The Lazy Bootstrap. A Fast Resampling Method for Evaluating Latent Class Model Fit

The latent class model is a powerful unsupervised clustering algorithm for categorical data. Many statistics exist to test the fit of the latent class model. However, traditional methods to evaluate those fit statistics are not always useful. Asymptotic distributions are not always known, and empirical reference distributions can be very time consuming to obtain. In this paper we propose a fast resampling scheme with which any type of model fit can be assessed. We illustrate it here on the latent class model, but the methodology can be applied in any situation. The principle behind the lazy bootstrap method is to specify a statistic which captures the characteristics of the data that a model should capture correctly. If those characteristics in the observed data and in model-generated data are very different we can assume that the model could not have produced the observed data. With this method we achieve the flexibility of tests from the Bayesian framework, while only needing maximum likelihood estimates. We provide a step-wise algorithm with which the fit of a model can be assessed based on the characteristics we as researcher find important. In a Monte Carlo study we show that the method has very low type I errors, for all illustrated statistics. Power to reject a model depended largely on the type of statistic that was used and on sample size. We applied the method to an empirical data set on clinical subgroups with risk of Myocardial infarction and compared the results directly to the parametric bootstrap. The results of our method were highly similar to those obtained by the parametric bootstrap, while the required computations differed three orders of magnitude in favour of our method.Comment: This is an adaptation of chapter of a PhD dissertation available at https://pure.uvt.nl/portal/files/19030880/Kollenburg_Computer_13_11_2017.pd

Enterohemorrhagic Escherichia coli with particular attention to the German outbreak strain O104:H4

This review deals with the epidemiology and ecology of enterohemorrhagic Escherichia coli (EHEC), a subset of the verocytotoxigenic Escherichia coli (VTEC), and subsequently discusses its public health concern. Attention is also given to the outbreak strain O104:H4, which has been isolated as causative agent of the second largest outbreak of the hemolytic uremic syndrome worldwide, which started in Germany in May 2011. This outbreak strain is not an EHEC as such but possesses an unusual combination of EHEC and enteroaggregative E. coli (EAggEC) virulence properties

Influence of sow dietary polyunsaturated fatty acid source on the immunoglobulin profile of piglets

To examine the effect of different n-3 polyunsaturated fatty acid (PUFA) sources in sow diets on piglets’ immunoglobulin (Ig) profile, two groups of twelve sows each were fed different diets from day 45 of pregnancy and during lactation on two commercial farms. On farm I, a palm oil diet (25 g/kg; PALM) and a linseed oil containing diet (20 g/kg; LIN) were fed. On farm II, the same PALM diet and a fish oil containing diet (20 g/kg; FISH) were fed. All diets contained equal amounts of C18:2n-6 (13 g/kg). One day before parturition, blood (for serum) was taken and shortly after parturition, colostrum was taken from the sows (not from sows on farm I) for determination of Ig levels. On day 5 post partum and the day before weaning, blood (for serum) was taken from 4 piglets of six sows per group (24 piglets in total per group; for 5-d old piglets on farm II, only 6 piglets of the FISH group were sampled). In all samples total IgG, IgA, IgM concentration and specific F4-IgG, -IgA and -IgM titer (Log2 titer) against E. coli were determined. On farm I, the sows of the LIN group showed a trend towards lower IgG titers compared to the PALM group around farrowing (P<0.1). On farm II, the sows on the FISH diet showed a significantly (P<0.05) lower F4-IgG titer compared to the sows fed PALM. The colostrum samples on farm II showed no differences between both groups. On farm I, the 5-d old piglets from the LIN group had significantly higher IgA and IgM concentrations and higher F4-IgA and F4-IgM titers (P<0.05). F4-IgA and F4-IgG titers were also significantly higher at weaning in the LIN group compared to the PALM group. On farm II, the piglets of the FISH group had a significantly higher IgG concentration and F4-IgA titer (P<0.05) and a trend towards a higher IgM concentration (P<0.1) around weaning compared to the PALM group. It seems that fish oil in the maternal diet increases total IgG concentration, while linseed oil reduces total IgG and increases total IgA compared to a palm fat containing diet. Both fish and linseed oil seem to have a positive effect on total IgM concentration compared to the palm diet

Coupling of structural solver and volume-conserving solver for form-finding of membrane structures subjected to ponding

The current study deals with coupling of a volume conserving solver and a structural solver to calculate the static deformation of flexible structures under the load of a given volume of water. The volume-conserving solver contains a horizontal plane representing the free surface of the fluid, which is moved in the non-linear iterations to conserve the volume. The Partitioned approach is chosen to have code modularity and reusability with many structural codes

Numerical energy absorption study of composite tubes for axial impact loadings

This paper focuses on the numerical energy absorption behaviour of pultruded composite tubes under an axial impact loading case. The circular and square cross sectional glass-polyester composite tubes are considered for the study. In order to capture the typical failure modes such as delaminations, lamina bending, axial cracks and fibre fracturing, a new innovative approach was used using multiple shell elements, cohesive elements and pre-defined seams. To predict the correct peak crush load and the corresponding energy absorption, the importance of the numerical modelling of multiple delaminations and triggering are discussed. Two types of triggering were chosen for the study (45⁰ deg chamfering around the edges and a tulip pattern with an included angle between the edges of 60⁰). Finally, the results of this numerical investigation are compared with experimental data. The commercially available finite element code ABAQUS V6.7-3 Explicit was used for this study

A fast strong coupling algorithm for the partitioned fluid–structure interaction simulation of BMHVs

The numerical simulation of Bileaflet Mechanical Heart Valves (BMHVs) has gained strong interest in the last years, as a design and optimisation tool. In this paper, a strong coupling algorithm for the partitioned fluidstructure interaction simulation of a BMHV is presented. The convergence of the coupling iterations between the flow solver and the leaflet motion solver is accelerated by using the Jacobian with the derivatives of the pressure and viscous moments acting on the leaflets with respect to the leaflet accelerations. This Jacobian is numerically calculated from the coupling iterations. An error analysis is done to derive a criterion for the selection of useable coupling iterations. The algorithm is successfully tested for two 3D cases of a BMHV and a comparison is made with existing coupling schemes. It is observed that the developed coupling scheme outperforms these existing schemes in needed coupling iterations per time step and CPU time

Feasibility of using combined EMG and kinematic signals for prosthesis control : A simulation study using a virtual reality environment

Acknowledgment This study was partly supported by a UK Medical Research Council Centenary Award to Keele University.Peer reviewedPublisher PD