A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

Background: Cardiovascular disease (CVD) is the number one cause of death worldwide. Objective: To determine of coronary care unit nurses' knowledge regarding patient rehabilitation after myocardial infarction. Methodology: A cross- sectional study was designed in the Cardiac Care Unit of Al-Diwaniyah Teaching Hospital and the Specialized Center for Cardiac Surgery and Catheterization for the period from (November 7, 2022) to (May 12, 2023). A non-probability (purposive) sample consisting of (75 nurses) working in the above-mentioned study site. To determination of coronary care unit Nurses' knowledge regarding patient rehabilitation after myocardial infarction, the researcher used a tool that consists of two parts: The first part:

Abstract A total of 207 specimens were collected from different sources including patients, health care staff and hospital environment in Ibb city, Yemen. The study used the bacteriocin produced from active producer strains in typing of Staphylococcus aureus. Depending on the morphological, cultural and biochemical characteristics, 54 (26.09%) isolates of Staphylococcus aureus were identified. An antibiotic sensitivity test was done for the bacterial isolates, and the results showed that there were multiple resistant antibiotics. The Staphylococcin production of these isolates has been detected by using wells assay. Fifty one isolates were Staphylococcin producer. Four isolates (staph19, staph25, staph28 and staph43) were chosen as go

No. Due to their apparently extreme optical to X-ray properties, Narrow Line Seyfert 1s (NLSy1s) have been considered a special class of active galactic nuclei (AGN). Here, we summarize observational results from different groups to conclude that none of the characteristics that are typically used to define the NLSy1s as a distinct group – from the, nowadays called, Broad Line Seyfert 1s (BLSy1s) – is unique, nor ubiquitous of these particular sources, but shared by the whole Type 1 AGN. Historically, the NLSy1s have been distinguished from the BLSy1s by the narrow width of the broad Hb emission line. The upper limit on the full width at half maximum of this line is 2000kms−1 for NLSy1s, while in BLSy1s it can be of several thousands

Polyacrylonitrile nanofiber (PANFS), a well-known polymers, has been extensively employed in the manufacturing of carbon nanofibers (CNFS), which have recently gained substantial attention due to their excellent features, such as spinnability, environmental friendliness, and commercial feasibility. Because of their high carbon yield and versatility in tailoring the final CNFS structure, In addition to the simple formation of ladder structures through nitrile polymerization to yield stable products, CNFS and PAN have been the focus of extensive research as potential production precursors. For instance, the development of biomedical and high-performance composites has now become achievable. PAN homopolymer or PAN-based precursor copolymer can

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Synthesis three organic inhibitors for carbon steel corrosion: 2-(propylthio)-1H-benzo[d]imidazole (PTBI), 2-(allylthio)- 1H-benzo[d]imidazole (ATBI) and 2-(prop-2-ynylthio)-1H-benzo[d]imidazole (YTBI) were prepared from reaction of 2-mercapto benzimidazole with different alkyl halide. The melting point and TLC were used to confirm the purity of the inhibitors as well as using the [FTIR, 1H-NMR and 13C-NMR] for the identify structures. The synthesized inhibitors were examined by potentiostatic polarization measurement as corrosion inhibitors of carbon steel in acidic media [1M H2SO4 ].The polarization measurement results showed that the mixed type inhibitors. In addition, the efficiency of inhibitors (YTBI) were studied at different con

Background BK polyomavirus is one of the common post-transplant viral infections, affecting ∼15% of renal transplantation recipients (RTR), leading to graft loss in more than half of cases. Objectives Study the rate of detection of BK virus (BKV) in RTRs in Pap-stained urine cytology specimens. Methods A single center study, urine samples were collected from 99 RTR patients, with 15 Living Donors (LD) and 15 patients with chronic kidney disease (CKD) were taken as controls. And urine cytology smears were Pap stained for detection of decoy cells (DCs). Results Out of the 99 RTRs, 27 (27.3%) patients were decoy positive, 8 out of these 27 patients had uncommon DCs, and 5 out of these 27 cytology positive patients (18.5%) had biopsy proven B

                 In this paper, we proved coincidence points theorems for two pairs mappings which are defined on nonempty subset   in metric spaces by using condition (1.1). As application, we established a unique common fixed points theorems for these mappings by using the concept weakly compatible (R-weakly commuting) between these mappings.

The aim of this research is to assess the validity of Detailed Micro-Modeling (DMM) as a numerical model for masonry analysis. To achieve this aim, a set of load-displacement curves obtained based on both numerical simulation and experimental results of clay masonry prisms loaded by a vertical load. The finite element method was implemented in DMM for analysis of the experimental clay masonry prism. The finite element software ABAQUS with implicit solver was used to model and analyze the clay masonry prism subjected to a vertical load. The load-displacement relationship of numerical model was found in good agreement with those drawn from experimental results. Evidence shows that load-displacement curvefound from the finite element m