In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.

Soils that cause effective damages to engineer structures (such as pavement and foundation) are called problematic or difficult soils (include collapsible soil, expansive soil, etc.). These damages occur due to poor or unfavorited engineering properties, such as low shear strength, high compressibility, high volume changes, etc. In the case of expansive soil, the problem of the shrink-swell phenomenon, when the soil reacts with water, is more pronounced. To overcome such problems, soils can be treated or stabilized with many stabilization ways (mechanical, chemical, etc.). Such ways can amend the unfavorited soil properties. In this review, the pozzolanic materials have been selected to be presented and discussed as chem

ABSTRACT This study presents an efficient approach for the separation and preconcentration of norepinephrine (NOR) from pharmaceutical formulations, environmental water, and human urine samples using a dispersive micro – solid phase extraction (DμSPE) technique employing magnetic nanoadsorbents. Two adsorbents, Fe3O4@TTAB and Fe3 O4@SiO2@TTAB, were prepared by functionalising iron oxide and silicacoated iron oxide nanoparticles with the cationic surfactant tetradecyltrimethylammonium bromide (TTAB). NOR was first converted into a sensitive diazonium dye via reaction with diazotised sulphamethazine and then extracted using mixed ademicelle – hemimicelle magnetic solid-phase extraction, followed by spectrophotometric quantification. Key

Phosphorus‐based Schiff base were synthesized by treating bis{3‐[2‐(4‐amino‐1.5‐dimethyl‐2‐phenyl‐pyrazol‐3‐ylideneamino)ethyl]‐indol‐1‐ylmethyl}‐phosphinic acid with paraformaldehyde and characterized as a novel antioxidant. Its corresponding complexes [(VO)₂L(SO₄)₂], [Ni₂LCl₄], [Co₂LCl₄], [Cu₂LCl₄], [Zn₂LCl₄], [Cd₂LCl₄], [Hg₂LCl₄], [Pd₂LCl₄], and [PtL

A novel azo dye was prepared by reacting the diazonium salt of 3-aminophenol with 8-hydroxyquinoline and subsequently used to prepare a series of Ni+2, Pd+2, Pt+4, and Cu+2 complexes. The ligand structure was characterized via1H-and 13C-nuclear magnetic resonance spectroscopy. The as-synthesized materials were characterized via Fourier-transform infrared, ultraviolet‒visible, and mass spectroscopy, as well as thermo gravimetry, differential scanning calorimetry, and elemental analysis. Conductivity, magnetic susceptibility, and the metal and chloride contents of the complexes were also determined. The ligand exhibited a trigonal geometry, whereas the Cu+2, Pd+2, Pt+4, and Ni+2 complexesexhibited tetrahedral, square planar, octahedral, and

Modified unsaturated polyester (MUPE) was blended with Cellulose (Cls) and with ethyl cellulose (ECls) at ambient conditions in the presence of ethyl methyl ketone peroxide (EMKP) as hardener. The blends containing different weight percentages (5-25 %) of Cls or ECls. Mechanical properties (impact strength, hardness, and bending) and dielectric constant were determined. The results observed that Cls increases the impact strength, hardness, and dielectric constant and decreases the bending of the MUPS, while ECls causes an increase in the three mechanical behaviours and a decrease in the dielectric constant of the MU-PS.

A survey of haemoproteids among the eight species of Iraq rallids were carried out in the
middle, south, and west of Iraq. Two haemoproteods were recorded, Haeomproteus porzanae
(Galli-Valerio, 1907) as a new record for Iraq and the new species H. baghdadensis described
from Fulica atra L. collected in the middle of Iraq.

Background: This study aimed to determine the cephalometric values of tetragon analysis on a sample of Iraqi adults with normal occlusion. Material and methods: Forty digital true lateral cephalometric radiographs belong to 20 males and 20 females having normal dental relation were analyzed using AutoCAD program 2009. Descriptive statistics and sample comparison with Fastlicht norms were obtained. Results: The results showed that maxillary and mandibular incisors were more proclined and the maxillary/mandibular planes angle was lower in Iraqi sample than Caucasian sample. Conclusion: It's recommended to use result from this study when using tetragon analysis for Iraqis to get more accurate result.

The new multidentate Schiff-base (E)-6,6′-((1E,1′E)-(ethane-1,2-diylbis(azan-1-yl-1-ylidene))bis(methan-1-yl-ylidene))bis(4-methyl-2-((E)(pyridine-2-ylmethylimino)methyl)phenol) H2L and its polymeric binuclear metal complexes with Cr(III), Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II) are reported. The reaction of 2,6-diformyl-4-methyl-phenol with ethylenediamine in mole ratios of 2:1 gave the precursor 3,3′-(1E,1′E)-(ethane-1,2-diylbis(azan-1-yl-1ylidene))bis(methan-1-yl-1-ylidene)bis(2-hydroxy-5-methylbenzaldehyde) W. Condensation of the precursor with 2-(amino-methyl)pyridine in mole ratios of 1:2 gave the new N6O2 multidentate Schiff-base ligand H2L. Upon complex formation, the ligand behaves as a dibasic oct

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class