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Improving Nitrogen and Phosphorus Efficiency for Optimal Plant Growth and Yield
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Nitrogen (N) and phosphorus (P) are the most important nutrients for crop production. The N contributes to the structural component, generic, and metabolic compounds in a plant cell. N is mainly an essential part of chlorophyll, the compound in the plants that is responsible for photosynthesis process. The plant can get its available nitrogen from the soil by mineralizing organic materials, fixed-N by bacteria, and nitrogen can be released from plant as residue decay. Soil minerals do not release an enough amount of nitrogen to support plant; therefore, fertilizing is necessary for high production. Phosphorous contributes in the complex of the nucleic acid structure of plants. The nucleic acid is essential in protein synthesis regulation; therefore, P is important in cell division and development of new plant tissue. P is one of the 17 essential nutrients for plant growth and related to complex energy transformations in the plant. In the past, growth in production and productivity of crops relied heavily on high-dose application of N and P fertilizers. However, continue adding those chemical fertilizers over time has bad results in diminishing returns regarding no improvement in crop productivity. Applying high doses of chemical fertilizers is a major factor in the climate change in terms of nitrous oxide gas as one of the greenhouse gas and eutrophication that happens because of P pollution in water streams. This chapter speaks about N and Puse efficiency and how they are necessary for plant and environment.

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Publication Date
Mon Nov 28 2016
Journal Name
Separation Science And Technology
Using sewage sludge as a permeable reactive barrier for remediation of groundwater contaminated with lead and phenol
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Publication Date
Sat Jun 02 2018
Journal Name
Agroforestry Systems
Biomass and buffer management practice effects on soil hydraulic properties compared to grain crops for claypan landscapes
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Publication Date
Fri Dec 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A comparative study of Gaussian mixture algorithm and K-means algorithm for efficient energy clustering in MWSN
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Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

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Publication Date
Sun Jan 03 2010
Journal Name
Journal Of Educational And Psychological Researches
The non right behavior appearance for the kindergarten children and its relation with the kindergarten teaching style
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The kindergarten teacher play a role in fixing the children behavior so she must plant the value and the habits that make a positive behavior and accepted by the society so the teacher must know all the right educational psychological styles to fix the children behavior and make them accepted psychologically and socially so the problem of the research start from knowing the relation between the methods of dealing with the kindergarten’s teachers and the non right behavior appearance for the kindergarten children. The current research aims to measure the negative behavior appearance of the children of kindergarten and distinguish it according to (sex and levels) and to distinguish the most using styles by the teachers of kinderg

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Publication Date
Wed Jan 01 2020
Journal Name
Petroleum And Coal
Evaluation of geomechanical properties for tight reservoir using uniaxial compressive test, ultrasonic test, and well logs data
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Publication Date
Fri Dec 23 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and in-vitro Evaluation of Secnidazole as Periodontal In-situ Gel for Treatment of Periodontal Disease
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This study aims to develop a thermosensitive mucoadhesive periodontal in situ gel of secnidazole for local release of drug for treatment of periodontitis, in order to increase the drug residence time and to increase patient compliance while lowering the side effects of the drug.

Cold method was used to prepare 30 formulas of secnidazole periodontal in situ gel, using different concentrations of thermosensitive polymers (poloxamer407 alone or in combination with poloxamer 188) and methyl cellulose (MC ) or hydroxypropyl methylcellulose (HPMC K4M )in different concentrations used as mucoadhesive polymer and the resultant formulations were subjected to several tests such as   gelation temperature GT, appearance and pH value. The fo

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Scopus (14)
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Publication Date
Fri Jan 01 2021
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
SYNTHESIS, SPECTROSCOPIC, CHARACTERIZATION AND BIOLOGICAL STUDIES FOR NEW COMPLEXES WITH N1, N5-BIS (3-HYDROXYPHENYL)- 2-OXOPENTANEDIAMIDE
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New complexes have been prepared from the new ligand [N1,N5-bis(3-hydroxyphenyl)-2- oxopentanediamide] derived from 2-Oxoglutaric acid and 3-aminophenol. Accordingly its binudear Mn(II),Co(II),Ni(II),Pd(II) and VO(II) complexes were prepared.. These compounds have been characterized by FT-IR, UV-Vis,Mass, 1H-NMR spectra, TGA curve, Chloride containing ,Molar conductance and atomic absorption. The characterization results gave binuclear complexes and pentadentate coordination and tetrahedral geometry for each Cobalt, Nickel, Manganese and Copper complexes otherwise Palladium complex gave a square planar geometry and Vanadium complex gave a square pyramidal geometry and the ligand is tetradentate. The biological activities for the new compoun

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Synthesis, Spectral Identification, Antibacterial Evaluationand Theoretical Study of Co, Fe, Rh and Pd Complexes for 2-benzoylthiobenzimidazol
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A new novel series of metalcomplexes are prepared from reactions between 2-benzoylthiobenzimidazole (L) with metal salts of Co (II) , Fe(III) and Rh (III) , while Pd(II) complex was obtained by mixing ligandsof 2-benzoylthiobenzimidazole (L) as primary ligand and bipyridine (L/ )as secondary ligand as well as palladium chloride as metal salt in an ethanoic medium. The geometry of these compounds were identified using C.H.N.microanalysis, Ultraviolet–visible, Fourier transforms infrared, magnetic susceptibility, molar conductivity and flame atomic absorption (A.A). From the dataobtained by these spectral analyses, the molecular structures for Rh and Fe complexes were proposed to be octahedral geometry. A square planar construction is propo

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Publication Date
Sun Sep 22 2019
Journal Name
Baghdad Science Journal
A Molecular and Biochemical Study for Cholesteryl Ester Transfer Protein (CETP) Taq1B in Iraqi Patients with Hyperlipidemia
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Cholesteryl ester transfer protein gene contains some single nucleotide polymorphisms, which have been associated with serum high-density lipoprotein concentration and other lipoproteins. This study is done for determining of cholesteryl ester transfer protein polymorphism and evaluate its effect on serum lipid profile concentrations in some hyperlipidemic patients compared with healthy subjects in Salah Al-din governorate-Iraq. Blood samples were taken from (90) patients suffering from hyperlipidemia, and (70) samples that were apparently healthy controls.  Serum lipid concentrations were measured by enzymatic assays. The polymorphism was genotyped using polymerase chain reaction restriction fragment length polymorphism analysis.&n

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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