An Application of ISO 5725 in Brewing Industry

2002 Mathematics Subject Classification: 62P30, 62P10.The colloidal stability is very important part of the total beer quality. The stabilized beers have to have a long shelf-life. Determination of some haze forming complexes could be very useful for prediction of beer colloidal stability. We study the repeatability and reproducibility of a method for determination of some haze forming complexes in beer. The method was tested in 10 laboratories. All of theme analyzed the same beer samples and carried out two measurements for each. Statistical evaluation of results was according ISO 5725 and previous experience. The applied ISO 5725 statistical analyzes ensured high quality and possibility of international recognition of the measurement method.Partially supported by Mathind IST-2000-26015 and by Pro-enbis GTC1-2001-43031

Utility of Different Electrocardiographical Leads during Diagnostic Ajmaline Test for Suspected Brugada Syndrome

In order to compare the value of different leads and lead combinations to detect the signature Brugada type ECG pattern, we analysed digital 10-second, 15-lead ECGs (12 standard leads + leads V1 to V3 from 3rd intercostal (i.c.) space, V1h to V3h) acquired during diagnostic Ajmaline testing in 128 patients (80 men, age 37±15 years) with suspected Brugada syndrome (BS) (patient group), 15-lead resting ECGs of 108 healthy subjects (53 men, age 31.9±10.5 years) (control group A) and standard 12-lead resting ECGs of 229 healthy subjects (111 men, age 33±4 years) (control group B). Bipolar leads between V2 (positive pole) and V4 or V5 (leads V2-4V2-5) were derived by subtracting leads V4 and V5 from V2 (custom-made program). The 6 peripheral, 6 right precordial leads (V1 to V3, V1h to V3h) and leads V2-4 and V2-5 of the patients group, leads V1h to V3h of control group A, and leads V2-4 and V2-5 of control group B were analysed for the presence of type 1 Brugada pattern. There were 21 (16.4%) positive and 107 (83.6%) negative Ajmaline tests. In 7 positive tests (33%), type 1 pattern appeared only in leads V1h to V3h, whereas in 14 tests 67%) it appeared in both V1 to V3 and V1h to V3h. Lead V2 displayed type 1 pattern during 10 positive tests; in all of them, plus 10 other positive tests type 1 was also noted in lead V2h (n=20, 95.2%). In all 10 cases, in which lead V2 exhibited type 1 pattern (n=10), lead V2-4 and/or V2-5 also exhibited type 1-like pattern. During 7 positive tests, in which lead V2h but not V2 exhibited type 1 pattern, lead V2-4 and/or V2-5 also demonstrated type 1 pattern. Type 1 pattern was observed in leads V3 and V3h during 1 (5%) and 5 (24%) positive tests, in 0 ECGs (0%) in control group A and in 1 ECG (0.4%) in control group B. In conclusion, the "high" V1 and V2 leads (3rd i.c. space) detect more sensitively Brugada type 1 pattern than the standard V1 and V2 leads (4th i.c. space); leads V3 and V3h are not essential for the diagnosis of BS; bipolar leads V2-4 and V2-5 are superior to lead V2 for the ECG diagnosis of BS

The transition to aeration in two-phase mixing in stirred vessels

We consider the mixing of a viscous fluid by the rotation of a pitched blade turbine inside an open, cylindrical tank, with air as the lighter fluid above. To examine the flow and interfacial dynamics, we utilise a highly-parallelised implementation of a hybrid front-tracking/level-set method that employs a domain-decomposition parallelisation strategy. Our numerical technique is designed to capture faithfully complex interfacial deformation, and changes of topology, including interface rupture and dispersed phase coalescence. As shown via transient, three-dimensional direct numerical simulations, the impeller induces the formation of primary vortices that arise in many idealised rotating flows as well as several secondary vortical structures resembling Kelvin-Helmholtz, vortex breakdown, blade tip vortices, and end-wall corner vortices. As the rotation rate increases, a transition to `aeration' is observed when the interface reaches the rotating blades leading to the entrainment of air bubbles into the viscous fluid and the creation of a bubbly, rotating, free surface flow. The mechanisms underlying the aeration transition are probed as are the routes leading to it, which are shown to exhibit a strong dependence on flow history.Comment: 14 pages, 9 figure

ECG Wavelet Analysis for the Detection of Gene Mutations in Patients with Brugada Syndrome

Abstract We applied wavelet transform (WT) Introduction The Brugada syndrome (BrS) is an inherited ion chanelopathy characterised by a typical electrocardiographic (ECG) pattern of J point and ST segment elevation in the right precordial leads and predisposition towards malignant ventricular arrhythmias Both depolarisation and repolarisation abnormalities contribute to the arrhythmia substrate and arrhythmia genesis in the BrS Wavelet analysis is a form of time-frequency transformation that has long been used in non-invasive electrocardiology for detection of characteristic ECG components, heart rate variability, analysis of ischaemic ST changes, ventricular repolarisation and others In this study, we hypothesised that continuous wavelet transform (WT) applied to the QRS and ST-T wave can help to identify carriers of SCN5A mutations among patients with the BrS. We analysed digital 15-lead ECGs previously recorded during positive diagnostic ajmaline test for BrS with simultaneous acquisition of the right precordial leads in both standard, as well as "high" electrode positions. Methods Study population and data acquisition The study population consisted of 26 patients (age 42.0±17.8 years, 13 men, 13 women, age 41.6±19.1 and 42.4±17.2, respectively, p=0.92 for men vs women) with suspected BrS who underwent diagnostic ajmaline test as part of their standard clinical management. All patients had either normal or non-diagnostic (i.e. not displaying type 1 Brugada ECG pattern) resting ECGs before the test. Details about this patient population have been partially described in previous publication

The association of spatial T wave axis deviation with incident coronary events. The ARIC cohort

BACKGROUND: Although current evidence suggests that the spatial T wave axis captures important information about ventricular repolarization abnormalities, there are only a few and discordant epidemiologic studies addressing the ability of the spatial T wave axis to predict coronary heart disease (CHD) occurrence. METHODS: This prospective study analyzed data from 12,256 middle-aged African American and white men and women, from the Atherosclerosis Risk in Communities Study (ARIC). Following a standardized protocol, resting standard 12-lead, 10-second electrocardiograms were digitized and analyzed with the Marquette GE program. The median follow-up time was 12.1 years; incident coronary heart disease comprised fatal and non-fatal CHD events. RESULTS: The incidence rate of CHD was 4.26, 4.18, 4.28 and 5.62 per 1000 person-years respectively, across the spatial T wave axis quartiles. Among women for every 10 degrees increase in the spatial T wave axis deviation, there was an estimated increase in the risk of CHD of 1.16 (95% CI 1.04–1.28). After adjustment for age, height, weight, smoking, hypertension, diabetes, QRS axis and minor T wave abnormalities, this hazard rate ratio for women fell to 1.03 (0.92–1.14). The corresponding crude and adjusted hazard ratios for men were 1.05 (95% CI 0.96–1.15) and 0.95 (0.86–1.04) respectively. CONCLUSIONS: In conclusion, this prospective, population-based, bi-ethnic study of men and women free of coronary heart disease at baseline shows that spatial T wave axis deviation is not associated with incident coronary events during long-term follow up. It is doubtful that spatial T wave axis deviation would add benefit in the prediction of CHD events above and beyond the current traditional risk factors

Comparison of Ajmaline and Procainamide Provocation Tests in the Diagnosis of Brugada Syndrome.

OBJECTIVES: The authors studied the response rates and relative sensitivity of the most common agents used in the sodium-channel blocker (SCB) challenge. BACKGROUND: A type 1 Brugada electrocardiographic pattern precipitated by an SCB challenge confers a diagnosis of Brugada syndrome. METHODS: Patients undergoing an SCB challenge were prospectively enrolled across Canada and the United Kingdom. Patients with no prior cardiac arrest and family histories of sudden cardiac death or Brugada syndrome were included. RESULTS: Four hundred twenty-five subjects underwent SCB challenge (ajmaline, n = 331 [78%]; procainamide, n = 94 [22%]), with a mean age of 39 ± 15 years (54% men). Baseline non-type 1 Brugada ST-segment elevation was present in 10%. A total of 154 patients (36%) underwent signal-averaged electrocardiography, with 41% having late potentials. Positive results were seen more often with ajmaline than procainamide infusion (26% vs. 4%, p < 0.001). On multivariate analysis, baseline non-type 1 Brugada ST-segment elevation (odds ratio [OR]: 6.92; 95% confidence interval [CI]: 3.15 to 15.2; p < 0.001) and ajmaline use (OR: 8.76; 95% CI: 2.62 to 29.2; p < 0.001) were independent predictors of positive results to SCB challenge. In the subgroup undergoing signal-averaged electrocardiography, non-type 1 Brugada ST-segment elevation (OR: 9.28; 95% CI: 2.22 to 38.8; p = 0.002), late potentials on signal-averaged electrocardiography (OR: 4.32; 95% CI: 1.50 to 12.5; p = 0.007), and ajmaline use (OR: 12.0; 95% CI: 2.45 to 59.1; p = 0.002) were strong predictors of SCB outcome. CONCLUSIONS: The outcome of SCB challenge was significantly affected by the drug used, with ajmaline more likely to provoke a type 1 Brugada electrocardiographic pattern compared with procainamide. Patients undergoing SCB challenge may have contrasting results depending on the drug used, with potential clinical, psychosocial, and socioeconomic implications

Relation between QT and RR intervals is highly individual among healthy subjects: implications for heart rate correction of the QT interval

Objective: To compare the QT/RR relation in healthy subjects in order to investigate the differences in optimum heart rate correction of the QT interval. Methods: 50 healthy volunteers (25 women, mean age 33.6 (9.5) years, range 19–59 years) took part. Each subject underwent serial 12 lead electrocardiographic monitoring over 24 hours with a 10 second ECG obtained every two minutes. QT intervals and heart rates were measured automatically. In each subject, the QT/RR relation was modelled using six generic regressions, including a linear model (QT = β + α × RR), a hyperbolic model (QT = β + α/RR), and a parabolic model (QT = β × RR(α)). For each model, the parallelism and identity of the regression lines in separate subjects were statistically tested. Results: The patterns of the QT/RR relation were very different among subjects. Regardless of the generic form of the regression model, highly significant differences were found not only between the regression lines but also between their slopes. For instance, with the linear model, the individual slope (parameter α) of any subject differed highly significantly (p < 0.000001) from the linear slope of no fewer than 21 (median 32) other subjects. The linear regression line of 20 subjects differed significantly (p < 0.000001) from the linear regression lines of each other subject. Conversion of the QT/RR regressions to QTc heart rate correction also showed substantial intersubject differences. Optimisation of the formula QTc = QT/RR(α) led to individual values of α ranging from 0.234 to 0.486. Conclusion: The QT/RR relation exhibits a very substantial intersubject variability in healthy volunteers. The hypothesis underlying each prospective heart rate correction formula that a “physiological” QT/RR relation exists that can be mathematically described and applied to all people is incorrect. Any general heart rate correction formula can be used only for very approximate clinical assessment of the QTc interval over a narrow window of resting heart rates. For detailed precise studies of the QTc interval (for example, drug induced QT interval prolongation), the individual QT/RR relation has to be taken into account