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jih-2981
The Effect of Endosulfan Pesticide in Some Biochemical Parameters of white Mice
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The present study aimed to examine the effect of endosulfan insecticide on some molecular and biochemical parameters in white mice. Thirty mice were separated randomly into three groups for treatment with endosulfan. One group (G1) served as the control, while the other two groups received intraperitoneal injections of endosulfan G2 (3 mg/kg) and G3 (17 mg/kg) twice a week for 21 and 45 days, respectively. A biochemical study by measuring liver  function parameters, including (alanine aminotransferase (ALT) and aspartate aminotransferase (AST)) and kidney function parameters, including (Blood Urea and Creatinine) and malondialdehyde (MDA), catalase activity (CAT). This study also tested DNA damage by comet assay (normal%, low%, medium%, high%). The results of renal function parameters (Blood Urea and Creatinine) were significantly increased in all treated groups after 21 and 45 days exposed to endosulfan compared with control groups. The highest value of blood urea recorded was (49.33 ±0.88 mg/dl) at 17 mg/kg for 45 days compared with the control group, and the highest value of Creatinine recorded was (1.81 ±0.13 mg/dl) at 17 mg/kg for 45 days compared with the control group. Liver function parameters (ALT and AST) significantly increased in all treated groups compared with control groups. The results of MDA, CAT enzyme, were significantly increased in all treated groups after 21 and 45 days compared with control groups. The highest value of MDA recorded was (3.93 ±0.07 μM) at 17 mg/kg for 45 days compared with the control group. Tail DNA (%) showed a significant increase at high concentrations, and the results showed a considerable increase in the severe damage of DNA in the treated group 17 mg\kg b.wt. (25.00 ±1.00)% for 45 days, compared with the control group (3.00 ±1.00) %.

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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Spectral Studies on Cobalt(II), Nickel(II), Copper(II), Palladium(II), Platinum(II, IV), Zinc(II), Cadmium(II) and Mercury(II) Complexes of(1, 2-diaminoethane-N,N'-bis(2- butylidine-3 onedioxime)
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The synthesis of [1,2-diaminoethane-N,N'-bis(2-butylidine-3- onedioxime)] [II2L] and its cobalt(II), nickel(II), copper(II), palladium(II), platinum(II, IV), zinc(II), cadmium(II) and mercury(II) complexes is reported. The compounds were characterised by elemental analyses, spectroscopic methods [I.R, UV-Vis, ('H NMR. and EI mass for H2L)], molar conductivities, magnetic moments. I.R. spectra show that (H2L) behaves as a neutral or mononegative ligand depending on the nature of the metal ions. The molar conductance of the complexes in (DMSO) is commensurate with their ionic character. On the basis of the above measurements, a square planar geometry is proposed for NOD, Pd(II), and Pt(II) complexes, and an octahedr-al structure with trans

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Agricultural And Statistical Sciences
ON ERROR DISTRIBUTION WITH SINGLE INDEX MODEL
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In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimator a Smoothing Technique for Estimating Regression Function
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    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

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Publication Date
Sun Mar 01 2009
Journal Name
Baghdad Science Journal
On Monotonically T2-spaces and Monotonicallynormal spaces
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In this paper we show that if ? Xi is monotonically T2-space then each Xi is monotonically T2-space, too. Moreover, we show that if ? Xi is monotonically normal space then each Xi is monotonically normal space, too. Among these results we give a new proof to show that the monotonically T2-space property and monotonically normal space property are hereditary property and topologically property and give an example of T2-space but not monotonically T2-space.

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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Publication Date
Wed Oct 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
ON DISCRETE WEIBULL DISTRIBUTION
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Most of the Weibull models studied in the literature were appropriate for modelling a continuous random variable which assumes the variable takes on real values over the interval [0,∞]. One of the new studies in statistics is when the variables take on discrete values. The idea was first introduced by Nakagawa and Osaki, as they introduced discrete Weibull distribution with two shape parameters q and β where      0 < q < 1 and b > 0. Weibull models for modelling discrete random variables assume only non-negative integer values. Such models are useful for modelling for example; the number of cycles to failure when components are subjected to cyclical loading. Discrete Weibull models can be obta

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Publication Date
Tue Apr 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving Fuzzy Attribute Quality Control Charts with proposed Ranking Function
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    The attribute quality control charts are one of the main useful tools to use in control of quality product in companies. In this paper utilizing the statistical procedures to find the attribute quality control charts for through fuzzified the real data which we got it from Baghdad Soft Drink Company in Iraq, by using triangular membership function to obtain the fuzzy numbers then employing the proposed ranking function to transform to traditional sample. Then, compare between crisp and fuzzy attribute quality control.

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Application Model for Linear Programming with an Evolutionary Ranking Function
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One of the most important methodologies in operations research (OR) is the linear programming problem (LPP). Many real-world problems can be turned into linear programming models (LPM), making this model an essential tool for today's financial, hotel, and industrial applications, among others. Fuzzy linear programming (FLP) issues are important in fuzzy modeling because they can express uncertainty in the real world. There are several ways to tackle fuzzy linear programming problems now available. An efficient method for FLP has been proposed in this research to find the best answer. This method is simple in structure and is based on crisp linear programming. To solve the fuzzy linear programming problem (FLPP), a new ranking function (R

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
Solving Fuzzy Games Problems by Using Ranking Functions
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In this paper, we deal with games of fuzzy payoffs problem while there is uncertainty in data. We use the trapezoidal membership function to transform the data into fuzzy numbers and utilize the three different ranking function algorithms. Then we compare between these three ranking algorithms by using trapezoidal fuzzy numbers for the decision maker to get the best gains

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