Common walnut (Juglans regia L.) has a long cultivation history, given its highly valuable wood and rich nutritious nuts. The Iranian Plateau has been considered as one of the last glaciation refugia and a centre of origin and domestication for the common walnut. However, a prerequisite to conserve or utilize the genetic resources of J. regia in the plateau is a comprehensive evaluation of the genetic diversity that is conspicuously lacking. In this regard, we used 31 polymorphic simple sequence repeat (SSR) markers to delineate the genetic variation and population stru

This study presents determination of the paleostress magnitudes and orientation of Bekhme Structure in Shaqlawa area northeastern Iraq. Paleostress Analysis of slip-fault measurements is performed using Right dihedral, Lisle diagram and Mohr Circles methods. Depending on Mohr Circles, Bott law and vertical thickness, the magnitudes of the paleostress at the time of the tectonic activity were determined. Firstly, Georient Software was used to estimate the orientation of the paleostresses (σ1, σ2 and σ3). Secondly, using the rupture –friction law, taking into account depth of the overburden and the vertical stress (σv) was calculated to determine the magnitude of the paleostresses (σ1=4500 bars, σ2=1

In this work, silver nanoparticles (AgNPs) were biosynthesized from leaves of Ziziphus mauritiana Lam. jujube plant in Iraq and tested against fungal pathogens. Extract of leaves of Z. mauritiana mixed with 10-3 M AgNO3exposed to slight sunlight for 3 days. Characterization of AgNPs was done using UV-visible spectroscopy, SPM (scanning probe microscopy) and atomic force microscopy (AFM). The change of solution color from pale brown to dark brown and the exhibited maximum peak at 445 nm accepted as an indicator to biosynthesized AgNPs. Aqueous extract of Ziziphus mauritiana is considered as biological reduced and stabilized agent for Ag+ to Ag0. AFM showed the formation of irregular shapes of AgNPs. The biosynthesized silver nanoparticles ha

Kidney damage in workers within environments of highly expected exposure to toxin, including heavy metals, could be a primary marker to expect hazards in population exposed to low levels of many environmental pollutants. The present study was designed to evaluate the possible effect of environmental exposure to cadmium and zinc on renal function among painters in Sulaimani city. Cross sectional study was performed on 37 male painting workers in Sulaimani city. Each worker was interviewed using structured questionnaire. Twenty five non-exposed healthy subjects were included as control group. Venous blood samples (10 ml) were obtained by vein puncture from both subjects and utilized for estimation of serum urea, creatinine levels, serum le

             In general, researchers and statisticians in particular have been usually used non-parametric regression models when the parametric methods failed to fulfillment their aim to analyze the models  precisely. In this case the parametic methods are useless so they turn to non-parametric methods for its easiness in programming. Non-parametric methods can also used to assume the parametric regression model for subsequent use. Moreover, as an advantage of using non-parametric methods is to solve the problem of Multi-Colinearity between explanatory variables combined with nonlinear data. This problem can be solved by using kernel ridge regression which depend o

The various properties of the ground and excited electronic states of coumarins 102 using density functional theory (DFT) and time-dependent density functional theory (TDDFT) was calculated by the B3LYP density functional model with 6-31G(d,p) basis set by Gaussian 09 W program. Spectral characteristics of coumarin102 have been probed into by methods of experimental UV-visible, and quantum chemistry. The UV spectrum was measured in methanol. The optimized structures, total energies, electronic states (HOMO- LUMO), energy gap, ionization potentials, electron affinities, chemical potential, global hardness, softness, global electrophilictity, and dipole moment were measured. We find good agreement between experimental data of UV spectrum and

Arabs knew the art of diction and elocution as part of their life in peace and war and in lamentation, satire, narration and description, as they were distinguished by influential and meaningful speeches in war and battle times, and the most prominent topics of the pre-Islamic rhetoric were pride, enthusiasm, bravery and other meanings related to heroism and call for war. It was not a long time when Arabs paid more attention to this great phonetic phenomenon, as they see that it elevates the status of the word and shows its meanings and significances. The current research aims to reveal the function of diction in conveying the meaning in radio drama.
The research methodology: the researcher adopted the analytic descriptive method gui

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

This paper presents the ability to use cheap adsorbent (corn leaf) for the removal of Malachite Green (MG) dye from its aqueous solution. A batch mode was used to study several factors, dye concentration (50-150) ppm, adsorbent dosage (0.5-2.5) g/L, contact time (1-4) day, pH (2-10), and temperature (30-60)   The results indicated that the removal efficiency increases with the increase of adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature. An SEM device characterized the adsorbent corn leaves. The adsorption's resulting data were in agreement with Freundlich isotherm according to the regression analysis, and the kinetics data followed pseudo-first-or

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi