The state of the art of material jetting—a critical review

Material jetting (MJ) technology is an additive manufacturing method that selectively cures liquid photopolymer to build functional parts. The use of MJ technology has increased in popularity and been adapted by different industries, ranging from biomedicine and dentistry to manufacturing and aviation, thanks to its advantages in printing parts with high dimensional accuracy and low surface roughness. To better understand the MJ technology, it is essential to address the capabilities, applications and the usage areas of MJ. Additionally, the comparison of MJ with alternative methods and its limitations need to be explained. Moreover, the parameters influencing the dimensional accuracy and mechanical properties of MJ printed parts should be stated. This paper aims to review these critical aspects of MJ manufacturing altogether to provide an overall insight into the state of the art of MJ

Parotidectomy Outcomes, Diagnosis and Complications on Pediatric Patients; Twelve Years of Experiences in A Tertiary Care Center

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MONITORING OF GLACIERS ON HORSESHOE ISLAND, ANTARCTICA BASED ON A DEEP LEARNING APPROACH FROM HIGH-RESOLUTION ORTHOPHOTOS (TAE-6 & TAE-7)

Global climate change is a phenomenon that seriously affects the balance of a wide variety of ecosystems and is the intense focus of climate scientists and environmental researchers. In this context, periodic monitoring of glacier areas in terms of a better understanding of atmosphere-ocean interactions; thus, predicting the effects of climate change and planning against future threats by evaluating environmental impacts is an important research area. Especially the polar regions, where the melting of glaciers and the rise of sea levels are visibly observed, are important for climate scientists in providing crucial observations to understand and predict global climate change. In this study, within the scope of the international bilateral cooperation project carried out in cooperation with Istanbul Technical University (ITU) and the Bulgarian Academy of Sciences (BAS) (Project No: 121N033), the spatial changes in snow/glacier areas obtained from UAV Photogrammetry products generated during the 6th and 7th Antarctic National Science Expeditions. Snow/glacier areas were segmented with the K-Net deep learning approach which has been previously tested for accuracy and provides glacier mapping with accuracy metrics over 99%, on the high spatial resolution orthophotos produced during the two periods. The snow/glacier areas difference between the two periods were calculated and compared and water bodies which are critical areas, were specifically examined. The result of this comparison shows that the glacier area decreased by approximately 11% in just 1 year. However, to better understand these changes in snow/glacier areas, the region needs to be observed closely for longer time periods. It is thought that future studies will contribute to efforts to manage global environmental impacts and cope with climate change by focusing on monitoring and better understanding changes in these critical regions