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Predicting maize ear grain weight in situ by ear dimensions
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To find out a simple and efficient equation to estimate maize ear grain weight on farm (in situ), twenty three maize crosses along with two synthetics were grown in the field. On the experimental farm of the Dept. of Field Crop Sci., College of Agric., Univ. of Baghdad, seeds of twenty five maize genotypes were grown in the fall season of 2013 with three replicates. At dough stage of the kernels, five naked ears of each experimental units were measured for length and maximum diameter. This will sum up 125 ears of the trial. The volumes of ears were calculated as cylinder (length× r2× 3.1416). Grain weight of all ears were determined after harvesting and drying to 15% grain moisture. A constant was calculated by dividing ear grain weight by each ear volume. Estimated ear grain weights were tested against observed by applying correlation coefficient and it was found to be positive and highly significant (r= 0.998**). The observed and estimated values of ear grain weights were tested by t-test. The two means of observed and estimated ear grain weights were fit to 0.89 probability of t-value. The final equation to estimate ear grain weight in situ is= r2× L× 0.94, where r is radius of ear and L is ear length. However, in case of super hybrids of high ear fertility and kernel filling, estimated ear grain weight will be= r2× L.

Publication Date
Mon Aug 01 2016
Journal Name
2016 3rd International Conference On Computer And Information Sciences (iccoins)
Measurement model of e-SQ dimensions and users' satisfaction in Malaysia IHL
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Publication Date
Thu Feb 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation Variables Effect on Gelation Temperature of Nefopam Hydrochloride intranasal in Situ Gel (Conference Paper) #
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Nefopam (N.F.) HCl is a non-narcotic centrally-acting, non-opioid benzoxazocine analgesic to relieve acute and chronic pain. It exhibits low bioavailability (about 36%) due to its first-pass degradation in the liver.

Intranasal administration has been used as a new route for targeting active brain sites and enhancing the bioavailability of N.F. HCl bypassing hepatic metabolism.

In situ gel of N.F. HCl was prepared by the cold method using different concentrations of Poloxamer 407, Poloxamer 188, HPMC K4M, Carbapol 934, and Hyaluronic acid polymers.

The results show that identification tests are superimposed with references, solubility study shows that N.F. HCl is suitable to be administered intranasally; Compatibi

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Publication Date
Fri Oct 07 2022
Journal Name
Texas Journal Of Engineering And Technology
Estimation of Pore Pressure and In-Situ Stresses for Halfaya Oil Field: A Case Study
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Publication Date
Wed Jan 24 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Development and Characterization of Hyaluronic Acid-Incorporated Thermosensitive Nasal in situ Gel of Meclizine Hydrochloride
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Background: Meclizine hydrochloride (MCZ) is an antihistamine that is used as an antiemetic to prevent and cure nausea and vomiting. Because of its limited water solubility and first-pass metabolism, it exhibits variable absorption. Objective: To formulate and evaluate MCZ as an intranasal in situ gel with increased residence time and permeability. Methods: We made an inclusion complex of MCZ using various cyclodextrins as a complexing agent to help the drug dissolve better. The complexes were studied, and the ones that were better at dissolving were chosen to be used in the creation of an in situ gel with poloxamer 407 (17–20% w/v) and hyaluronic acid (0.25–0.75% w/v). Prepared formulas were subjected to various evaluation tes

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Publication Date
Thu Jun 30 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY OF YIELD AND ITS COMPONENTS OF INTRODUCED VARIETIES OF MAIZE UNDER DIFFERENT PLANTING DENSITIES: STUDY OF YIELD AND ITS COMPONENTS OF INTRODUCED VARIETIES OF MAIZE UNDER DIFFERENT PLANTING DENSITIES
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In order to evaluate the performance of introduced varieties of maize and test them under different levels of plant density, and to determine which of the introduced varieties give a high yield and at what plant density, a field experiment was carried out at Station A in the Department of Field Crops- College of Agricultural Engineering Sciences - University of Baghdad- Jadiriyah, for the fall season 2021, the RCBD design was used with four replications, in a split plot arrangement, the three plant densities (50.000, 70.000, and 90.000 Plant s ha-1) were the main plates, while the varieties represented the secondary factor, which is six varieties of maize, class 2 = 5783 DKC, Class 3 = 6315 DKC, Class 4= 6590 DKC, whic

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Publication Date
Tue Jul 01 2014
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Serum Leptin levels in ovarian polycystic disease and its correlation to body weight
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Background: Poly cystic ovary syndrome is a common disorder in women of reproductive age, it is associated with disturbance of reproductive, endocrine and metabolic functions. The pathophysiology of PCOS appears to be multifactorial and polygenic. Leptin seems to play an important role in pathophysiology of PCOS especially in women with BMI ≥25kg/m2. Objectives: To assess leptin level in both PCOS and healthy women and explore the relation to their body weight and body mass index. Patient and Methods: A total of 120 women were enrolled in this study, 60 women (50%) had PCOS (study group) and the reminder 60 women (50%) were healthy women and considered as control group. BMI was calculated first. Both groups were further sub

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Determination of Serum Adiponectin Levels in Normal Weight Women with Polycystic Ovary Syndrome
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Background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women of reproductive age with primary manifestations of infertility, menstrual dysfunction and clinical or biochemical hyperandrogenism (hirsutism, acne and elevated androgen). Adiponectin is the most abundant adipokine. It has insulin-sensitizing, anti-atherogenic, and antiinflammatory actions.Objective: Low adiponectin levels in women with PCOS have been largely attributed to obesity which is common among these patients. Therefore, the aim of this study was to measure adiponectin levels in normal weight women with PCOS and its contribution to development of disease.Subjects and Methods: Fifty two (52) women were included in this study with age ra

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
Health-Related Quality of Life in Diabetic Women with Comparing Obese & Normal weight
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Background: The prevalence of both obesity & diabetes are increasing all over the world & more in women.  They have a negative impact not only on morbidity & mortality but also on quality of life.

Objectives: To assess the HRQoL with a specific comparison between obese & normal weight among wo

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Scoping Review of Machine Learning Techniques and Their Utilisation in Predicting Heart Diseases
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Heart diseases are diverse, common, and dangerous diseases that affect the heart's function. They appear as a result of genetic factors or unhealthy practices. Furthermore, they are the leading cause of mortalities in the world. Cardiovascular diseases seriously concern the health and activity of the heart by narrowing the arteries and reducing the amount of blood received by the heart, which leads to high blood pressure and high cholesterol. In addition, healthcare workers and physicians need intelligent technologies that help them analyze and predict based on patients’ data for early detection of heart diseases to find the appropriate treatment for them because these diseases appear on the patient without pain or noticeable symptoms,

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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