The global food supply heavily depends on utilizing fertilizers to meet production goals. The adverse impacts of traditional fertilization practices on the environment have necessitated the exploration of new alternatives in the form of smart fertilizer technologies (SFTs). This review seeks to categorize SFTs, which are slow and controlled-release Fertilizers (SCRFs), nano fertilizers, and biological fertilizers, and describes their operational principles. It examines the environmental implications of conventional fertilizers and outlines the attributes of SFTs that effectively address these concerns. The findings demonstrate a pronounced environmental advantage of SFTs, including enhanced crop yields, minimized nutrient loss, improved nut

Let R be associative; ring; with an identity and let D be unitary left R- module; . In this work we present semiannihilator; supplement submodule as a generalization of R-a- supplement submodule, Let U and V be submodules of an R-module D if D=U+V and whenever Y≤ V and D=U+Y, then annY≪R;. We also introduce the the concept of semiannihilator -supplemented ;modules and semiannihilator weak; supplemented modules, and we give some basic properties of this conseptes

The importance of knowledge is represented in the use of various sources of information, the corresponding to the same level of importance is the use of modern means and technologies in the delivery and investment of these sources to the beneficiaries, among these means and technologies are the multimedia that deal with most of the human senses, but the most important of which is sight and hearing, if these are invested the means in the field of education will give many positive results, such as the speed of receiving information, its clarity, and its freedom from impurities and influences, as well as its stability in memory as it is based on nderstanding, not memorization. On this basis, the experience of supporting the education process

Three isolated bacteria were examined to remove heavy metals from the industrial wastewater of the Diala State Company of Electrical Industries, Diyala-Iraq. The isolated bacteria were identified as Pseudomonas aeruginosa, Escherichia coli and Sulfate Reducing Bacteria (SRB). The three isolates were used as an adsorption factor for different concentrations of Lead and Copper (100, 150, and 200 ppm.), in order to examine the adsorption efficiency of these isolates. In addition, the effect of three factors on heavy metals adsorption were examined; temperature (25, 30, and 37 ?C), pH (3 and 4.5) and contact time (2 and 24 hrs). The results showed that the highest level of lead adsorption was obtained at 37 ?C by E. coli, P, aerugenosa and

This study investigates the results of electrocoagulation (EC) using aluminum (Al) electrodes as anode and stainless steel (grade 316) as a cathode for removing silica, calcium, and magnesium ions from simulated cooling tower blowdown waters. The simulated water contains (50 mg/l silica, 508 mg/l calcium, and 292 mg/l magnesium). The influence of different experimental parameters, such as current density (0.5, 1, and 2 mA/cm²), initial pH(5,7, and 10), the temperature of the simulated solution(25⁰C and 35 ⁰C), and electrolysis time was studied. The highest removal efficiency of 80.183%, 99.21%, and 98.06% for calcium, silica, and magnesium ions, respectively, were obtained at a current de

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

Let R be a commutative ring with identity 1 and M be a unitary left R-module. A submodule N of an R-module M is said to be pure relative to submodule T of M (Simply T-pure) if for each ideal A of R, N?AM=AN+T?(N?AM). In this paper, the properties of the following concepts were studied: Pure essential submodules relative to submodule T of M (Simply T-pure essential),Pure closed submodules relative to submodule T of M (Simply T-pure closed) and relative pure complement submodule relative to submodule T of M (Simply T-pure complement) and T-purely extending. We prove that; Let M be a T-purely extending module and let N be a T-pure submodule of M. If M has the T-PIP, then N is T-purely extending.