et al. Strategies for multivessel revascularization in patients with diabetes. N Engl J Med 2012;367(25):2375-84, and Contini GA, Nicolini F, Fortuna D, et al. Five-year outcomes of surgical or percutaneous myocardial revascularization in diabetic patients. Int J Cardiol 2012. [Epub ahead of print]

There is debate as to whether percutaneous coronary intervention (PCI) with drug-eluting stents or coronary artery bypass surgery (CABG) is the best procedure for subjects with type 2 diabetes and coronary artery disease requiring revascularization. There is some evidence that following these procedures there is less further revascularization with CABG than PCI in subjects with diabetes. Two recent studies; the FREEDOM (Future Revascularization Evaluation in patients with Diabetes mellitus: Optimal Management of Multivessel Disease) trial, and a trial using a real world diabetic population from a Registry, have shown that the benefits of CABG over PCI in subjects with type 2 diabetes extends to lower rates of death and myocardial infarct, in addition to lower rates of revascularization. However, the rates of stroke may be higher with CABG than PCI with drug-eluting stents in this population. Thus, if CABG is going to be preferred to PCI in subjects with type 2 diabetes and multivessel coronary disease, consideration should be given to how to reduce the rates of stroke with CABG.

Effectiveness of MED for Fault Diagnosis in Roller Bearings

Diagnostics of rolling element bearings is usually performed by means of vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. The aim is to monitor the integrity of the bearing components, in order to avoid catastrophic failures, or to implement condition based maintenance strategies. In particular, the trend in this field is to combine in a single algorithm different signal-enhancement and signal-analysis techniques. Among the first ones, Minimum Entropy Deconvolution (MED) has been pointed out as a key tool able to highlight the effect of a possible damage in one of the bearing components within the vibration signal. This paper presents the application of this technique to signals collected on a simple test-rig, able to test damaged industrial roller bearings in different working conditions. The effectiveness of the technique has been tested, comparing the results of one undamaged bearing with three bearings artificially damaged in different locations, namely on the inner race, outer race and rollers. Since MED performances are dependent on the filter length, the most suitable value of this parameter is defined on the basis of both the application and measured signals. This represents an original contribution of the paper.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.