Tooth Cementum Annulation (TCA) is an age estimation method carried out on thin cross sections of the root of the human tooth. Age is computed by adding the tooth eruption age to the count of annual incremental lines which are called tooth rings and appear in the cementum band. Algorithms to denoise and segment the digital image of the tooth section are considered a crucial step towards compute...

Invasion by exotic plant species can alter ecosystem function and reduce native plant diversity, but relatively little is known about their effects on belowground microbial communities. Here we investigated the effects of exotic cordgrass (Spartina alterniflora) invasion on the distribution of soil bacterial communities in a mangrove nature reserve of the Jiulong River Estuary, southeast China ...

We investigate various questions concerning the reciprocal sum of divisors, or prime Mersenne numbers $2^n-1$. Conditional on Elliott-Halberstam Conjecture and Generalized Riemann Hypothesis, we determine $\max_{n\le x} \sum_{p \mid 2^n-1} 1/p$ to within $o(1)$ \sum_{d\mid 2^n-1}1/d$ a factor $1+o(1)$, as $x\to\infty$. This refines, conditionally, earlier estimates Erd?s Erd?s-Kiss-Pomerance. C...

Sufficient conditions for consistency of statistical models are deduced by using Fréchet-Šmulian’s necessary and sufficient conditions for conditionally compactness relative to the topology of convergence in measure being imposed on the family of associated densities by so-called a control measure . The method relies upon the facts established in [4] where sufficient conditions for consistency ...

In a Bayesian network with continuous variables containing a variable(s) that is a conditionally deterministic function of its continuous parents, the joint density function does not exist. Conditional linear Gaussian distributions can handle such cases when the deterministic function is linear and the continuous variables have a multi-variate normal distribution. In this paper, operations requ...

In a Bayesian network with continuous variables containing a variable(s) that is a conditionally deterministic function of its continuous parents, the joint density function for the variables in the network does not exist. Conditional linear Gaussian distributions can handle such cases when the deterministic function is linear and the continuous variables have a multi-variate normal distributio...

We illustrate several recent results on efficient estimation for semiparametric time series models with two types of AR(1) models: having independent and centered innovations, and having general and conditionally centered innovations. We consider in particular estimation of the autoregression parameter, the stationary distribution, the innovation distribution, and the stationary density.

When a hybrid Bayesian network has conditionally deterministic variables with continuous parents, the joint density function for the continuous variables does not exist. Conditional linear Gaussian distributions can handle such cases when the continuous variables have a multi-variate normal distribution and the discrete variables do not have continuous parents. In this paper, operations require...

An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its parents). In this case, the joint density function for the variables in the network does not exist. Conditional linear Gaussian (CLG) distributions can handle such cases when all variables are normally distributed. In this...