The Weibull-Geometric distribution

In this paper we introduce, for the first time, the Weibull-Geometric distribution which generalizes the exponential-geometric distribution proposed by Adamidis and Loukas (1998). The hazard function of the last distribution is monotone decreasing but the hazard function of the new distribution can take more general forms. Unlike the Weibull distribution, the proposed distribution is useful for modeling unimodal failure rates. We derive the cumulative distribution and hazard functions, the density of the order statistics and calculate expressions for its moments and for the moments of the order statistics. We give expressions for the R\'enyi and Shannon entropies. The maximum likelihood estimation procedure is discussed and an algorithm EM (Dempster et al., 1977; McLachlan and Krishnan, 1997) is provided for estimating the parameters. We obtain the information matrix and discuss inference. Applications to real data sets are given to show the flexibility and potentiality of the proposed distribution

Bayesian Life Test Planning for the Log-Location-Scale Family of Distributions

This paper describes Bayesian methods for life test planning with censored data from a log-location-scale distribution, when prior information of the distribution parameters is available. We use a Bayesian criterion based on the estimation precision of a distribution quantile. A large sample normal approximation gives a simplified, easy-tointerpret, yet valid approach to this planning problem, where in general no closed form solutions are available. To illustrate this approach, we present numerical investigations using the Weibull distribution with Type II censoring. We also assess the effects of prior distribution choice. A simulation approach of the same Bayesian problem is also presented as a tool for visualization and validation. The validation results generally are consistent with those from the large sample approximation approach

Smectic ordering in liquid crystal - aerosil dispersions II. Scaling analysis

Liquid crystals offer many unique opportunities to study various phase transitions with continuous symmetry in the presence of quenched random disorder (QRD). The QRD arises from the presence of porous solids in the form of a random gel network. Experimental and theoretical work support the view that for fixed (static) inclusions, quasi-long-range smectic order is destroyed for arbitrarily small volume fractions of the solid. However, the presence of porous solids indicates that finite-size effects could play some role in limiting long-range order. In an earlier work, the nematic - smectic-A transition region of octylcyanobiphenyl (8CB) and silica aerosils was investigated calorimetrically. A detailed x-ray study of this system is presented in the preceding Paper I, which indicates that pseudo-critical scaling behavior is observed. In the present paper, the role of finite-size scaling and two-scale universality aspects of the 8CB+aerosil system are presented and the dependence of the QRD strength on the aerosil density is discussed.Comment: 14 pages, 10 figures, 1 table. Companion paper to "Smectic ordering in liquid crystal - aerosil dispersions I. X-ray scattering" by R.L. Leheny, S. Park, R.J. Birgeneau, J.-L. Gallani, C.W. Garland, and G.S. Iannacchion

Progressive Telomere Dysfunction Causes Cytokinesis Failure and Leads to the Accumulation of Polyploid Cells

Most cancer cells accumulate genomic abnormalities at a remarkably rapid rate, as they are unable to maintain their chromosome structure and number. Excessively short telomeres, a known source of chromosome instability, are observed in early human-cancer lesions. Besides telomere dysfunction, it has been suggested that a transient phase of polyploidization, in most cases tetraploidization, has a causative role in cancer. Proliferation of tetraploids can gradually generate subtetraploid lineages of unstable cells that might fire the carcinogenic process by promoting further aneuploidy and genomic instability. Given the significance of telomere dysfunction and tetraploidy in the early stages of carcinogenesis, we investigated whether there is a connection between these two important promoters of chromosomal instability. We report that human mammary epithelial cells exhibiting progressive telomere dysfunction, in a pRb deficient and wild-type p53 background, fail to complete the cytoplasmatic cell division due to the persistence of chromatin bridges in the midzone. Flow cytometry together with fluorescence in situ hybridization demonstrated an accumulation of binucleated polyploid cells upon serial passaging cells. Restoration of telomere function through hTERT transduction, which lessens the formation of anaphase bridges by recapping the chromosome ends, rescued the polyploid phenotype. Live-cell imaging revealed that these polyploid cells emerged after abortive cytokinesis due to the persistence of anaphase bridges with large intervening chromatin in the cleavage plane. In agreement with a primary role of anaphase bridge intermediates in the polyploidization process, treatment of HMEC-hTERT cells with bleomycin, which produces chromatin bridges through illegimitate repair, resulted in tetraploid binucleated cells. Taken together, we demonstrate that human epithelial cells exhibiting physiological telomere dysfunction engender tetraploid cells through interference of anaphase bridges with the completion of cytokinesis. These observations shed light on the mechanisms operating during the initial stages of human carcinogenesis, as they provide a link between progressive telomere dysfunction and tetraploidy

Quantitative imaging of concentrated suspensions under flow

We review recent advances in imaging the flow of concentrated suspensions, focussing on the use of confocal microscopy to obtain time-resolved information on the single-particle level in these systems. After motivating the need for quantitative (confocal) imaging in suspension rheology, we briefly describe the particles, sample environments, microscopy tools and analysis algorithms needed to perform this kind of experiments. The second part of the review focusses on microscopic aspects of the flow of concentrated model hard-sphere-like suspensions, and the relation to non-linear rheological phenomena such as yielding, shear localization, wall slip and shear-induced ordering. Both Brownian and non-Brownian systems will be described. We show how quantitative imaging can improve our understanding of the connection between microscopic dynamics and bulk flow.Comment: Review on imaging hard-sphere suspensions, incl summary of methodology. Submitted for special volume 'High Solid Dispersions' ed. M. Cloitre, Vol. xx of 'Advances and Polymer Science' (Springer, Berlin, 2009); 22 pages, 16 fig

Modeling autosomal dominant Alzheimer's disease with machine learning

INTRODUCTION: Machine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease. METHODS: Longitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non-carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status. RESULTS: The Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2  = 0.95), fluorodeoxyglucose (R2  = 0.93), and atrophy (R2  = 0.95) in mutation carriers compared to non-carriers. DISCUSSION: Results suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions