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The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review
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The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Every stage must be finished in order for the analysis to go smoothly. Additionally, accurate success measures and the creation of an acceptable ECG signal database are prerequisites for the analysis of electrocardiogram (ECG) signals. Identification and diagnosis of various cardiac illnesses depend heavily on the ECG segmentation and feature extraction procedure. Electrocardiogram (ECG) signals are frequently obtained for a variety of purposes, including the diagnosis of cardiovascular conditions, the identification of arrhythmias, the provision of physiological feedback, the detection of sleep apnea, routine patient monitoring, the prediction of sudden cardiac arrest, and the creation of systems for identifying vital signs, emotional states, and physical activities. The ECG has been widely used for the diagnosis and prognosis of a variety of heart diseases. Currently, a range of cardiac diseases can be accurately identified by computerized automated reports, which can then generate an automated report. This academic paper aims to provide an overview of the most important problems associated with using deep learning and machine learning to diagnose diseases based on electrocardiography, as well as a review of research on these techniques and methods and a discussion of the major data sets used by researchers.

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Publication Date
Thu Feb 01 2024
Journal Name
Doklady Chemistry
Synthesis, Characterization, and Biological Evaluation of New Cyclic Quinazoline Derivatives as Potential Antibacterial and Antifungal Agents
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Heterocyclic compounds are crucial for medicinal chemistry and the development of therapeutic agents like broad-spectrum antibiotics. This study devised a facile procedure to synthesize novel antimicrobial bicyclic heterocycles from 2-mercapto-3-phenylquinazolin-4(3H)-one. Advanced analytical techniques including 1 H and 13C NMR, elemental analysis, and FT-IR spectroscopy characterized the intricate chemical structures of the products. In vitro assays tested the heterocycles against aerobic and anaerobic bacterial strains using fluconazole and ciprofloxacin as antifungal and antibacterial controls. Results demonstrated the formidable broad-spectrum antibacterial and antifungal activities of the synthesized compounds, with growth inhibition

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Publication Date
Sun Jan 01 2023
Journal Name
Chemical Methodologies
Cytotoxicity and Anticancer Effect of Chitosan-Ag NPs-Doxorubicin-Folic Acid Conjugate on Lungs Cell Line
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This study looked at how the synthetic chitosan-AgNPs-Doxorubicin-folic acid combination affected the A549 cell line in terms of cytotoxicity and anticancer activity. By reducing silver nitrate (AgNO3) and biodegradable chitosan, silver nanoparticles were biosynthesized. The produced conjugate was examined by using FT-IR spectroscopy, atomic force microscopy (AFM), and field emission scanning electron microscopy (FE-SEM). The cytotoxicity assay for the viability of A549 cells revealed that the combination of chitosan, AgNPs, doxorubicin, and folic acid decrease cell viability in a dose-determined by method over 48 hours, which direct to a dependent reduce in the activity of A549 cells. The mechanism analysis of the impacted living cells lea

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Publication Date
Mon Dec 01 2025
Journal Name
Applied Thermal Engineering
Efficient thermal management of PVT systems via water-PCM hybridization: New design with optimized geometrical configuration
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Publication Date
Sun Mar 01 2020
Journal Name
Food Hydrocolloids
Properties and antimicrobial activity of polyvinyl alcohol-modified bacterial nanocellulose packaging films incorporated with silver nanoparticles
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Publication Date
Thu Feb 11 2016
Journal Name
Journal Of Materials Science: Materials In Electronics
Electrochemical deposition of CdSe-sensitized TiO2 nanotube arrays with enhanced photoelectrochemical performance for solar cell application
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Publication Date
Tue Nov 01 2022
Journal Name
Isa Transactions
Robust adaptive active disturbance rejection control of an electric furnace using additional continuous sliding mode component
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The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated

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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimal Operating Conditions for Adsorption of Heavy Metals from an Aqueous Solution by an Agriculture Waste
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   The aim of this work is to detect the best operating conditions that effect on the removal of Cu2+, Zn2+, and Ni2+ ions from aqueous solution using date pits in the batch adsorption experiments. The results have shown that the Al-zahdi Iraqi date pits demonstrated more efficient at certain values of operating conditions of adsorbent doses of 0.12 g/ml of aqueous solution, adsorption time 72 h, pH solution 5.5 ±0.2, shaking speed  300 rpm, and smallest adsorbent particle size needed for removal of metals.  At the same time the particle size of date pits has a little effect on the adsorption at low initial concentration of heavy metals. The adsorption of metals increases with increas

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Publication Date
Tue Sep 01 2020
Journal Name
Petroleum
Reversible and irreversible adsorption of bare and hybrid silica nanoparticles onto carbonate surface at reservoir condition
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Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the

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Publication Date
Sat Nov 30 2024
Journal Name
Iraqi Journal Of Science
Effects of Phenolic Plant Extracts on Biofilm Formation by Klebsiella pneumoniae Isolated from Urinary Tract Infections
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Ten isolates of Klebsiella pneumoniae, seven isolates of Pseudomonas aeruginosa and nine isolates of Staphylococcus aureus, were obtained from 100 urine samples collected from Baghdad hospitals. All isolates were identified biochemically and confirmed by using VITEK 2 and were then tested for their susceptibility towards 6 antibiotics and for phenolic extracts of Thymus vulgaris and Cinnamomum cassia. All bacteria were greatly affected by T. vulgaris, especially K. pneumoniae. Viable count was performed, it was noted that the number of bacterial cells reduced from 1×108 CFU to 1.2× 103, 2×105 and 1.8×106CFU of K. pneumoniae, P. aeruginosa and S. aureus respectively. While C. cassiahad a slight effect on them. K. pneumoniae isola

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Publication Date
Sun Jul 21 2024
Journal Name
Journal Of Clinical Medicine
Microbiological and Salivary Biomarkers Successfully Predict Site-Specific and Whole-Mouth Outcomes of Nonsurgical Periodontal Treatment
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Background/Objectives: Nonsurgical periodontal treatment (NSPT) is the gold-standard technique for treating periodontitis. However, an individual’s susceptibility or the inadequate removal of subgingival biofilms could lead to unfavorable responses to NSPT. This study aimed to assess the potential of salivary and microbiological biomarkers in predicting the site-specific and whole-mouth outcomes of NSPT. Methods: A total of 68 periodontitis patients exhibiting 1111 periodontal pockets 4 to 6 mm in depth completed the active phase of periodontal treatment. Clinical periodontal parameters, saliva, and subgingival biofilm samples were collected from each patient at baseline and three months after NSPT. A quantitative PCR assay was us

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