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Fatigue and Tensile Characteristics for Composite Materials Used in Prosthetic Socket
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In this research, the use of natural materials like wool and cannabis as intermediate reinforcement for prosthetic limbs due to their comfort, affordability, and local availability was discussed. As part of this study on below-the-knee (BK) prosthetic sockets, two sets of samples were made using a vacuum method. These sets were made of natural fiber-reinforced polymer composites with lamination 80:20: group (Y) had 4 perlon, 1 wool 4 perlon, and group (G) had 4 perlon, 1 cannabis 4 perlon. The two groups were compared with a socket made of polypropylene. Tensile testing was used to determine the mechanical characteristics of the socket materials. The Y group has a yield stress of 17 MPs, an ultimate strength of 18.75 MPa, and an elastic modulus of 4.021 GPa, while for the G group, these values are 12.75 MPa, 18.84 MPa, and 4.076 GPa, respectively. The fatigue test was used to evaluate the failure characteristics of the socket. An F-socket was utilized to test the interface compression between both the limb and the socket. For the Tekscan sensor, the calculated pressure in the medial region is 350 K Pa, while it is 330 KPa in the posterior region. Solid Works software was used to draw a prosthetic socket for the numerical study. The failure safety agent for the composite material for group Y was 1.26. The finite element method (ANSYS Workbench 14.5) was used to look at the fatigue characteristics to detect the maximum stress, safety factor, and total deformation.

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Publication Date
Sun Jun 01 2025
Journal Name
Chemical Engineering And Processing - Process Intensification
Wastewater treatment through a hybrid electrocoagulation and electro-Fenton process with a porous graphite air-diffusion cathode
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Publication Date
Fri Dec 20 2024
Journal Name
Iraqi Journal Of Pharmaceutical Sciences
Genetic Polymorphisms at TNF-Alpha Receptors Associated some Autoimmune Diseases and Response of Anti-TNF Biologics: Review
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Some genetic factors are not only involved in some autoimmune diseases but also interfere with their treatment, Such as Crohn's disease (CD), Rheumatoid Arthritis (RA), ankylosing spondylitis (AS), and psoriasis (PS). Tumor Necrosis Factor (TNF) is a most important pro-inflammatory cytokine, which has been recognized as a main factor that participates in the pathogenesis and development of autoimmune disorders. Therefore, TNF could be a prospective target for treating these disorders, and many anti-TNF were developed to treat these disorders. Although the high efficacy of many anti-TNF biologic medications, the Patients' clinical responses to the autoimmune treatment showed significant heterogeneity. Two types of TNF receptor (TNFR); 1 an

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Publication Date
Mon Apr 03 2023
Journal Name
Polymer Composites
Effect of silver nanoparticles on structural, thermal, electrical, and mechanical properties of poly(vinyl alcohol) polymer nanocomposites
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Publication Date
Wed May 01 2019
Journal Name
Environmental Technology & Innovation
Biomineralization based remediation of cadmium and nickel contaminated wastewater by ureolytic bacteria isolated from barn horses soil
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Publication Date
Thu Nov 18 2021
Journal Name
Healthcare
Effect of Practice Environment on Nurse Reported Quality and Patient Safety: The Mediation Role of Person-Centeredness
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This study aims to explore the potential mediation role of person-centeredness between the effects of the work environment and nurse reported quality and patient safety. A quantitative cross-sectional survey collected data from 1055 nurses, working in medical and surgical units, in twelve Malaysian private hospitals. The data collection used structured questionnaires. The Hayes macro explored the mediation effect of person-centeredness between the associations of work environment dimensions and care outcomes, controlling nurses’ demographics and practice characteristics. A total of 652 nurses responded completely to the survey (61.8% response rate). About 47.7% of nurses worked 7-h shifts, and 37.0% were assigned more than 15 pati

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Parametric Analysis of Surface Roughness and Metal Removal Rate during Electrical Discharge Machining of O1 Tool Steel
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This work studies the impact of input machining parameters of Electrical Discharge Machining (EDM) on the machining process performance. Tool steel O1 was selected as the workpiece material, copper as the electrode material, and kerosene as the dielectric medium. Experimental runs have been carried out with a Design of Experiment (DOE) technique. Twenty tests are accomplished with the current range of (18 to 24 Ampere), a pulse duration range of (150 to 200 µs), and a pulse-off time range of (25 to 75 µs). Based upon the experimental study's output results, the EDM parameter's effect (voltage of power supply, discharge current, pulse duration, and pulse pause interval) on the responses of the process represented by sur

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Publication Date
Thu Aug 08 2024
Journal Name
Computation
Evaluation of the Dynamics of Psychological Panic Factor, Glucose Risk and Estrogen Effects on Breast Cancer Model
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Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Influence of Cold Plasma on Sesame Paste and the Nano Sesame Paste Based on Co-occurrence Matrix
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The aim of the research is to investigate the effect of cold plasma on the bacteria grown on texture of sesame paste in its normal particle and nano particle size. Starting by using the image segmentation process depending on the threshold method, it is used to get rid of the reflection of the glass slides on which the sesame samples are placed.  The classification process implemented to separate the sesame paste texture from normal and abnormal texture. The abnormal texture appears when the bacteria has been grown on the sesame paste after being left for two days in the air, unsupervised k-mean classification process used to classify the infected region, the normal region and the treated region. The bacteria treated with cold plasma, t

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Fri Apr 30 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Implementation of artificial neural network to achieve speed control and power saving of a belt conveyor system
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According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

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