The study was conducted out at the Ministry of Agriculture's Poultry Research Station/Animal ResourcesDepartment/Agricultural Research Center. To see how body weight (BW) and leptin hormone (LEP) levels inbreeder blood affect fertility and hatchability. 140 Iraqi local laying chickens (120 females + 20 males) aged 28weeks were used in the study. Following the numbering of The experiment was divided into three periods,each lasting 28 days, during which the breeder's live body weight was recorded and divided into two categories(greater than 1.5 kg and less than 1.5 kg), and blood samples were collected at the end of each period todetermine the concentration of leptin hormone in the breeders' blood. For comparison between mothers'performance, hormone concentration is separated into three groups: high, medium, and low, and according tothe interaction between body weight and leptin concentration to compare between mothers' performance.The results indicated a significant increase (p<0.05) in the concentration of cholesterol, high-density lipoprotein(HDL), low-density lipoprotein (LDL), very low-density lipoprotein (VLDL), and triglyceride (TG). Linearitybetween the studied traits and leptin concentration levels, by calculating the regression and correlationcoefficients, and adopting the hypothetical approach in estimating the prediction results to reach the bestpredictive values that approximate reality. We conclude from this study that body weight and theconcentration of leptin have unspecified effects on the serom chemical characteristics of laying hens.
KE Sharquie, AA Noaimi, MA Al-Shukri, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3
The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.
Introduction: Cardiovascular diseases are the main cause of death among type 2 diabetic patients. Higher levels of plasminogen activator urokinase receptor have been found to predict morbidity and mortality across acute and chronic diseases in the common populace. This study aims to explore the role of serum plasminogen activator urokinase receptor levels as a cardiometabolic risk factor among type 2 diabetic Iraqi patients. Methods: Seventy type 2 diabetic patients (40 male and 30 female) (mean age: 46.20±7.56 years) participated in this study; 35 patients were with cardiovascular disease and 35 were without cardiovascular disease; their ages range was 40-55 years. In addition, 30 individuals who apparently healthy were selected a
... Show MoreUnconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria. Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core. Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um
... Show MoreAmputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte
... Show MoreThe Frequency-hopping Spread Spectrum (FHSS) systems and techniques are using in military and civilianradar recently and in the communication system for securing the information on wireless communications link channels, for example in the Wi-Fi 8.02.X IEEE using multiple number bandwidth and frequencies in the wireless channel in order to hopping on them for increasing the security level during the broadcast, but nowadays FHSS problem, which is, any Smart Software Defined Radio (S-SDR) can easily detect a wireless signal at the transmitter and the receiver for the hopping sequence in both of these, then duplicate this sequence in order to hack the signal on both transmitter and receiver messages using the order of the se
... Show MoreBackground Methotrexate (MTX) is a classical folic acid antagonist widely used in the treatment of malignant and non-malignant disorders. However, its clinical application is often restricted by concomitant adverse effects, including renal damage. Numerous studies have highlighted the role of oxidative stress and inflammation in mediating MTX-related nephrotoxicity. Therefore, the current study aimed to explore the possible renoprotective action of Citronellol (CT), a natural compound with prominent antioxidant and anti-inflammatory activities, against nephrotoxicity induced by MTX. Methods To fulfill our objective, 24 adult male Wistar rats were randomly allocated into four groups: control, MTX, 100 mg/kg CT plus MTX and 200 mg/kg C
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