134 samples of plants and animals wastes were taken from three different regions outside Baghdad and three different regions in Baghdad. 24 cellulolytic isolates fungi AO, C1, TH1, AN1, R1, TV, PG, AF, B1, L1, AP, TH, AP1, AN3, AO2, A, A1, C, F, AO1, C2, F1, CL and AP2 independent were chosen out of 48 selected fungi. The best optimal conditions for growth were 30ºC and pH 7. The isolates were identified and screened according to the colony diameter, biomass and density of spores in addition of capability to produce the hydrolytic enzymes for cellulose.
To determine the abilities of salivary E‐cadherin to differentiate between periodontal health and periodontitis and to discriminate grades of periodontitis.
E‐cadherin is the main protein responsible for maintaining the integrity of epithelial‐barrier function. Disintegration of this protein is one of the events associated with the destructive forms of periodontal disease leading to increase concentration of E‐cadherin in the oral biofluids.
A total of 63 patients with periodontitis (case) and 35
Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
... Show MoreObjective: Certain advantages of donkeys are still not listed as for other equine species. Moreover, donkeys lack comprehensive scientific studies. The present study examines the histological architecture and histochemical characteristics of the esophagus in the Iraqi local breed donkey (Equus asinus). Materials and Methods: Eight esophagus samples were collected from a local breed donkey. Tissue specimens (~1 cm³) were collected from the cervical, thoracic, and abdominal regions of the esoph¬agus and processed via routine histological technique. The tissue sections were stained with hema¬toxylin and eosin, Massons Trichrome, and combined Alcian blue (pH 2.5) plus PAS (AB-PAS). Results: The esophagus of the local breed donkey h
... Show MoreThe utilization of carbon dioxide (CO₂) to enhance wellbore injectivity presents a cost-effective and sustainable strategy for mitigating greenhouse gas emissions while improving reservoir performance. This study introduces an environmentally friendly method employing a water-soluble chitosan salt (CS) that generates a carbonated-rich acid solution upon contact with dry CO₂ at 25 °C and 508 psi. CS solutions (100–2000 ppm) were prepared and evaluated for CO₂ uptake, acid generation, and rheological behavior. Results show that 1000 ppm achieves an optimal CO2 uptake (2612 mg/l), with moderate viscosity increase (from 1.52 to 3.37 cp), while higher concentrations exhibit a sharp rise due to polymer-like network formation. Core floodi
... Show MoreGiardia lamblia is one of most common protozoan cause diarrheas, and the most health problem in development countries worldwide. Our work aimed to assess activity and toxicity of metronidazole loaded silver nanoparticles in treatment of acute giardiasis in mice. After inoculated mice with Giardia cysts in a dose of 105 cyst for acute infection, treatments were given for eight days. Number Giardia cysts in stool were discovered. Toxicity nanoparticles was estimated by Measurement oxidative stress markers (GSH) and (MDA) in liver, kidney tissue homogenate. The results showed single therapy was better effect by silver nanoparticles, highest percentages of reduction in number of cysts Giardia lamblia of infected mice treated with silver nanopar
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
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