Browsing by Author "Koyuncu, Onur"

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    Article
    The Effect of Low-Flow Versus Highflow Anesthesia on Postoperative Cognitive Functions in Geriatric Patients Undergoing Tur-P Surgery
    (Turkish Geriatrics Soc, 2024) Unal, Ekin Anil; Comez, Mehmet Selim; Demirkiran, Hilmi; Koyuncu, Onur; Hakimoglu, Sedat; Urfali, Senem
    Introduction: This paper investigates the effect of low -flow anesthesia applications on postoperative cognitive function in geriatric age group (>= 65 years old) patients who underwent elective transurethral resection of the prostate surgery. Materials and Method: A total of 98 patients aged 65 and over who underwent elective transurethral resection of the prostate surgery under general anesthesia between December 2021 and November 2022 in Hatay Mustafa Kemal University Research Hospital's Department of Anesthesiology and Reanimation were included in the study. The patients were subjected to a mini mental test the day before the operation and postoperatively at six hours, one day, three days, and seven days. Visual analogue scale scores were evaluated at 3, 6, 12, 24, 48, and 72 hours. The data obtained were compared between the patient groups who underwent low -flow (1 L/min, n: 49) and high flow (4 L/min, n: 49) anesthesia. P< 0.05 was considered statistically significant. Results: A comparison between the postoperative 6thhour, 1st day, 2nd day, 3rd day, and 7th day mini mental testing scores of the low -flow anesthesia and high flow anesthesia groups did not exhibit any notable variations (p: 0.668, 0.785, 0.745, 0.705, respectively). The visual analogue scale scores of the cases at 3, 6, 12, 24, 48, and 72 hours did not differ statistically according to the type of flow applied (p: 0.316, 0.925, 0.651, 0.548, 0.624, 0.466, respectively). Conclusion: It is thought that low -flow anesthesia can be applied safely, but it does not have a significant effect on cognitive functions compared to high flow anesthesia.
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    Article
    Potential of SEM and Deep Learning in Archaeobotanical Identification of Ancient Wheat Varieties
    (Routledge Journals, Taylor & Francis Ltd, 2025) Anagun, Yildiray; Isik, Sahin; Olgun, Murat; Ulker, Mehmet; Koyuncu, Onur; Dikmen, Gokhan; Biber, Hanifi
    This study investigated the morphological similarity between bread wheat landraces from the Van Lake Basin and ancient Urartian wheat seeds (9th century BCE) discovered at & Ccedil;avu & scedil;tepe Fortress, utilising a Convolutional Neural Network (CNN)-based framework. Scanning Electron Microscopy (SEM) datasets were created using 15 lines from 10 landraces and the ancient seeds; EfficientNetB0, ResNet18 and InceptionResNetV2 models were employed to extract discriminative surface texture features. The ancient wheat samples showed the highest surface-texture similarity to the Muradiye-1-1 line (Red Kirik wheat) across the tested models (39.8% to 44.1%). These results suggest a phenotypic convergence between ancient and modern landraces under similar agroecological conditions, demonstrating the utility of CNN models for archaeobotanical analysis.