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Smart fertilizer technologies: An environmental impact assessment for sustainable agriculture
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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

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Cranio-maxillofacial Surgery
Assessment of regional asymmetry of the face before and after surgical correction of unilateral cleft lip
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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
An efficient color quantization using color histogram
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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Electrofacies Characterization of an Iraqi Carbonate Reservoir
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

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Publication Date
Sun Mar 01 2015
Journal Name
Craniomaxillofacial Trauma & Reconstruction
Mandibular Fractures in Iraq: An Epidemiological Study
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The purpose of this study was to evaluate the epidemiological characteristics of the mandibular fractures relating to gender, age, the etiology of injury, and the rendered treatment modalities and complications. The data of the patients who sustained mandibular fractures were retrieved and were analyzed retrospectively, and based on these data a descriptive analysis was conducted. A total of 112 patients were included in this study; the most common cause was road traffic accidents (RTAs) followed by assaults and missile injuries. The most frequently involved age group was 11 to 20 years, treatment modalities included conservative, closed reduction and indirect fixation, and open reduction and internal fixation (ORIF) in 11.6, 79.5, and 8.9%

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
CVOTING: An Anonymous Ballot E-Voting System
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One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,

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Publication Date
Sun Sep 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Rhabdomyolysis; is it an overlooked DKA complication
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Publication Date
Wed Jun 14 2023
Journal Name
Al-academy
Irony in conceptual art (An analytical study )
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In the 20th century, the concept of "sarcasm" has relatively prevailed, and in this sense, it is a method in the art of conversation that wants to keep the question about the intended meaning, that is, "saying something and suggesting its opposite."
There are other concepts that indicate that sarcasm is saying something in a way that provokes the recipient of the statement an infinite number of different interpretations, with multiple readers of different interpretations. While the philosophy of irony stands by the standards of things, exaggeration or minimization, this manipulation takes place within the enjoyment. However, it's a method to present sharp criticism in an atmosphere of criticism that differs from generation to gener

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Publication Date
Thu Sep 16 2021
Journal Name
International Journal Of Clinical Practice
An overview of post‐COVID‐19 complications
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Tue Sep 14 2021
Journal Name
Nature Reviews Microbiology
Towards an integrative view of virus phenotypes
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