Background: The emergence and spread of multidrug-resistant Gram-negative bacilliin burn wound infections related to biofilm formation, which lend to challenge in treatment with conventional antibiotics andprompting to search for novel antimicrobial agents to control the infections.Silver nanoparticles (AgNPs) have wide spectrum biological properties with different mechanisms of action and less toxicity towards human cells.

Objective:The goal of this study was to evaluated the anti-bacterial and anti-biofilm activities of AgNPs alone and in combination with aminoglycoside (Amikacin) and β-lactam (Ampicillin) antibiotics against multidrug resistant Gram-negative bacilli (Pseudomonas aeruginos

Introduction:

        Many business owners suffer major financial problems during periods of financial stagnation, the decline of markets and businesses, or under the impact of financial shocks for certain reasons that result in large debts and the consequent financial and legal obligations. This is the beginning of a long and endless path of suffering and the search for a safe exit. It is even worse for financial institutions to facilitate financial solutions that rely on lending as a solution to their financial problem. Debt and its consequences increase, and the problem deepens and becomes complicated until things become entangled and the escape or declaration of bank

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

Two groups of chronic hepatitis B and C virus patients were divided into Pre-treated patients (25 CHB patients with positive HBs Ag for more than 6 months and 40 CHC patients), and post-treated patients [12 CHB patients (4, 6, and 2 were treated with lamivudine, IFN-? and combination of LMV + IFN-? respectively), and 27 patients for CHC (3, 13 and 11 patients were treated with Ribavirin, IFN-? and combination therapy (RBV+ IFN-?) respectively].These patients were followed up for 6 months. By using ELISA technique, levels of IL-6, IL-10, IFN-? and TNF-? were measured in vivo and in vitro (supernatant of PBMCs stimulated with PHA) and compared with healthy control. The mean level of IL-6, IL-10 and TNF-? in CHB patients showed significant dif