In this investigation , borax (B) (additive I) and chlorinated paraffin (CP.) (additive II) ,were used as flame retardants for each of epoxy and unsaturated polyester resins in the weight ratios of 2,4,6, & 8% by preparing films of (130×130×3) mm dimensions. Also films of these resins with a mixture of [50%(B.)+50%(CP.)] (additive III) in the same weight ratios were prepared in order to study the synergistic effect of these additives on the flammability of the two resins . Three standard test methods were used to measure the flame retardation which are : 1-ASTM : D-2863 2-ASTM : D-635 3-ASTM : D-3014

Objective To investigate the accuracy of gingival crevicular fluid (GCF) E-cadherin and total antioxidant capacity (TAC) to discriminate periodontal health from disease. Subjects and Methods GCF samples were collected from participants with periodontal health (control), gingivitis, and periodontitis (n = 25 each group). The latter group was further subdivided according to stage (S) and grade. Periodontal parameters were recorded then levels of biomarkers were assayed using ELISA and antioxidant status by use of the Total Antioxidant Capacity Assay for E-cadherin and TAC, respectively. Results All periodontal parameters were significantly higher in periodontally diseased groups than controls. The GCF E-cadherin significantly increased

Actinomycetes are free, spore-forming, high (G+C) ratio (>55%) saprophytic microorganisms that are widely distributed in most soils, colonize plants, and are prevalent in water. This is frequently accompanied by the production of filament airborne mycelium. Actinomycetes are well-known microcolonies for creating antibiotics and other critical bioactive components that are beneficial to humans. Approximately 70% to 80% of commercially available medications and antiviral active compounds have been synthesized so far. Secondary metabolites produced by microbes have the potential to be used in a variety of sectors, including antimicrobial agents, enzyme technology, pigment manufacture, antitumor agents against cancer cells, and toxin pr

The problem of research was the lack of research that dealt with issue of the job design approach that is more suitable for knowledge work, therefore, the research aims to determine the impact of job enrichment,  and knowledge capitalon strategic success, starting from the hypothesis that there significant impact of job enrichment and knowledge capital on strategic success, to achieve this goal the researchers from the theoretical literature and  related studies conclude to the construction of the scheme shows the hypothetical relationship between the variables, which was adopted job enrichment as independent variable while knowledge capital plays two roles, the first as an independent variable and the second as an intermediate

Background: Odontogenic cysts are characterized by their sluggish growth and ability to enlarge, primarily affecting the oral and maxillofacial tissues. Timely diagnosis and treatment are crucial to prevent potentially serious consequences. The present study aimed to evaluate and compare the immunohistochemical expression of cytokeratin 19 in the epithelium of odontogenic keratocyst, dentigerous, and radicular cysts.

Methods: This study analyzed forty-five formalin-fixed, paraffin-embedded tissue blocks containing odontogenic cysts. The sample consisted of fifteen odontogenic keratocysts, fifteen dentigerous cysts, and

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi