Journal de biométrie et biostatistique

Previous studies of handwriting grip kinetics have demonstrated the ability to classify writers based on the topography of grip forces associated with signature writing. However, the topographic representation requires a large array of individual sensors in practice. The possibility of differentiating participants on the basis of a summative, temporal force profile is yet unknown. In this study, we investigated the variability of features derived from a time-evolving total grip force profile. Using an instrumented writing utensil, twenty adult participants provided 600 samples of a well-practised bogus signature over a period of 10 days. Deploying a combination of temporal, spectral and information-theoretic features, a linear discriminant analysis classifier outperformed nonparametric and nonlinear classifier alternatives and discriminated among participants with an average misclassification rate of 5.8% as estimated by cross-validation. These results suggest the existence of a unique kinetic profile for each writer even when generating the same written product. Our findings highlight the potential of using grip kinetics as a biometric measure.

Newfoundland and Labrador NL has had the highest percentage of overweight/obese residents in Canada since 2007. This complex trait is determined by multiple genetic and environmental factors that interact with one another. The existing studies examine such factors under the assumption that they are measured accurately. However, error- prone environmental and genetic factors are unavoidable. The impact of ignoring these errors varies from bias to false results in detecting associations. Motivated by COD-ING study, we present methodologies to estimate model parameters, while accounting for measurement error and misclassification. We applied bias-corrected methods for three separate studies: candidate-gene association study and two gene-environment interaction models, where both environmental and genetic factors are subject to error. Our results based on simulation studies show that the proposed methodologies perform quite satisfactory.

Background: The instrumental activities of daily living (IADLs) are important index of physical functioning in older adult studies. These count outcomes with a large proportion of zeros are often collected in longitudinal studies. Data were from the Hispanic Established Population for Epidemiological Study of the Elderly (HEPESE), a four wave (seven years) longitudinal study of community-dwelling elderly Mexican-Americans. There were excess zeros IADLs observed during follow-up.
Methods: We present semiparametric zero-inflated Poisson (ZIP) and hurdle model with random effects to evaluate IADLs in the context of excess zeros. Results: Age, education, household income, marital status, smoking, cognitive functioning and prescription medication use were not significantly associated with IADLs. The counts of IADLs changed with age nonlinearly.
Conclusions: zero-inflated Poisson (ZIP) and hurdle model with random effect fits the IADLs counts with excess zeros in longitudinal studies.

This paper is concerned with face recognition under uncontrolled conditions, e.g. at a distance in surveillance scenarios, and post-rioting forensic, whereby captured face images are severely degraded/blurred and of low resolution. This is a tough challenge due to many factors including difficulties in determining a model for image degradation that encompasses a range of realistic capturing conditions. We present the results of our investigations into recently developed Compressive Sensing (CS) theory to develop scalable face recognition schemes using a variety of overcomplete dictionaries that construct super-resolved face images from any input low-resolution degraded face image. We shall demonstrate that deterministic as well as non-deterministic dictionaries that do not involve the use of face image information but satisfy some form of the Restricted Isometry Property (RIP) used for CS can achieve face recognition accuracy levels as good a, if not better than, those achieved by dictionaries, proposed in the literature, that are learnt from face image databases using elaborate procedures. We shall elaborate on how this approach helps in crime fighting and terrorism.

Two nonparametric tests are proposed in testing for k nondecreasing treatment effects under a mixed design consisting of a completely randomized portion and a randomized block portion. The randomized block portion may contain missing observations for some of the treatments within a block. A simulation study is conducted to estimate the powers of the two tests for 3, 4, and 5 treatments under a variety of different treatment effects and underlying distributions. Powers are estimated when the randomized block portion is 1/4, 1/3, 1/2, 1.0, 1.5, 2.0, 3.0 and 4.0 times the completely randomized portion. A recommendation as to which test has higher powers is given.

The C677T MTHFR polymorphism is distributed widely among ethnics populations and showing a high heterogeneity. The fact that there were no published data on the prevalence of C677T MTHFR polymorphism in Bosnia and Herzegovina prompted us to determine its prevalence in sample of Bosnian population.
Two hundred and seven unrelated, apparently healthy subjects from Southern east Bosnia were included in study. Genotyping of C677T MTHFR polymorphism was done using polymerase chain reaction (PCR) followed by restriction digestion (RFLP) with HinfI enzyme.
Out of 207 healthy subjects, 44.44% were heterozygous and 11.11% were homozygous for C677T MTHFR polymorphism. Allele and genotype frequency of MTHFR C677T did not differ between males and females carriers (X2=0.87; df=1; P=0.350).This study is the first to report frequency of C677T polymorphism in healthy Bosnian population. Frequency of the T allele and C677T MTHFR genotype observed in this study is consistent with the data from literature.

To analyze responses of solid tumor to treatments and to compare treatment effects with antitumor therapies, we applied semiparametric mixed-effects models to fit tumor volumes measured over a period. The population and individual nonparametric functions were approximated by smoothing spline. We also proposed an intuitive method for a comparison of the antitumor effects of two different treatments. Biological interpretation was also discussed.