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Enhancing Electrochemical Cells Performance with Modified Ionic Liquids and Deep Eutectic Solvents using Titanium Dioxide Nanoelectrodes- Graphite
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Ionic liquids (ILs) and deep eutectic solvents (DESs) have been found to be highly effective as electrolytes in TiO2 NTAs-graphite cells when combined with additives that enhance conductivity by reducing the viscosity of these liquids. The presence of CaCl2.6H2O: Acetamide DES with DI water as an additive resulted in a cell voltage of 1.31V and an internal resistance of 19 ohm. This can be attributed to the concentration and quality of the ionic species. The cells exhibited an interesting response to the AlCl3-chloroacetamide IL with dichloromethane DCM as an additive, with a cell voltage of 1.81V and an internal resistance of 5.0 ohm. Once again, this is influenced by the quality and concentration of the ionic species. Furthermore, the cells demonstrated thermal stability during the charging and discharging processes. Additionally, the surfaces of the TiO2 NTAs electrodes were examined, along with the impact of the IL and DES on these electrodes, using SEM and EDXA equipment.

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Engineering
Analytical and Numerical Tooth Contact Analysis (TCA) of Standard and Modified Involute Profile Spur Gear
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Among all the common mechanical transmission elements, gears still playing the most dominant role especially in the heavy duty works offering extraordinary performance under extreme conditions and that the cause behind the extensive researches concentrating on the enhancement of its durability to do its job as well as possible. Contact stress distribution within the teeth domain is considered as one of the most effective parameters characterizing gear life, performance, efficiency, and application so that it has been well sought for formal gear profiles and paid a lot of attention for moderate tooth shapes. The aim of this work is to investigate the effect of pressure angle, speed ratio, and correction factor on the maxi

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Publication Date
Mon Mar 13 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of Calcium Carbonate Coating on Osseointegration of Commercially Pure Titanium Implant by Torque Removal Test and Histomorphometric Analysis
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Abstract Background: One of the most important methods to replace lost teeth is dental implants. In order to increase the strength of connection of the implant with the jaw bone to provide early loading after placement, implant is coated by different coating materials that achieved that purpose. The aim of this study was to evaluate the influence of coating CP Ti implant with calcium carbonate on the strength of bone-implant interface after two and six weeks of implantation in rabbit femur bone by torque removal test, histological and histomorphometric analysis. Materials and methods: Coating the surface of commercially pure titanium screws with extra pure synthetic calcium carbonate via electrophoretic deposition method (EPD) was done. The

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Publication Date
Thu Jun 11 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The Effect of Pores in Dual Nano Hydroxyapatite Coating on Thermally Oxidized Commercial Pure Titanium: Mechanical and Histological Evaluation
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Background:In this study,TiO2 layer was thermally grown as a diffusion barrier on CP Ti substrate prior to electrophoretic deposition of HA coatings, to improve the coating’s compatibility also macro and micro pores in nano Hydroxyapatite dual coatings were created and their effect on the bond strength between the bone and implant was evaluated. Materials and methods: Electrophoretic Deposition technique (EPD) was used to obtain coatings for each one of four types of Hydroxyapatite(HA)on CP Ti screws (micro HA, nano HA, dual nano HA with micro pores, dual nano HA with macro pores) where carbon particles used as fugitive material to be removed by thermal treatment to create porosity.For examination of the changes occurred on the subs

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Molecular Liquids
Corrosion inhibition behavior of expired diclofenac Sodium drug for Al 6061 alloy in aqueous media: Electrochemical, morphological, and theoretical investigations
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The behavior corrosion inhibition of aluminum alloy (Al6061) in acidic (0.1 M HCl) and saline (3.5% NaCl) solutions was investigated in the absence and the presence of expired diclofenac sodium drug (DSD) as a corrosion inhibitor. The influence of temperature and was studied using electrochemical techniques. In addition, scanning electron microscopy (SEM) was used to study the surface morphology. The results showed that DSD acted as a powerful inhibitor in acidic solutions, while a moderate influence was observed with saline one. Maximum inhibition efficiency was 99.99 and 83.32% in acidic and saline solutions at 150 ppm of DSD, respectively. Corrosion current density that obtained using electrochemical technique was increased with temperat

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Mon Apr 07 2025
Journal Name
Al-nahrain Journal For Engineering Sciences
Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification
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Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

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Publication Date
Fri May 01 2026
Journal Name
Journal Of Engineering
Electronic Circuit Design and Modeling of Biodegradable Mxene-Based Wireless Biosensor for Deep Wound Monitoring
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One of the most significant challenges of medical care is the infection of postoperative wounds, and conventional visual examination often fails to detect it early. This research proposes the design of an innovative, passive wireless telemetry system for non-intrusive monitoring of the wound-healing process.  The system integrates a biocompatible resonance circuit (LC) with a high-sensitivity piezoresistive sensor based on MXene (Ti3C2Tx). It operates within the standard industrial and medical (ISM) band at 13.56 MHz.The detection mechanism in the system is based on the principle of "impedance modulation" (Impedance Modulation), which arises from changes in the sensor's resistance under physiological tissue pressure. The system was

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