Multi-scale modeling of Arctic tundra vegetation requires characterization of the heterogeneous tundra landscape, which includes representation of distinct plant functional types (PFTs). We combined high-resolution multi-spectral remote sensing imagery from the WorldView-2 satellite with light detecting and ranging (LiDAR)-derived digital elevation models (DEM) to characterize the tundra landsc...

Objective: The current research is to investigate the relation between deterministic thinking and mental health among drug abusers, in which the role of  cognitive distortions is considered and clarified by focusing on deterministic thinking. Methods: The present study is descriptive and correlative. All individuals with experience of drug abuse who had been referred to the Shafagh Reha...

Diagnosis of soil salinity and characterizing its spatial variability both vertically and horizontally are needed to establish control measures in irrigated agriculture. In this regard, it is essential that salinity development in varying soil depths be known temporally and spatially. Apparent soil electrical conductivity, measured by electromagnetic induction instruments, has been widely used ...

We extend the hypocoercivity framework for piecewise-deterministic Markov process (PDMP) Monte Carlo established in [Andrieu et. al. (2018)] to heavy-tailed target distributions, which exhibit subgeometric rates of convergence equilibrium. make use weak Poincar\'e inequalities, as developed work [Grothaus and Wang (2019)], ideas we adapt PDMPs interest. On way report largely potential-independe...

Given the above model of stationary random spatial effects { ( ) : } s s R   , our ultimate objective is to apply these concepts to spatial models involving global trends, ( ) s  , i.e., to spatial stochastic models of the form, ( ) ( ) ( ) , Y s s s s R      . In continuous spatial data analysis, the most fully developed models of this type focus on spatial prediction, where values of ...

Deterministic dependency parsing has often been regarded as an efficient algorithm while its parsing accuracy is a little lower than the best results reported by more complex methods. In this paper, we compare deterministic dependency parsers with complex parsing methods such as generative and discriminative parsers on the standard data set of Penn Chinese Treebank. The results show that, for C...