Aksaray Üniversitesi Kurumsal Akademik Arşivi
DSpace@Aksaray, Aksaray Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Assessment of p-wave dispersion and atrial electromechanical delay in patients with non-obstructive coronary artery myocardial ınfarction
(Springer International Publishing, 2025) Keleşoğlu, Şaban; Yılmaz, Yücel; Elçik, Deniz; İnci, Sinan; Gül, Murat; Kalay, Nihat
We investigated p-wave dispersion (Pd) and atrial electromechanical delay (EMD) in patients diagnosed with non-obstructive coronary artery disease and myocardial infarction (MINOCA). Background: The clinical importance and recognition of MINOCA are increasing. However, there is a gap in knowledge regarding the risk of atrial fibrillation in patients with MINOCA. Methods: Forty-three patients with MINOCA (average age 48.69 ± 5.83 years) and thirty-four patients with non-obstructed coronary artery disease (INOCA) (average age 49.82 ± 10.22 years) were enrolled in the study. Echocardiographic studies were conducted in the MINOCA and INOCA groups in the left lateral decubitus position using a medical ultrasound device. Atrial electromechanical coupling (PA) and intra-atrial and interatrial EMD were measured using tissue Doppler echocardiography. Pd was measured using 12-lead electrocardiography. Results: Clinical and demographic characteristics were similar between groups. The maximum P-wave (Pmax) time and Pd values of patients diagnosed with MINOCA were significantly longer than those of patients diagnosed with INOCA (Pmax times: 109.72 ± 7.09 ms and 95.17 ± 7.50 ms, respectively, p < 0.01; Pd: 47.30 ± 8.99 ms and 34.14 ± 11.31 ms, respectively, p < 0.01). Tissue Doppler Imaging (TDI) revealed significantly longer atrial EMD parameters (PA lateral and PA septum) in patients diagnosed with MINOCA than in those diagnosed with INOCA (69.60 ± 8.79 ms and 57.08 ± 11.54 ms, respectively, p < 0.01; 54.83 ± 6.45 ms and 45.35 ± 8.50 ms, respectively, p < 0.01). Conclusion: This study showed that the duration of atrial EMD and Pd was prolonged in patients with MINOCA, suggesting a potential susceptibility to atrial conduction abnormalities.
Pedogenic evidence sheds light on the post-Roman pedo-sedimentological and human history of Tarsus, the Roman capital of CE 60, Cilicia, Mersin, Türkiye
(Elsevier B.V., 2025) Kapur, Selim; Akça, Erhan; Kadir, Selahattin; Previtali, Franco; Billor, Zeki; Zucca, Claudio; Casati, Enrico; Eren, Muhsin; Karagöz, Alptekin
The ancient city of Tarsus is underlying a sediment of 400 cm where the contemporary Tarsus grew. The diffusely stratified layers of the deposited sediment from the Kydnos (Tarsus) river overlying the Roman Road excavation site located in the heart of the modern city. The sediment is laden with technogenic materials. The profile of the stratigraphic layers represents a Pedocomplex (PDC) and its horizons are the Pedomembers (PDMs). All the PDMs were described and sampled for physical, chemical, mineralogical, micromorphological, and thermoluminescense analyses seeking pedogenic evidences. The origin of PDC materials is a fluvial and/or lagoon environment (archaeologically predicted date, about 60 CE, and they are calcareous, high in available P and some are high in total phosphorus contents). They have been partially modified by human activity in a settlement area, thus bringing some historical evidence suggesting that the site was part of the growing city after its abandonment. Thin sections show a vigorous biological degradation of the organic residues in the PDMs along with occasional evidence of soil-forming processes. The preliminary conclusions were extracted from the results obtained through the newly formed hydroxyapatite (Hap) determined by micromorphology, therefore proposing the new suffix π for the WRB soil naming system. Primary, high temperature and clay minerals together with TL analyses of the layers, were conducted to reveal the provenance and weathering phases of the horizons. The seeds recovered from an inhabited layer helped to interpret the food and medicinal habits of the local society and the contemporary presence of the lagoon.
Scheduling in the industry 5.0 environment: a bibliometric analysis
(Springer International Publishing AG, 2025) Başar, Ramazan; Engin, Orhan
The results of the bibliographic analysis evaluate the development of a field by examining publications, citations, and other metrics in the scientific literature. By bringing together the results of the analysis, trends in the literature, important figures, and the general development of the field can be understood. In this research, all scheduling studies in the Industry 5.0 environment that contained the words “Industry 5.0” and “scheduling” in the study title, abstract, and keywords were scanned using the Web of Science database. This database has a large corpus of data. As a result of the screening, a total of 62 studies were subjected to bibliometric analysis. The bibliometric package in the RStudio program was used for data analysis. As a result of the bibliometric analysis, various analyzes were performed according to year, author, keyword, source of publication, number of citations, institutions, and countries of publication, and the current situation related to academic writing was examined. According to the results obtained, industry 5.0-based scheduling studies are a very new topic that started to be studied in 2019 and has an annual growth rate of 25.99%.
Solar energy performance prediction with regression algorithm in machine learning based on weather condition: a case study
(Springer Science + Business Media, 2025) Coşgun, Atıl Emre
The escalating global demand for electrical energy, propelled by population growth, modern lifestyles, and technological advancements, underscores the necessity for transitioning toward renewable energy sources to mitigate the adverse impacts of fossil fuel dependency, notably global warming. Among renewables, solar photovoltaic (PV) energy systems have emerged as a prominent choice due to their eco-friendliness, sustainability, and minimal maintenance costs. However, the inherent unpredictability of renewable energy sources poses a significant challenge, particularly evident in the fluctuations of solar PV power generation caused by varying solar radiation and meteorological factors. This variability necessitates precise forecasting of solar PV power generation to optimize grid integration, ensure stability, and maximize benefits. Machine learning techniques offer a flexible and data-driven approach, capable of capturing complex nonlinear relationships between variables for enhanced forecasting accuracy. This paper is focused on regression algorithm forecasting approaches in machine learning for predicting solar PV power output under diverse weather conditions. For this, the regression learner tool from MATLAB’s machine learning has been used. By addressing key research questions, it aims to identify optimal forecasting approaches, assess their impact on solar energy production, and provide insights for policy formulation and regulation establishment, applicable to regions with limited research or data availability.
Using artificial ıntelligence in teaching health and physical education
(Taylor and Francis Ltd., 2025) Konukman, Ferman; Sortwell, Andrew; Filiz, Bijen; Tüfekçioğlu, Ertan; Yılmaz, Emine Büşra; Ünlü, Hüseyin
This article provides insight into the origin of AI, explores current research into the application of AI in HPE, and presents interdisciplinary research to provide practical and effective strategies for teachers.
