Welcome to IKU Academic Digital Archive System
OpenAccess@IKU is Istanbul Kultur University's Academic Digital Archive System, established in June 2014 to digitally store and provide open access to academic and artistic outputs in line with international standards and intellectual property rights. The system includes various outputs such as articles, presentations, theses, books, book chapters, reports, encyclopedias, and works of art produced by the university's faculty members and students.
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Recent Submissions
Two Dimensional Proteomic Analyses Revealed Salinity and Drought Tolerance Related Protein Alterations in Two Gamma-Induced Soybean Mutants
(Julius Kuhn-Institut Federal Research Center for Cultivated Plants, 2025) AYAN, ALP; MERİÇ, SİNAN; GÜMÜŞ, TAMER; ÇELİK, ÖZGE; ATAK, ÇİMEN
Soybean [Glycine max (L.) Merr], is an important industrial oil seed plant. Along with the nutritional value for humans and animals, it has raw materials for various industrial products. In the present study, we investigated the two-dimensional protein expression profiles in salinity and drought tolerant mutant plants derived from S04-05 soybean variety by Cs-137 gamma radiation source induced mutations. Altogether 54 different protein spot alterations were identified as salinity and drought responsive by two-dimensional electrophoresis and MALDI-TOF-MS. A protein-protein interaction network was constructed considering significantly altered proteins by STRING analysis software. Identified proteins, which presented differential expressions under both stress conditions, were clustered under 13 distinct groups based on their cellular functions. Two of these biological processes, photosynthesis and carbohydrate metabolism, were found significantly altered by KEGG analysis. Our results contribute proteomic data to salinity and drought tolerance of our soybean mutants, which originated from S04-05, a variety mildly susceptible to salinity and drought. These results may provide a basis for future investigations into the genetic and physiological aspects of both stress tolerances.
Market Basket Analysis Using Apriori and Eclat Algorithm in an E-Commerce Company
(Springer Science and Business Media Deutschland GmbH, 2025) Çatkın, Mehmet; Yüksel, Şengül; Konyalıoğlu, Aziz Kemal; APAYDIN, TUĞÇE; Özcan, Tuncay
E-commerce companies are facing significant challenges due to escalating competition, the homogenization of products and services, rapid shifts in customer demands, and the burgeoning volume of customer transactions. Consequently, these companies grapple with complex problems such as customer segmentation, customer churn analysis, market basket analysis, and the design of product recommendation systems. Leveraging data mining and machine learning algorithms offers substantial opportunities to effectively address these issues. For e-commerce enterprises, analysing customers’ purchasing behaviours and crafting personalized product recommendations not only enhances customer loyalty but also encourages impulse purchases. This approach also contributes to a more user-friendly platform, thereby increasing customer satisfaction. The present study aims to conduct a market basket analysis utilizing real-world data from an e-commerce company. Association rule mining algorithms, specifically Apriori and Eclat, are employed for this analysis. Through these methods, correlations and patterns between product categories are uncovered. Moreover, each algorithm is analyzed by comparing its execution duration and the quality of its results. These specified techniques, including Apriori, an intelligent join-based algorithm, and Eclat, a sophisticated tree-based algorithm, demonstrate remarkable intelligence by efficiently identifying and analyzing patterns within complex datasets. Their innovative methodologies enable them to dynamically adapt to data structures and extract frequent itemset with high performance, as evidenced by their outstanding results in current literature.
On Digamma Series Convertible Into Hypergeometric Series
(American Mathematical Society, 2025) ÇETİNKAYA, ASENA; Karp, Dmitrii
Series containing the digamma function arise when calculating parametric derivatives of hypergeometric functions, and play a role in evaluation of Feynman diagrams. As these series are typically non-hypergeometric, a few instances when they are summable in terms of hypergeometric functions are of importance. In this paper, by employing appropriate limiting processes, we convert multi-term identities for the generalized hypergeometric functions evaluated at positive/negative unity into identities connecting them to digamma series. The resulting formulas can be viewed as hypergeometric expressions for the sum of the partial derivatives of the generalized hypergeometric function with respect to all its parameters, and seem to have no direct analogues in the literature.
Endocrine Disruptors Attitude Scale: A Scale Development Study
(AVES, 2025) MİRAL, MUKADDES TURAN; Mamuk, Rojjin; Di̇şsi̇z, Melike; İşgüven, Şükriye Pınar
Objective: Endocrine disruptors are substances and mixtures that cause health problems in individuals and generations by affecting the endocrine system. There is no measurement tool for the assessment of people’s attitudes toward endocrine disruptors. The development of a valid and reliable measurement tool for the measurement of the attitudes of adult individuals toward endocrine disruptors is the aim of this study. Methods: This study with a methodological design was conducted with 366 participants who were at least 18 years old and literate in Turkish between December 01, 2021, and March 01, 2022, in İstanbul and Famagusta. To collect data, the “Participant Introduction Form” and “Endocrine Disruptors Attitude Scale” were used. Data were evaluated with descriptive statistics, exploratory and confirmatory factor analysis, dependent samples t-test, Cronbach’s α internal consistency coefficient, and Pearson correlation analysis. Results: When the item–total score correlations of 35 items in the draft scale were examined, 14 items with less than 0.30 and negative values were excluded from the scale. The correlation coefficient of all the remaining items was positive and significant (P < .001). The difference between test and retest mean scores was not statistically significant (P > .05). Cronbach’s α reliability coefficient was determined as α = 0.81 for the Consumer behavior sub-dimension, α = 0.80 for Nutrition and hygiene, and α = 0.85 for the whole scale. Conclusion: The scale is concluded to be a reliable and valid tool and can be utilized for determining the determination of attitudes of adults toward endocrine disruptors.
Harmonic Close-to-Convex Mappings Associated with Salagean q-differential Operator
(Babes-Bolyai University, 2025) Mishra, Omendra; ÇETİNKAYA, ASENA; Sokol, Janusz
In this paper, we define a new subclass (Formula presented) of analytic functions and a new subclass (Formula presented) of harmonic functions (Formula presented) associated with Sălăgean q-differential operator. We prove that a harmonic function (Formula presented) belongs to the class (Formula presented) if and only if the analytic functions h+∊g belong to (Formula presented) for each ∊ (|∊| = 1), and using a method by Clunie and Sheil-Small, we determine a sufficient condition for the class (Formula presented) to be close-to-convex. We provide sharp coefficient estimates, sufficient coefficient condition, and convolution properties for such functions classes. We also determine several conditions of partial sums of (Formula presented).