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 nutrient use efficiency, and reduced greenhouse gas (GHG) emissions. Nevertheless, amidst these benefits, the challenges and constraints associated with these technologies, such as production expenses and potential environmental impacts of specific components, are also discussed. A comparative assessment of these SFTs emphasizes the importance of a balanced approach, considering three crucial factors: efficiency, environmental safety, and cost-effectiveness. While no single SFT achieves optimal balance across these dimensions, integrating multiple fertilizer technologies may help mitigate individual drawbacks. Also, financial and cost-to-benefit analyses are essential to gauge their applicability across diverse cropping environments. Future perspectives shed light on emerging SFTs and innovative approaches to overcome prevailing challenges and cultivate a more impactful role in fostering sustainable agriculture
NAA Mustafa, University of Sulaimani, Ms. c Thesis, 2010 - Cited by 4
With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t
... Show MoreBackground: Diabetes mellitus has been suggested
to be the most common metabolic disorder
associated with magnesium deficiency, and because
available data suggest that adverse outcomes are
associated with hypomagnesemia, it is prudent that
routine surveillance for hypomagnesemia be done
and the condition be treated whenever possible.
Aim of the study:To explore the serum Mg
concentrations of diabetic patients and healthy
controls in our locality.
Mehtods: One hundred and forty four diabetic
patients (22 with type I and 122 with type II diabetes
mellitus) recruited from the outpatient diabetes clinic
at the Specialized Center For Endocrine DiseasesBaghdad (62 patients), National Diabetes Center-Al
The main purpose of this work is the construction of an optical parametric amplifier (OPA) to generate a 629 nm pulsed laser. KTP nonlinear crystals were used for both parametric oscillation and amplification. A singly resonant parametric oscillator (OPO) is constructed to generate a signal of 1.54 μm and idler of 3.4 μm when the OPO system is pumped by 1.064 μm Q – switched Nd: YAG laser. The signal was then mixed with the pumping beam in OPA system to form the wanted wavelength. The obtained optical conversion efficiency was 60%.
Catalytic reforming of naphtha occupies an important issue in refineries for obtaining high octane gasoline and aromatic compounds, which are the basic materials of petrochemical industries. In this study, a novel of design parameters for industrial continuous catalytic reforming reactors of naphtha is proposed to increase the aromatics and hydrogen productions. Improving a rigorous mathematical model for industrial catalytic reactors of naphtha is studied here based on industrial data applying a new kinetic and deactivation model. The optimal design variables are obtained utilizing the optimization process in order to build the model with high accuracy and such design parameters are then applied to get the best configuration of this pro
... Show MoreAn experimental study is made here to investigate the discharge coefficient for contracted rectangular Sharp crested weirs. Three Models are used, each with different weir width to flume width ratios (0.333, 0.5, and 0.666). The experimental work is conducted in a standard flume with high-precision head and flow measuring devices. Results are used to find a dimensionless equation for the discharge coefficient variation with geometrical, flow, and fluid properties. These are the ratio of the total head to the weir height, the ratio of the contracted weir width to the flume width, the ratio of the total head to the contracted width, and Reynolds and Weber numbers. Results show that the relationship between the discharge co
... Show MoreIn this study miconazole nitrate was formulated as topically applied emulgel; different formulas were prepared using sodium carboxymethylcellulose (SCMC) and carboxypolymethylene (carbomer 941) as gelling agents. The influence of type of gelling agent and concentration of both oil phase and emulsifying agent on drug release was studied and compared with commercially available miconazole nitrate cream (Mecozalen®). The results of in vitro release showed that SCMC emulgel bases gave better release than carbomer 941 bases and the release of drug increase from both bases as a function of increasing the concentration of emulisifying agent. The oil phase had retardation effect when
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in