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Effect of Drought Stress (Water Deficit) and Plant Density on Productivity of Water and Zea mays (Baghdad Varieties) in Middle Region of Iraq
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The objective of this study was to investigate the drought stress and plant density possibility on water productivity and grain yield of maize (Zea mays L.) (Planting Baghdad 3 synthetic varieties), Field experiment was conducted at Abu Ghraib Research Station (Baghdad) during spring and Autumn seasons of 2016 using a randomized complete block design arranged in split plot with three replications. Three irrigation treatment included: irrigation after depletion 50% of available water (T1), irrigation after depletion 75% of available water (T2) and irrigation after depletion 90% of available water (T3) in the main plots and three plant density which were: 1 seeds hill-1 (D1) giving a uniform plant density of 66666 plants ha-1 , 2 seeds hill1 (D2) giving a uniform plant density of 133332 plants ha-1 and 3 seeds hill-1 (D3) giving a uniform plant density of 266664 plants ha-1 assigned in sub plots. The results showed that the plant density of 66666 plants ha-1 gave highest value for most growth and yield components (day's number to 50% male and female flowering, leaf area, dry matter for root and number of ears per plant) for both seasons, but no significant with plant density of 133332 plants ha-1 . Irrigation at depletion 75% of available water was superior in grain yield and most components of growth, also this treatment not significant compare with irrigation at depletion 50% of available water in all parameter of growth and yield of corn. Irrigation at depletion 75% of available water was saving 21.5 and 12.23% depth of water added compare to irrigation at depletion 50% of available water in spring and autumn season, respectively. The irrigation at depletion 75% of available water gave the highest grain yield 9356 kg ha-1 and plant density D1 gave the highest value 8449 kg ha-1 and not difference with D2 8278 kg ha-1 , but increased compare to D3 treatment.

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Publication Date
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Recovering Time-Dependent Coefficients in a Two-Dimensional Parabolic Equation Using Nonlocal Overspecified Conditions via ADE Finite Difference Schemes
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of The College Of Languages (jcl)
La traducción de LJI ,Robinson Crusoe en la imaginación de los niños . Infants' literature (Robinson Crusoe) in children's imagination
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Resumen

      La literatura infantil es uno de los géneros literarios que incluye varios estilos de la prosa, cuento,  poesía etc. Ha florecido en el siglo XX con la aparición de los autores que dedicaron la mayor parte de su tiempo para escribir sus composiciones para los niños, tomando de las leyendas y las historias populares y religiosas a fin de hacerla sencilla para ser correspondiente con sus edades. La traducción de la literatura infantil lleva a ampliar los horizontes y los conocimientos de los niños cuando conocen las costumbres y las tradiciones de los pueblos. Se sabe que hay muchas dificultades respecto al proceso de la traducirían en cuanto a la comprensión de l

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
A Posteriori L_∞ (L_2 )+L_2 (H^1 )–Error Bounds in Discontinuous Galerkin Methods For Semidiscrete Semilinear Parabolic Interface Problems
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The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use the robust RFCH method with a polychoric correlation matrix in structural equation modeling When you are ordinal data
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Optimizing Blockchain Consensus: Incorporating Trust Value in the Practical Byzantine Fault Tolerance Algorithm with Boneh-Lynn-Shacham Aggregate Signature
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The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen

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Publication Date
Mon Jun 30 2025
Journal Name
Acta Logistica
A business continuity-based framework for risk management in smart supply chains: a fuzzy multi-criteria decision-making approach
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The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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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

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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of Education And Health Promotion
The net atrioventricular compliance in mild to moderate hypertensive patients during the early left ventricle filling: A case series
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BACKGROUND:

The compliance is considered one of the most important parameters which is defined as the change in volume with given change in pressure (dv/dp). It is varying inversely with both diastolic filling and modulus of chamber stiffness.

AIMS:

This study aimed to deduce the net atrioventricular compliance which is affected the trans mitral blood flow.

MATERIALS AND METHODS:

This study focuses on study group of 25 patients (15 males

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Colloid Interface Science
Corrigendum to “Organic acid concentration thresholds for ageing of carbonate minerals: Implications for CO2 trapping/storage” [J. Colloid Interface Sci. 534 (2019) 88–94]
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Erratum for Organic acid concentration thresholds for ageing of carbonate minerals: Implications for CO2 trapping/storage.

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Publication Date
Thu Jun 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Oral Health Status, Salivary MMP-8& Secretory Leukocyte Peptidase Inhibitor (SLPI) Among Uncontrolled Type-I Diabetes Mellitus In Iraqi Patients
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Background: diabetes is a metabolic disease characterized by hyperglycemia that results in deficiency or absence of insulin production. The dental caries and gingivitis/periodontitis are widespread chronic diseases in diabetes. The aim of the present study was determined the salivary matrix metalloproteinase (MMP-8), Secretory Leukocyte Peptidase Inhibitor (SLPI) and oral health status among uncontrolled diabetic group in comparison with healthy control group. Materials and Methods: The total sample composed of 90 adults aged (18-35) years. Divided into 60 uncontrolled diabetic patients (HbA1c >7%) and 30 healthy control group. Unstimulated saliva was collected from each subject with type-I DM, BMI, duration of diabetes, HbA1c%, DMFT, gingi

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