Trends in childhood type 1 diabetes incidence in Europe during 1989-2008: evidence of non-uniformity over time in rates of increase

AIMS/HYPOTHESIS:

The aim of the study was to describe 20-year incidence trends for childhood type 1 diabetes in 23 EURODIAB centres and compare rates of increase in the first (1989-1998) and second (1999-2008) halves of the period.

METHODS:

All registers operate in geographically defined regions and are based on a clinical diagnosis. Completeness of registration is assessed by capture-recapture methodology. Twenty-three centres in 19 countries registered 49,969 new cases of type 1 diabetes in individuals diagnosed before their 15th birthday during the period studied.

RESULTS:

Ascertainment exceeded 90% in most registers. During the 20-year period, all but one register showed statistically significant changes in incidence, with rates universally increasing. When estimated separately for the first and second halves of the period, the median rates of increase were similar: 3.4% per annum and 3.3% per annum, respectively. However, rates of increase differed significantly between the first half and the second half for nine of the 21 registers with adequate coverage of both periods; five registers showed significantly higher rates of increase in the first half, and four significantly higher rates in the second half.

CONCLUSIONS/INTERPRETATION:

The incidence rate of childhood type 1 diabetes continues to rise across Europe by an average of approximately 3-4% per annum, but the increase is not necessarily uniform, showing periods of less rapid and more rapid increase in incidence in some registers. This pattern of change suggests that important risk exposures differ over time in different European countries. Further time trend analysis and comparison of the patterns in defined regions is warranted.

Crack detection of steel girders using Brillouin optical time domain analysis

This article presents the results from an experimental program designed to evaluate the performance of a system consisting of a readout unit and a ribbon type Fiber Optic Sensor (FOS) based on Brillouin Optical Time Domain Analysis (BOTDA). The system is intended for the detection of cracks as well as the monitoring of long-term performance for steel bridge girders. The program consisted of introducing a crack at the center of a 3-m-long steel beam and monitoring its progression using static loading tests performed at ambient and sub-zero temperatures. For sensor lengths similar to those used in the field, the resonant frequency shifts per unit increase in crack width were found to decrease from 114 MHz/mm at ambient temperature (~25C) to 65 MHz/mm at -10C. Results also revealed nonlinearity and variability, which can be attributed to an incompatibility between the settings of the laser pump in the readout unit and the sensor length. Significant losses were detected along the bonded segments of the sensor and were attributed to the presence of ripples along the sensor. These undulations worsen with a reduction in temperature and are induced by the bonding procedure as well as the slack provided in the plastic sleeves containing the splices.

Comparison of Wavelet Transform and Time-Domain Analysis of Second Trimester Uterine Artery Doppler Waveforms in Screening for Pre-Eclampsia

The aim of this study was to compare time-domain waveform analysis of second-trimester uterine artery Doppler using the resistance index (RI) with waveform analysis using a mathematical tool known as wavelet transform for the prediction of pre-eclampsia (PE). This was a retrospective, nested case-cohort study of 336 women, 37 of whom subsequently developed PE. Uterine artery Doppler waveforms were analysed using both RI and waveform analysis. The utility of these indices in screening for PE was then evaluated using receiver operating characteristic curves. There were significant differences in uterine artery RI between the PE women and those with normal pregnancy outcome. After wavelet analysis, significant difference in the mean amplitude in wavelet frequency band 4 was noted between the 2 groups. The sensitivity for both Doppler RI and frequency band 4 for the detection of PE at a 10% false-positive rate was 45%. This small study demonstrates the application of wavelet transform analysis of uterine artery Doppler waveforms in screening for PE. Further prospective studies are needed in order to clearly define if this analytical approach to waveform analysis may have the potential to improve the detection of PE by uterine artery Doppler screening.

The influence of market deregulation on fast food consumption and body mass index:A cross-national time series analysis

Objective
To investigate the effect of fast food consumption on mean population body mass index (BMI) and explore the possible influence of market deregulation on fast food consumption and BMI.

Methods
The within-country association between fast food consumption and BMI in 25 high-income member countries of the Organisation for Economic Co-operation and Development between 1999 and 2008 was explored through multivariate panel regression models, after adjustment for per capita gross domestic product, urbanization, trade openness, lifestyle indicators and other covariates. The possible mediating effect of annual per capita intake of soft drinks, animal fats and total calories on the association between fast food consumption and BMI was also analysed. Two-stage least squares regression models were conducted, using economic freedom as an instrumental variable, to study the causal effect of fast food consumption on BMI.

Findings
After adjustment for covariates, each 1-unit increase in annual fast food transactions per capita was associated with an increase of 0.033 kg/m2 in age-standardized BMI (95% confidence interval, CI: 0.013–0.052). Only the intake of soft drinks – not animal fat or total calories – mediated the observed association (β: 0.030; 95% CI: 0.010–0.050). Economic freedom was an independent predictor of fast food consumption (β: 0.27; 95% CI: 0.16–0.37). When economic freedom was used as an instrumental variable, the association between fast food and BMI weakened but remained significant (β: 0.023; 95% CI: 0.001–0.045).

Conclusion
Fast food consumption is an independent predictor of mean BMI in high-income countries. Market deregulation policies may contribute to the obesity epidemic by facilitating the spread of fast food.

An extensible complex fast Fourier transform processor chip for real-time spectrum analysis and measurement

This paper describes in detail the design of a CMOS custom fast Fourier transform (FFT) processor for computing a 256-point complex FFT. The FFT is well-suited for real-time spectrum analysis in instrumentation and measurement applications. The FFT butterfly processor reported here consists of one parallel-parallel multiplier and two adders. It is capable of computing one butterfly computation every 100 ns thus it can compute a 256-point complex FFT in 102.4 μs excluding data input and output processes.

An integrated 256-point complex FFT processor for real-time spectrum analysis and measurement

This paper describes in detail the design of a custom CMOS Fast Fourier Transform (FFT) processor for computing 256-point complex FFT. The FFT is well suited for real-time spectrum analysis in instrumentation and measurement applications. The FFT butterfly processor consists of one parallel-parallel multiplier and two adders. It is capable of computing one butterfly computation every 100 ns thus it can compute 256-complex point FFT in 25.6 μs excluding data input and output processes.

The Future of services: Uncovering latent needs through trend analysis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Limited sampling strategies for estimation of cyclosporine exposure in pediatric hematopoietic stem cell transplant recipients : methodological improvement and introduction of sampling time deviation analysis.

Le suivi thérapeutique est recommandé pour l’ajustement de la dose des agents immunosuppresseurs. La pertinence de l’utilisation de la surface sous la courbe (SSC) comme biomarqueur dans l’exercice du suivi thérapeutique de la cyclosporine (CsA) dans la transplantation des cellules souches hématopoïétiques est soutenue par un nombre croissant d’études. Cependant, pour des raisons intrinsèques à la méthode de calcul de la SSC, son utilisation en milieu clinique n’est pas pratique. Les stratégies d’échantillonnage limitées, basées sur des approches de régression (R-LSS) ou des approches Bayésiennes (B-LSS), représentent des alternatives pratiques pour une estimation satisfaisante de la SSC. Cependant, pour une application efficace de ces méthodologies, leur conception doit accommoder la réalité clinique, notamment en requérant un nombre minimal de concentrations échelonnées sur une courte durée d’échantillonnage. De plus, une attention particulière devrait être accordée à assurer leur développement et validation adéquates. Il est aussi important de mentionner que l’irrégularité dans le temps de la collecte des échantillons sanguins peut avoir un impact non-négligeable sur la performance prédictive des R-LSS. Or, à ce jour, cet impact n’a fait l’objet d’aucune étude. Cette thèse de doctorat se penche sur ces problématiques afin de permettre une estimation précise et pratique de la SSC. Ces études ont été effectuées dans le cadre de l’utilisation de la CsA chez des patients pédiatriques ayant subi une greffe de cellules souches hématopoïétiques. D’abord, des approches de régression multiple ainsi que d’analyse pharmacocinétique de population (Pop-PK) ont été utilisées de façon constructive afin de développer et de valider adéquatement des LSS. Ensuite, plusieurs modèles Pop-PK ont été évalués, tout en gardant à l’esprit leur utilisation prévue dans le contexte de l’estimation de la SSC. Aussi, la performance des B-LSS ciblant différentes versions de SSC a également été étudiée. Enfin, l’impact des écarts entre les temps d’échantillonnage sanguins réels et les temps nominaux planifiés, sur la performance de prédiction des R-LSS a été quantifié en utilisant une approche de simulation qui considère des scénarios diversifiés et réalistes représentant des erreurs potentielles dans la cédule des échantillons sanguins. Ainsi, cette étude a d’abord conduit au développement de R-LSS et B-LSS ayant une performance clinique satisfaisante, et qui sont pratiques puisqu’elles impliquent 4 points d’échantillonnage ou moins obtenus dans les 4 heures post-dose. Une fois l’analyse Pop-PK effectuée, un modèle structural à deux compartiments avec un temps de délai a été retenu. Cependant, le modèle final - notamment avec covariables - n’a pas amélioré la performance des B-LSS comparativement aux modèles structuraux (sans covariables). En outre, nous avons démontré que les B-LSS exhibent une meilleure performance pour la SSC dérivée des concentrations simulées qui excluent les erreurs résiduelles, que nous avons nommée « underlying AUC », comparée à la SSC observée qui est directement calculée à partir des concentrations mesurées. Enfin, nos résultats ont prouvé que l’irrégularité des temps de la collecte des échantillons sanguins a un impact important sur la performance prédictive des R-LSS; cet impact est en fonction du nombre des échantillons requis, mais encore davantage en fonction de la durée du processus d’échantillonnage impliqué. Nous avons aussi mis en évidence que les erreurs d’échantillonnage commises aux moments où la concentration change rapidement sont celles qui affectent le plus le pouvoir prédictif des R-LSS. Plus intéressant, nous avons mis en exergue que même si différentes R-LSS peuvent avoir des performances similaires lorsque basées sur des temps nominaux, leurs tolérances aux erreurs des temps d’échantillonnage peuvent largement différer. En fait, une considération adéquate de l'impact de ces erreurs peut conduire à une sélection et une utilisation plus fiables des R-LSS. Par une investigation approfondie de différents aspects sous-jacents aux stratégies d’échantillonnages limités, cette thèse a pu fournir des améliorations méthodologiques notables, et proposer de nouvelles voies pour assurer leur utilisation de façon fiable et informée, tout en favorisant leur adéquation à la pratique clinique.

Time Resolved Analysis of C2 Emission from Laser Induced Graphite Plasma in Helium Atmosphere

We report time resolved study of C2 emission from laser produced carbon plasma in presence of ambient helium gas. The 1.06µm: radiation from a Nd:YAG laser was focused onto a graphite target where it·produced a transient plasma. We observed double peak structure in the time profile of C2 species. The twin peaks were observed only after a threshold laser fluence. It is proposed that the faster velocity component in the temporal profiles originates mainly due to recombination processes. The laser fluence and ambient gas dependence of the double peak intensity distribution is also reported.

Spatial and time resolved analysis of CN bands in the laser induced plasma from graphite

Analysis of the emission bands of the CN molecules in the plasma generated from a graphite target irradiated with 1-06/~m radiation pulses from a Q-switched Nd:YAG laser has been done. Depending on the position of the sampled volume of the plasma plume, the intensity distribution in the emission spectra is found to change drastically. The vibrational temperature and population distribution in the different vibrational levels have been studied as function of distance from the target for different time delays with respect to the incidence of the laser pulse. The translational temperature calculated from time of flight is found to be higher than the observed vibrational temperature for CN molecules and the reason for this is explained.

Multivariate ARIMA Compositional Time Series Analysis

A compositional time series is obtained when a compositional data vector is observed at different points in time. Inherently, then, a compositional time series is a multivariate time series with important constraints on the variables observed at any instance in time. Although this type of data frequently occurs in situations of real practical interest, a trawl through the statistical literature reveals that research in the field is very much in its infancy and that many theoretical and empirical issues still remain to be addressed. Any appropriate statistical methodology for the analysis of compositional time series must take into account the constraints which are not allowed for by the usual statistical techniques available for analysing multivariate time series. One general approach to analyzing compositional time series consists in the application of an initial transform to break the positive and unit sum constraints, followed by the analysis of the transformed time series using multivariate ARIMA models. In this paper we discuss the use of the additive log-ratio, centred log-ratio and isometric log-ratio transforms. We also present results from an empirical study designed to explore how the selection of the initial transform affects subsequent multivariate ARIMA modelling as well as the quality of the forecasts

Time series analysis of lava flux

We have applied time series analytical techniques to the flux of lava from an extrusive eruption. Tilt data acting as a proxy for flux are used in a case study of the May–August 1997 period of the eruption at Soufrière Hills Volcano, Montserrat. We justify the use of such a proxy by simple calibratory arguments. Three techniques of time series analysis are employed: spectral, spectrogram and wavelet methods. In addition to the well-known ~9-hour periodicity shown by these data, a previously unknown periodic flux variability is revealed by the wavelet analysis as a 3-day cycle of frequency modulation during June–July 1997, though the physical mechanism responsible is not clear. Such time series analysis has potential for other lava flux proxies at other types of volcanoes.

A comparison of two time-domain analysis procedures in the determination of VO2 kinetics by pseudorandom binary sequence exercise testing

The purpose of this study was to apply and compare two time-domain analysis procedures in the determination of oxygen uptake (VO2) kinetics in response to a pseudorandom binary sequence (PRBS) exercise test. PRBS exercise tests have typically been analysed in the frequency domain. However, the complex interpretation of frequency responses may have limited the application of this procedure in both sporting and clinical contexts, where a single time measurement would facilitate subject comparison. The relative potential of both a mean response time (MRT) and a peak cross-correlation time (PCCT) was investigated. This study was divided into two parts: a test-retest reliability study (part A), in which 10 healthy male subjects completed two identical PRBS exercise tests, and a comparison of the VO2 kinetics of 12 elite endurance runners (ER) and 12 elite sprinters (SR; part B). In part A, 95% limits of agreement were calculated for comparison between MRT and PCCT. The results of part A showed no significant difference between test and retest as assessed by MRT [mean (SD) 42.2 (4.2) s and 43.8 (6.9) s] or by PCCT [21.8 (3.7) s and 22.7 (4.5) s]. Measurement error (%) was lower for MRT in comparison with PCCT (16% and 25%, respectively). In part B of the study, the VO2 kinetics of ER were significantly faster than those of SR, as assessed by MRT [33.4 (3.4) s and 39.9 (7.1) s, respectively; P<0.01] and PCCT [20.9 (3.8) s and 24.8 (4.5) s; P < 0.05]. It is possible that either analysis procedure could provide a single test measurement Of VO2 kinetics; however, the greater reliability of the MRT data suggests that this method has more potential for development in the assessment Of VO2 kinetics by PRBS exercise testing.