TR-Dizin İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/396
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Article Citation - WoS: 1Comprehensive Prediction of FBN1 Targeting Mirnas: A Systems Biology Approach for Marfan Syndrome(Galenos Publishing House, 2025-09-22) Orhan, M.E.; Demirci, Y.M.; Saçar Demirci, M.D.S.; Demirci, Muserref Duygu SacarObjective: Marfan syndrome (MFS) is a genetic connective tissue disorder primarily caused by mutations in the FBN1 gene. Emerging evidence highlights the regulatory role of microRNAs (miRNAs) in modulating gene expression in MFS, but a systematic investigation into miRNAs targeting FBN1 is lacking. This study aimed to comprehensively identify miRNAs interacting with the FBN1 transcript to reveal potential molecular regulators and therapeutic targets. Methods: Human miRNA sequences were retrieved from miRBase (Release 22.1), and the canonical FBN1 transcript (RefSeq: NM_000138.5) was used for target prediction. Computational interaction analysis was conducted using the psRNATarget server with stringent parameters to detect potential miRNA binding sites. Expression profiles and disease associations of the top candidate miRNAs were further investigated through database integration and literature review. Results: Out of 2656 human mature miRNAs analyzed, 251 were predicted to bind FBN1, with the hsa-miR-181 family exhibiting the highest number of predicted interactions. Evidence from the literature highlighted dysregulation of hsa-miR-181 expression in MFS patients, suggesting a functional role in disease pathophysiology. Conclusion: This study identifies key members of the hsa-miR-181 family as post-transcriptional regulators of FBN1, offering new insights into miRNA-driven mechanisms in MFS. These findings support the potential of RNA-based diagnostics and therapeutic strategies targeting miRNA-FBN1 interactions. ©Copyright 2025 The Author.Article Tracing Trajectories of Regime Support in Turkey(Ege Univ, Fac Economics & Admin Sciences, 2022-06-09) Inan, MuratAccording to the legitimacy approach of political culture research, public's approval of a particular regime as the best form of government and rejection of its alternatives provides public support for that particular regime. This research attempted to trace temporal trajectories of approval of democratic political system as well as it's three alternative forms of government among the electorates of recent three major political parties in Turkey, the Justice and Development Party (AKP), the Republican People's Party (CHP) and the Nationalist Movement Party (MHP). It also revealed the extent these parties' manifesto documents praise democratic political system across the successive eighteen general elections in the modern Turkish political history. It revealed the changes in both public and party support for four alternative regimes across years in modern Turkish history. This research analyzed the World Values Survey and the Manifesto Project data using quantitative research methods. It has achieved four main findings. First, voters are more stable than their parties across time in terms of pro-democracy. Second, democracy clearly emerges as the strongest alternative among the four alternative regimes for all the three electorates. Third, supporting democracy and rejecting its three alternatives occupy different places in the minds of the three party electorates. Fourth, changes in the three political parties' pro-democracy as identified in their manifesto documents are not always parallel with changes in those of their voters.Article Citation - WoS: 2Citation - Scopus: 2The Nexus of Leadership, Political Empowerment, and Social Mobilization: The Case of the July 15 Coup Attempt in Turkey(Seta Foundation, 2020-06-30) Donmez, Rasim Ozgur; Timur, Kasim; Lloyd, Fatma Armagan TekeThis study analyzes the mutually empowering relations between Turkish President Recep Tayyip Erdogan and his followers, and how Erdogan's charismatic leadership and image functioned to galvanize his followers on the night of July 15, 2016, when large numbers of them mobilized against the attempted coup. The article has three sections. The first is a theoretical discussion which sheds light on the concept and the underlying mechanisms of political empowerment and its effects on the relationships between leaders and followers. The second section evaluates Erdogan's characteristics and ruling style, which was instrumental in motivating resistance to the abortive coup. Finally, the third section analyzes the various means by which Erdogan was able to inspire the masses to mobilize against the armed junta through interviews and observations.Article Citation - WoS: 1Citation - Scopus: 1The Comparison of Fragility Curves of Moment-Resisting and Braced Frames Used in Steel Structures Under Varying Wind Load(Turkish Chamber Civil Engineers, 2025-03-01) Ozalp, Abdulkadir; Gokdemir, Hande; Ciftci, CihanIn this study, the performance of two different steel structure types (moment-resisting frame and braced frame) under wind loading was compared by addressing the fragility curves of these structure types. To perform this comparison, the dimensions of the members of these structural systems were first determined. Then, nonlinear static pushover analyses were conducted to assess the performance levels of each frame type. After applying these analyses, time-history analyses were performed with 100 different wind loads for each varying equivalent mean wind speed. Afterwards, the probability of exceeding the predetermined structural performance limits of the structure types was determined using Monte Carlo simulation method. Finally, the results of the simulation method were used to adapt the maximum likelihood estimation method to obtain the fragility curves of the structures. To conclude, it has been revealed that the material cost of the structure doubles when diagonal elements are used, but the wind speed required for a 100% collapse probability to occur in the braced frame is twice as high compared to the moment-resisting frame.Article Real-Effort Tasks in Laboratory Experiments(Economic and Financial Research Assoc - Efad, 2023-09-30) Demirtas, Burak KaganLaboratory experiments used in economics are differentiated in terms of many technical features. One of these technical features is whether the experiment involves a real-effort task. A real-effort task can be defined as a task in which the experiment participants work on aAreal job during the experiment, spend time and effort, determine their performance level and as a result earn a certain amount of money. This study aims to examine real-effort tasks that are frequently used in experimental economics studies, and to discuss potential problems that researchers may face when conducting experiments with real- effort tasks. Within the scope of this review, real-effort tasks commonly used in the literature are categorized under four groups: real-effort tasks based on mathematical operations, puzzles, slider task, and word encryption tasks. Choice of the real-effort task is important for an experimental study because it may lead to misinterpretation of the findings. AAsAa result of the study, the learning effect, the boredom of the task and the abilities required by the task are seen as possible sources of measurement error. While the learning effect and boredom may cause problems especially in within-subject designs, it was found that differences in the abilities of participants may cause measurement errors especially in between-subject designs.Article Citation - WoS: 1Re-Visiting Ambivalent Sexism Inventory (ASI): Construct Validity of Benevolent Sexism and Measurement Invariance of ASI(Istanbul Univ, Fac Letters, dept Psychology, 2022-04-06) Aktan, Timucin; Yalcindag, BilgeThe ambivalent sexism theory states that sexism comprises hostile and benevolent beliefs and that benevolent sexism is a second-order factor consisting of protective paternalism, complementary gender differentiation and heterosexual intimacy. The subdimensions of benevolent sexism toward women have recently piqued people's interest. The Turkish version of the ambivalent sexism inventory's (ASI's) construct validity should be reexamined in light of this apparent interest in contemporary studies. Accordingly, in the current study, the aim is to test the preferred structural model in which protective sexism was defined as a second-order factor consisting of protective patriarchy, complementary differentiation between genders and heterosexual intimacy. Moreover, measurement invariance analysis will be used to test the stability of the scale's structure in different samples. The data of 1803 participants from different studies conducted between 2009 and 2019 (1194 women and 593 men, 16 unidentified) were merged. Findings of the confirmatory factor analyses indicated that the four-factor solution (i.e. hostile sexism and three subfactors of benevolence) fitted the data better than the other models (i.e. one-factor and two-factor models, and the preferred structural model). Explanatory factor analysis via exploratory structural equation modeling revealed a two-factor solution composed of benevolence and hostility, but the findings also underlined two psychometrically weak items. Finally, measurement invariance analyses demonstrated full invariance between private and public university samples, and an invariance between women and men samples except for sample means. Only the means of the samples differed in the women-men comparison, but in a theoretically predicted way, and men had higher scores in all subscales except for complementary gender differentiation. In sum, our findings provided significant support for the construct validity and measurement invariance of ASI while raising questions about the theoretical construct measured and the items needed to be revised.Article Performance Evaluation of Energy Companies With a Novel Integrated Multi- Criteria Decision Making Method(Kafkas University Iibf, 2022-12-27) Madenoglu, Fatma Selen; Unlusoy, Omer Faruk; Yilmaz, CagatayFinancial statements are an important tool for assessing and analyzing an organization's financial performance. Financial performance analysis allows for an accurate and appropriate appraisal of an organization's performance. The evaluation procedure must be thoroughly stated because financial performance indicators represent a company's competitiveness. This study provides a novel integrated multi-criteria decision-making method for analyzing an organization's financial performance. The applicability of the proposed method is assessed employing financial ratios that are integrated to generate a financial performance score for eight well-known Turkish energy companies. The criteria are weighted using the entropy method in the proposed method. The multi- attributive border approximation area comparison (MABAC) method is used to rank the companies. As the weights of the criteria have an impact on the ranking outcomes, a sensitivity analysis of the weights is performed. We also exhibit a comparison analysis of energy company rankings to validate the proposed approach's results using four MCDM methods: ELECTRE, MAUT, TOPSIS, and WASPAS. In addition, an alternative weighting method is also used to evaluate the results. The results show that the proposed method is an effective MCDM for coping with evaluation problems.Article Citation - WoS: 4Citation - Scopus: 5Noise-Assisted Multivariate Empirical Mode Decomposition Based Emotion Recognition(Istanbul Univ-Cerrahapasa, 2018-08-03) Ozel, Pinar; Akan, Aydin; Yilmaz, BulentEmotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms. Currently, in addition to classical time-frequency methods, emotional state data have been processed via data-driven methods such as empirical mode decomposition (EMD). Despite its various benefits, EMD has several drawbacks: it is intended for univariate data; it is prone to mode mixing; and the number of local extrema must be enough before the EMD process can begin. To overcome these problems, this study employs a multivariate EMD and its noise-assisted version in the emotional state classification of electroencephalogram signals. Emotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms. Currently, in addition to classical time-frequency methods, emotional state data have been processed via data-driven methods such as empirical mode decomposition (EMD). Despite its various benefits, EMD has several drawbacks: it is intended for univariate data; it is prone to mode mixing; and the number of local extrema must be enough before the EMD process can begin. To overcome these problems, this study employs a multivariate EMD and its noise-assisted version in the emotional state classification of electroencephalogram signals.Article Citation - WoS: 2Machine Learning Based Network Intrusion Detection With Hybrid Frequent Item Set Mining(Gazi Univ, 2024-10-02) Firat, Murat; Bakal, Gokhan; Akbas, Ayhan; Bakal, MehmetWith the development and expansion of computer networks day by day and the diversity of software developed, the damage that possible attacks can cause is increasing beyond the predictions. Intrusion Detection Systems (STS/IDS) are one of the practical defense tools against these potential attacks that are constantly growing and diversifying. Thus, one of the emerging methods among researchers is to train these systems with various artificial intelligence methods to detect subsequent attacks in real time and take the necessary precautions. However, the ultimate goal is to propose a hybrid feature selection approach to improve the classification performance. The raw dataset originally enclosed 85 descriptor features (attributes) for classification. These attributes are extracted using CICFlowMeter from a PCAP file where network traffic is recorded for data curation. In this study, classical feature selection methods and frequent item set mining approaches were employed in feature selection for constructing a hybrid model. We aimed to examine the effect of the proposed hybrid feature selection approach on the classification task for the network traffic data containing ordinary and attack records. The outcomes demonstrate that the proposed method gained nearly 3% improvement when applied with the Logistic Regression algorithm on classifying more than 225,000 records.Article Citation - WoS: 1GIS-AHP Approach for a Comprehensive Framework to Determine the Suitable Regions for Geothermal Power Plants in Izmir, Turkiye(Konya Teknik Univ, 2024-02-15) Koca, Kemal; Karipoglu, Fatih; Ozturk, Emel ZerayGeothermal energy is gaining more reputation and importance around the world. Correspondingly, suitable location selection is a critical step and has become necessary for the successful installation and operation of geothermal power plants. This study investigated suitability of & Idot;zmir region, located in the Aegean part of T & uuml;rkiye, in terms of geothermal power plants applications by using the combination of Geographical Information System and Analytic Hierarchy Process. Based on the request of power plants, thirteen important criteria were evaluated under three main categories named as physical (C1), environmental (C2) and technical (C3). Moreover, expert's opinions were taken into consideration to calculate the importance of these criteria. Key results showed that & Idot;zmir was suitable for geothermal power plants. The final suitability map layer pointed out that %8.73 (1.037 km2) of total area were determined as highly suitable regions in terms of installation. In addition, the obtained suitability map layer was compared with actual geothermal power plants. Based on the comparison study, power plants in Seferihisar were moderately suitable for geothermal power plants while the location of Bal & ccedil;ova power plant was highly suitable. Regarding the suitability assessment in the present study, the location of Dikili power plants had the least suitability score.