Klebsiella pneumoniae are Gram-negative which cause many diseases such as urinary tract infections, respiratory tract infections and septicemia. Inulinase is an enzyme used in food manufacture and pharmaceuticals. Inulinase is used in decreasing lipid ratio and, cholesterol in blood and considered as a prebiotic factor inside intestine. Many microorganisms can produce inulinase, such as yeast, fungi and bacteria; among such bacteria: Bacillus spp., Arthrobacter spp., and Pseudomonas spp. but there are no studies about inulinase production by K. pneumoniae have been reported. So the current study aims at investing the ability of producing and purification inulinase by K. pneumoniae. Method: K. pneumoniae were isolated from many hospitals and screened for the production of inulinase. Isolation percentage was 32%. A combination between the enzyme and the ceftazidime were assayed for detecting the antibacterial activity agonist Gram positive and Gram negative bacteria were done. Results: It is found that K. pneumoniae K4 isolate is the best producer of this enzyme. Inulinase, purified with ammonium sulfate at 70% saturation with specific activity 7.01 U/mg protein. As well, it's found that inulinase had increased the activity of ceftazidime against bacteria when combination between this enzyme and the antibiotic had done. Conclusion: This study proves for the first time that K. pneumoniae can produce inulinase which can be used in tremendous applications and also proves the broad spectrum bioactivity of inulinase against microbial pathogens. Ceftazidime antimicrobial activity against bacteria, is increased when a combination between inulinase and ceftazidime had done.
Cystic fibrosis (CF) is an autosomal recessive multisystem disease that results from mutation(s) of the cystic fibrosis transmembrane conductance regulator (
Diabetes distress (DD), an emotional burden that does not meet the diagnostic criteria for major depressive disorder, has gained attention in the diabetes literature. It was to evaluate the impact of diabetes education among psychological distress in type 2 diabetes patients.
A cross-sectional study was conducted between November 1, 2024, and March 1, 2025, at the Endocrine and diabetes center in Baghdad City, Iraq, tar
Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an
... Show MoreIn recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
... Show MoreIn this article, a continuous terminal sliding mode control algorithm is proposed for servo motor systems. A novel full-order terminal sliding mode surface is proposed based on the bilimit homogeneous property, such that the sliding motion is finite-time stable independent of the system’s initial condition. A new continuous terminal sliding mode control algorithm is proposed to guarantee that the system states reach the sliding surface in finitetime. Not only the robustness is guaranteed by the proposed controller but also the continuity makes the control algorithm more suitable for the servo mechanical systems. Finally, a numerical example is presented to depict the advantages of the proposed control algorithm. An application in the rota
... Show MoreConjugate heat transfer has significant implications on heat transfer characteristics, particularly in thick wall applications and small diameter pipes. In this study, a three-dimensional numerical investigation was carried out using commercial CFD software “ANSYS FLUENT” to study the influence of conjugate heat transfer of laminar flow in mini channels at constant heat flux wall conditions. Two parameters were studied and analyzed: the wall thickness and thermal conductivity and their effect on heat transfer characteristics such as temperature profile and Nusselt number. Thermal conductivity of (0.25, 10, 202, and 387) W/m2C and wall thickness of (1, 5, and 50) mm were used for a channel of (1*2) mm cross
... Show MoreThe influence of Cr3+ doping on the ground state properties of SrTiO3 perovskite was evaluated using GGA-PBE approximation. Computational modeling results infered an agreement with the previously published literature. The modification of electronic structure and optical properties due to Cr3+ introducing into SrTiO3 were investigated. Structural parameters assumed that Cr3+ doping alters the electronic structures of SrTiO3 by shifting the conduction band through lower energies for the Sr and Ti sites. Besides, results showed that the band gap was reduced by approximately 50% when presenting one Cr3+ atom into the SrTiO3 system and particularly positioned at Sr sites. Interestingly, substituting Ti site by Cr3+ led to eliminating the band ga
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