812 resultados para Hier-archical clustering
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Little is known about engagement in multiple health behaviours in childhood cancer survivors.
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AIMS: Multiple arrhythmia re-inductions were recently shown in His-Purkinje system (HPS) ventricular tachycardia (VT). We hypothesized that HPS VT was a frequent mechanism of repetitive or incessant VT and assessed diagnostic criteria to select patients likely to have HPS VT. METHODS AND RESULTS: Consecutive patients with clustering VT episodes (>3 sustained monomorphic VT within 2 weeks) were included in the analysis. HPS VT was considered plausible in patients with (i) impaired left ventricular function associated with dilated cardiomyopathy or valvular heart disease; or (ii) ECG during VT similar to sinus rhythm QRS or to bundle-branch block QRS. HPS VT was plausible in 12 of 48 patients and HPS VT was demonstrated in 6 of 12 patients (50%, or 13% of the whole study group). Median VT cycle length was 318 ms (250-550). Catheter ablation was successful in all six patients. CONCLUSION: His-Purkinje system VT is found in a significant number of patients with repetitive or incessant VT episodes, and in a large proportion of patients with predefined clinical or electrocardiographic characteristics. Since it is easily amenable to catheter ablation, our data support the screening of all patients with repetitive VT in this regard and an invasive approach in a selected group of patients.
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We present studies of the spatial clustering of inertial particles embedded in turbulent flow. A major part of the thesis is experimental, involving the technique of Phase Doppler Interferometry (PDI). The thesis also includes significant amount of simulation studies and some theoretical considerations. We describe the details of PDI and explain why it is suitable for study of particle clustering in turbulent flow with a strong mean velocity. We introduce the concept of the radial distribution function (RDF) as our chosen way of quantifying inertial particle clustering and present some original works on foundational and practical considerations related to it. These include methods of treating finite sampling size, interpretation of the magnitude of RDF and the possibility of isolating RDF signature of inertial clustering from that of large scale mixing. In experimental work, we used the PDI to observe clustering of water droplets in a turbulent wind tunnel. From that we present, in the form of a published paper, evidence of dynamical similarity (Stokes number similarity) of inertial particle clustering together with other results in qualitative agreement with available theoretical prediction and simulation results. We next show detailed quantitative comparisons of results from our experiments, direct-numerical-simulation (DNS) and theory. Very promising agreement was found for like-sized particles (mono-disperse). Theory is found to be incorrect regarding clustering of different-sized particles and we propose a empirical correction based on the DNS and experimental results. Besides this, we also discovered a few interesting characteristics of inertial clustering. Firstly, through observations, we found an intriguing possibility for modeling the RDF arising from inertial clustering that has only one (sensitive) parameter. We also found that clustering becomes saturated at high Reynolds number.