A field experiment was carried out at the research station of the College of Agriculture - Wasit University / Kut, during the fall season 2021 in soil with texture (sandy mixture) using the RCBD design in the arrangement of splintered plates and with three replications, to study the effect of spraying different combinations of organic emulsion (Appetizer) and NPK nano fertilizer with urea fertilizer on the growth of synthetic cultivars of yellow corn. The main panels included three synthetic varieties of yellow corn (Fajr1, Sumer and Baghdad3), which symbolized by (V1,V2,V3) in sequence, while the secondary panels included five fertilization treatments in which mineral fertilizer (urea) was used 46% nitrogen with the full recommendation (300 kg/ha-1) (control treatment) symbolized by T1 and (adding urea according to the recommendation with the addition of the organic emulsion (Appetizer) in two batches before flowering and full flowering) and symbolized by T2 and (adding urea according to the recommendation with nano-NPK in two batches before flowering and full flowering) and symbolized by T3 and (reduction of the recommendation treatment in the first and second batches with the addition of the organic emulsion (Appetizer) in two batches before flowering and full flowering) and symbolized by T4 and (reduction of the recommendation treatment in the first and second batches with the addition of nano-NPK in two batches before flowering and full flowering) It is symbolized by T5. The results showed that there were significant differences between the different fertilization treatments, as the T5 nano fertilization treatment achieved the highest average in most of the growth and quality indicators, It gave the highest average number of days from planting up to 75% of male flowering amounted to 68.00 days and the highest average number of days from planting to 75% of female flowering amounted to 73.44 days and the highest plant height (172.96 cm) and ear height (70.01 cm), the number of leaves per plant (15.23) and the content of The chlorophyll of the leaf under the ear (60.09). The results also showed that the Baghdad3 variety excelled in most of the growth indicators and gave the highest average number of days from planting up to 75% of male flowering amounting to 66.07 days and the highest average number of days from planting up to 75% of female flowering amounted to 72.00 days and the highest plant height (170.04 cm) and ear height (67.11 cm), the number of leaves per plant (14.26), the chlorophyll content of the leaf under the ear (55.49). The interaction between fertilization treatments and cultivars was not significant for most of the growth characteristics.
Aim of the study is to find any correlation between obesity (insulin resistance) and type I diabetes in children. Obesity and diabetes mellitus are the common health problems, and obesity is common cause of the insulin resistance. The results revealed marked increased in glucose, insulin, HbAlc and insulin resistance in obese diabetic type I patients comparing to control group they were obese and non-obese found to be within normal values for glucose, insulin, FIbAlc , and insulin resistance.
We can summarize the main risk factors for type 2 diabetes mellitus (T2DM) by looking at our nutrition, age, and lifestyle. β-cell dysfunction and insulin resistance (IR) are outcomes of the pathophysiology of type 2 diabetes. As an indirect result of IR on important metabolic enzymes, lipid and lipoprotein abnormalities are also a factor in T2DM patients. Recent research has indicated that lipid fluctuation may be the cause of poor glucose metabolism as well as one of its effects. Fatty acids (FAs) affect cell membrane fluidity and permeability, insulin receptor binding and signaling, and the translocation of glucose transporters. Therefore, it is suggested that FAs might play a crucial part in the emergence of IR and T2DM.
Abstract* Backgrounds The retention of the maxillary complete denture may be influenced by adequate recording in the patient’s mouth, marking, and carving of the post-dam on the maxillary cast. Failure to do so may lead to loss of retention. Successful denture construction with patient’s comfort could be achieved by effective methods of recording, marking, and carving of the post-dam. The aim of the study was to assess Iraqi dentists in their knowledge and application of the post-dam in maxillary complete dentures. Methods Questionnaires were distributed randomly through online Google Forms and 118 Iraqi dentists with different academic degree participated in the study. A multinomial logistic regression model was also used to ass
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Background: The rapid integration of Artificial Intelligence (AI) into healthcare necessitates that nursing education evolves to equip students with essential technological competencies. Objectives: To explore pediatric nursing students' perceptions of AI in nursing and analyze associations with sociodemographic factors and prior AI knowledge. Methods: A descriptive cross-sectional study was conducted from December 2024 to March 2025 across five universities in Baghdad. A non-probability sample of 500 pediatric nursing students completed the Shinners Artificial Intelligence Perception (SAIP) tool. Data were analyzed using descriptive statistics and inferential comparisons (t-tests/ANOVA) via SPSS. Results: Participants had a mean ag
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Colors are universal, and throughout the ages, they have been associated with
various religious, social and spiritual meanings. They symbolize a galaxy of things
to designate certain ideas or symbols that are sometimes contradictory.
The present study is an attempt to investigate colors, their meanings and
symbolism, and the approaches to translating color idioms from English into
Arabic. It fathoms one of the thorny areas for translation theorists let alone
practitioners. Various definitions, classifications of types and symbolism across
cultures are provided. After reviewing idioms and methods of translating them, a
survey of 114 sentences that include color idioms was conducted to see which
method is mostly
In this work, satellite images classification for Al Chabaish marshes and the area surrounding district in (Dhi Qar) province for years 1990,2000 and 2015 using two software programming (MATLAB 7.11 and ERDAS imagine 2014) is presented. Proposed supervised classification method (Modified Vector Quantization) using MATLAB software and supervised classification method (Maximum likelihood Classifier) using ERDAS imagine have been used, in order to get most accurate results and compare these methods. The changes that taken place in year 2000 comparing with 1990 and in year 2015 comparing with 2000 are calculated. The results from classification indicated that water and vegetation are decreased, while barren land, alluvial soil and shallow water
... Show MoreThis article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.
This study delves into the design optimization of a hydropower harvesting system, exploring various parameters and their influence on system performance. By modifying the variables within the model to suit different flow conditions, a judiciously optimized design is attainable. Notably, the lift force generated is found to be intricately linked to the strategic interplay of the bluff body's location, cylinder dimensions, and flow velocity. The findings culminate in the establishment of empirical equations, one for lift force and another for displacement, based on the force equation. Many energy harvesting approaches hinge on the reciprocating motion inherent to the structural system. The methodology developed in this study emerges as a pot
... Show MoreThis search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k
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