Pseudomonas aeruginosa is a common and major opportunistic human pathogen, its causes many and dangersinfectious diseases due to death in some timesex: cystic fibrosis , wounds inflammation , burns inflammation , urinary tract infection , other many infections otitis external , Endocarditis , nosocomial infection and also causes other blood infections (Bacteremia). thereforebecomes founding fast and exact identification of P. aeruginosafrom samples culture very important.However, identification of this species may be problematic due to the marked phenotypic variabilitydemonstrated by samples isolates and the presence of other closely related species. To facilitate species identification, we used 16S ribosomal DNA(rRNA) sequence data

The movement and broadening of foreign and European words into Persian is a topic within historical linguistics. Such changes are semantic, phonological

Since many of these European loanwords into Persian took a remarkable space within Persian dictionaries, and became an indispensible part of the language, a study of the original languages of these loanwords may identify the enormous effect of those languages upon Persian, being a receptor language, and may refer to the liveliness.

Among the important factors which helped the movement of various loanwords into Persian are:

• Geographical: this is seen via contact between Persian people and those neighboring people, specifically those speaking Ara

 This paper argues the accuracy of behavior based detection systems, in which the Application Programming Interfaces (API) calls are analyzed and monitored. The work identifies the problems that affecting the accuracy of such detection models. The work was extracted (4744) API call through analyzing. The new approach provides an accurate discriminator and can reveal malicious API in PE malware up to 83.2%. Results of this work evaluated with Discriminant Analysis

In this study, a novel application of lab-scale dual chambered air-cathode microbial fuel cell (MFC) has been developed for simultaneous bio-treatment of real pharmaceutical wastewater and renewable electricity generation. The microbial fuel cell (MFC) was provided with zeolite-packed anodic compartment and a cation exchange membrane (CEM) to separate the anode and cathode. The performance of the proposed MFC was evaluated in terms of COD removal and power generation based on the activity of the bacterial consortium in the biofilm mobilized on zeolite bearer. The MFC was fueled with real pharmaceutical wastewater having an initial COD concentration equal to 800 mg/L and inoculated with anaerobic aged sludge. Results demo

Background: diabetes is a metabolic disease characterized by hyperglycemia that results in deficiency or absence of insulin production. The dental caries and gingivitis/periodontitis are widespread chronic diseases in diabetes. The aim of the present study was determined the salivary matrix metalloproteinase (MMP-8), Secretory Leukocyte Peptidase Inhibitor (SLPI) and oral health status among uncontrolled diabetic group in comparison with healthy control group. Materials and Methods: The total sample composed of 90 adults aged (18-35) years. Divided into 60 uncontrolled diabetic patients (HbA1c >7%) and 30 healthy control group. Unstimulated saliva was collected from each subject with type-I DM, BMI, duration of diabetes, HbA1c%, DMFT, gingi

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