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bsj-5579
Future Scenario of Global Climate Map change according to the Köppen -Geiger Climate Classification
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Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, and 0.09%, respectively. While the areas of Warm Temperature and Dessert will increase by 4.5% and 0.75%, respectively. The results of this study provide useful information on future climate Köppen-Geiger maps and areas that will most likely be affected by climate change in the following decades

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Publication Date
Wed Jan 08 2020
Journal Name
International Journal Of Advanced Science And Technology
The local stability of an eco-epidemiological model involving a harvesting on predator population
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In this paper a prey - predator model with harvesting on predator species with infectious disease in prey population only has been proposed and analyzed. Further, in this model, Holling type-IV functional response for the predation of susceptible prey and Lotka-Volterra functional response for the predation of infected prey as well as linear incidence rate for describing the transition of disease are used. Our aim is to study the effect of harvesting and disease on the dynamics of this model.

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Mon Aug 01 2016
Journal Name
2016 38th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Changes in the EEG amplitude as a biomarker for early detection of Alzheimer's disease
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The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Revolutionizing Systematic Reviews and Meta-analyses: The Role of Artificial Intelligence in Evidence Synthesis
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Publication Date
Tue Oct 01 2024
Journal Name
Separation And Purification Technology
A comprehensive review on the use of Ti3C2Tx MXene in membrane-based water treatment
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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Detecting the antibacterial activity of green synthesized silver (Ag) nanoparticles functionalized with ampicillin (Amp)
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In the current study, synthesis and characterization of silver nanoparticles (AgNPs) before and after functionalization with ampicillin antibiotic and their application as anti-pathogenic agents towards bacteria were investigated. AgNPs were synthesized by a green method from AgNO3 solution with glucose subjected to microwave radiation. Characterization of the nanoparticles was conducted using UV-Vis spectroscopy, scanning electron microscopy (SEM), zeta potential determination and Fourier transform infrared (FTIR) spectroscopy. From SEM analysis, the typical silver nanoparticle particle size was found to be 30 nm and Zeta potential measurements gave information about particle stability. Analysis of FTIR patterns and UV-VIS spectroscopy con

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Adsorption of the Color Pollutant onto NiO Nanoparticles Prepared by a New Green Method
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Green synthesis methods have emerged as favorable techniques for the synthesis of nano-oxides due to their simplicity, cost-effectiveness, eco-friendliness, and non-toxicity. In this study, Nickel oxide nanoparticles (NiO-NPs) were synthesized using the aqueous extract of Laurus nobilis leaves as a natural capping agent. The synthesized NiO-NPs were employed as an adsorbent for the removal of Biebrich Scarlet (BS) dye from aqueous solution using adsorption technique. Comprehensive characterization of NiO-NPs was performed using various techniques such as atomic force microscopy (AFM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), Brunauer-Emmett and Teller (BET) analysis, and scanning electron microscopy (SEM). Additionally, o

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Clinical And Experimental Dentistry
The effect of osseodensification on implant stability and bone density: A prospective observational study
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Background: The aims of this study were to evaluate the effect of implant site preparation in low-density bone using osseodensification method in terms of implant stability changes during the osseous healing period and peri-implant bone density using CBCT. Material and methods: This prospective observational clinical study included 24 patients who received 46 dental implants that were installed in low-density bone using the osseodensification method. CBCT was used to measure the bone density pre- and postoperatively and implant stability was measured using Periotest® immediately after implant insertion and then after 6 weeks and 12 weeks postoperatively. The data were analyzed using paired t-test and the probability value <0.05 was conside

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Publication Date
Mon Jul 01 2019
Journal Name
Journal Of Educational And Psychological Researches
The Level of Academic Achievement and its Relationship with Some Characteristics of Female Students at College of Education for Girls in Baghdad University: The Level of Academic Achievement and its Relationship with Some Characteristics of Female Students at College of Education for Girls in Baghdad University
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Abstract

Personality is one of the most important elements that should be developed in university student. Thus, we have to develop the positive traits and neutralize the negative traits of students as well as we have to pay attention to the level of student achievement at the same time, the researcher designed a scale to measure the traits of study sample. The research come out with a number of recommendations and proposals, the most important of which Enhancing the positive characteristics of university students in order to reach them to the level of mature personality with mental health. Enhancing the positive role of the high level of achievement by motivating the stude

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
The Effects of Long-Term Operation and High Temperature on Material Properties of Austenitic Stainless Steel Type 321H
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Changes in mechanical properties of material as a result of service in different conditions can be provided by mechanical testing to assist the estimation of current internal situation of these materials, or the degree of deterioration may exist in furnaces serviced at high temperature and exceed their design life. Because of the rarity works on austenitic stainless steel material type AISI 321H, in this work, ultimate tensile strength, yield strength, elongation, hardness, and absorbed energy by impact are evaluated based on experimental data obtained from mechanical testing. Samples of tubes are extracted from furnace belong to hydrotreaterunit, also samples from un-used tube material are used to make comparisons between these properti

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