Abiotic stresses including salinity are the major limiting factors of growth and crop production worldwide. Microbial endophytes as the most important soil microorganisms, by modifying plants at genetical, physiological and ecological levels increase their yield per area unit and provide the possibility of crop production in saline and arid soils or climates with biotic and abiotic stresses. Th...

Drought stress is the major problem in arid and semi-arid regions of the world. Investigating the response of different cultivars of crop plants to drought stress can help to select the tolerant ones for agriculture in arid lands. In this study, a greenhouse experiment was conducted as a factorial experiment based on completely randomized design with two common bean cultivars (Phaseolus vulgari...

This study assessed the chemical and microbial contents in the water of public swimming pools in Akwa Ibom State, Nigeria. A total of 16 public pools were selected through probability sampling from the 32 pools that existed in the five urban areas of Akwa Ibom State. Water samples were collected from the sampled pools and tested in the laboratory for chemical and microbial contents. Results sho...

The aim of this paper is to study continuum models for surface diffusion taking into account free adatoms on the surface, which is of particular importance in the (self-assembled) growth of nanostructures. The extended model yields a coupled system of parabolic differential equations for the surface morphology and the adatom density, involving a cross-diffusion structure. We investigate two dif...

We show that it is possible, for every machine universal for Kolmogorov complexity, to enumerate the lexicographically least description of a length n string in O(n) attempts. In contrast to this positive result for strings, we find that, in any Kolmogorov numbering, no enumerator of nontrivial size can generate a list containing the minimal index of a given partial-computable function. One can...

In this paper new methodologies for clustering and dimensionality reduction of large data sets are illustrated using both a least-squares and maximum likelihood approach. The methodologies are described by both real applications and Monte Carlo simulations.