P. aeruginosa is a famous bacterium that causes several diseases and has a high ability to be a multidrug resistant organism that is linked with the formation of biofilm. This study aimed to investigate tssC1 gene role in the resistance of different antibiotics in the presence of biofilm. We constructed biofilm for the isolates under the study and showed the effect of different antibiotics on biofilm formation and maturation. The presence of the gene was detected through achieving PCR reaction. Finally, tssC1 gene variation was determined through sequencing and aligning the sequencing products. The results showed that most of the isolates (80%) formed biofilm that played a role in the resistance of different antibiotics which could

In this work, PAni nanofibers (NFs) are successfully synthesized via hydrothermal method. The structural, surface morphological, optical, electrical and H2S gas sensing properties have been investigated for PAni thin films deposited by spin coating technique. The XRD pattern reveals crystalline nature of PAni NFs with crystallite size of 9.2 nm. The SEM image of Polyaniline clearly indicates that the polymer possesses nanofiber like structure. The optical properties show that the optical energy gap follows allowed direct electronic transition calculated using Tauc’s equation. Intense hotoluminescence (PL) peaks at 309, 340 and 605 nm are observed. The electrical properties such as D.C. conductivity and Hall effect have been studied wher

A two-dimensional computational study had been performed regarding aerodynamic forces and pressures affecting a cambered inverted airfoil, CLARK-Y smoothed with ground effects by solving the Reynolds-averaged Navier-Stokes equations, using the commercial software COMSOL Multiphysics 5.0 solver. Turbulence effects are modeled using the Menter shear-stress transport (SST) two-equation model. The negative lift (down-force), drag forces and pressures surface were predicted through the simulation of wings over inverted wings in different parameters namely; varying incidences i.e. angles of attack of the airfoils, varying the ride hide from the ground covering various force regions, two-dimensional cross-section of the inverted front wings to be

  Measurement of stability constant of some complexes formed by (6-(2-amino-2-(4hydroxy phenyl)-acetamido)-3,3-dimethyl-7-oxo-4-thia-1-aza-bicyclo[3,2,0] heptanes-2carboxylic acid (Amoxicillin) with (Cr+3, Co+2, Ni+2, Cu+2,Ag+1, and Cd+2) ions, have been performed(Amoxicillin) was found to behave as bidentate ligand with ahardness parameter(α)of (0.46)and asoftness parameter(β)of (1.03) while complexes being formed were of (1:1)ratio.
 

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class

In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden