The present study aimed to determine the genetic divergence of seven maize genotypes (Al-Maha, Sumer, Al-Fajr, Baghdad, 5018, 4 × 1 single hybrid, and 4 × 2 single hybrid) under two varied levels of nitrogen fertilization (92 and 276 kg N ha-1). The experiment occurred in 2022 in a randomized complete block design (RCBD) with a split-plot arrangement and three replications at the College of Agricultural Engineering Sciences, University of Baghdad, Iraq. The nitrogen fertilization levels served as main plots, with the maize genotypes allocated as the subplots. The results revealed that genetic variance was higher than the environmental variance for most traits, and the coefficient of phenotypic variation was close to the genetic variation coefficient under the two levels of nitrogen fertilization. Heritability (broad sense) at the 92 kg N ha-1 (N1 level) was the highest for traits. i.e., ear height, grains per row, grains per ear, individual plant yield, yield per unit area, days to 50% male flowering, leaf area, ear length, rows per ear, and 100-grain weight, with values of 92.556%, 90.760%, 90.123%, 95.007%, 95.007%, 88.976%, 89.974%, 88.748%, 85.521%, and 89.690%, respectively. For the N level of 276 kg ha-1 (N2 level), the heritability in a broad sense was high for the traits, viz., days to 50% male flowering (91.546%), plant height (96.150%), ear height (91.038%), ear length (92.454%), individual plant yield (98.108%), yield in the unit area (98.108%), and plant dry weight (85.488%). The cluster analysis divided the maize genotypes into four and five cluster groups under the nitrogen fertilization level of 92 and 276 kg N ha-1, respectively. These different groups of maize genotypes could be due to the genetic divergence among the genotypes resulting from their varied genetic makeup and origin.
Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreOmentin (or intelectin) is a main visceral fat secretory adipokine. There is a growing interest to link omentin, obesity and co-morbidity factors. The aim of the present study is to evaluate serum omentin and its association to insulin resistance biomarkers, lipid profile and atherogenic indies. This cross – sectional study was conducted in Obesity Research and Therapy Unit-Alkindy College of Medicine by recruiting (115) individuals; 49 males /66 females. Subjects between (20 to 60) years of age were selected and classified into two groups according to their Body mass index (BMI). Group1 involved healthy lean volunteers (25 male/ 36 female; BMI 18.5 - 24.9). Group2 involved obese subjects; (24 male / 36 female with BMI ≥ 30). The s
... Show MoreThe topic of the research on the Observatory of the Walls on Jurisprudential Matters in the Hanafi Fiqh, by Imam San’a Allah bin Ali bin Khalil Al-Ala’iyya Wai al-Naqshbandi, al-Rumi, who died in 1137 AH, which includes seven chapters, the first section of it concerning division and related matters, and the second section in the adaptation It is the apportionment of benefits in common objects, the third section, which pertains to lines, surfaces, and bodies, the fourth section, which concerns the inclined wall and certification, and the fifth section, which concerns the provisions of the walls and its claims, and the sixth section, which concerns the door of roads and doors, the opening of the skylight, the sails of the wing, the can
... Show MoreThis research aims to find out the relationship of risk behavior & job satisfaction for workers in the emergency program in the international relief agency (UNRWA) in the Gaza Strip and the level of each of them, and to achieve that we have been conducting research on the strength of "210" sample employees of the emergency program staff in the international relief agency in Gaza governorates, and try to answer the research questions the researcher through the use of measurements of risk behavior and job satisfaction are two of the researcher, The researcher has used several statistical methods to identify the validity and reliability of scales and access to research and interpretations of the results, and these methods: the m
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