Comparison of some chemical parameters of a naturally debittered olive (Olea europaea L.) type with regular olive varieties

Some olives grown in Karaburun peninsula in the west part of Turkey and mostly coming from Erkence variety lose their bitterness while still on the tree and are called Hurma among locals. This olive type does not require further processing to remove the bitter compounds. In this study, sugar, organic acid and fatty acid profiles of Hurma, Erkence (not naturally debittered) and Gemlik (commonly consumed as table olive) olives were determined throughout 8 weeks of maturation period for two consecutive harvest seasons, and the results were analysed by principal component analysis (PCA). PCA of sugar and organic acid data revealed a differentiation in terms of harvest year but not on variety. Hurma olive is separated from others due to its fatty acid profile, and it has higher linoleic acid content compared to others. This might be an indication of increased desaturase enzyme activity for Hurma olives during natural debittering phase.TUBITAK (TOVAG-110O780

The role of theory of mind, emotion knowledge and empathy in preschoolers’ disruptive behavior

Objectives : Research examining disruptive behaviors in clinical groups of preschool and school-aged children has consistently revealed significant difficulties in their emotion knowledge and empathy but intact performance in their theory-of-mind (ToM). However, it is largely not known if these difficulties in emotion knowledge and empathy as opposed to ToM are specific to extreme forms of disruption in clinical groups or rather represent broad deficiencies related to disruptive behaviors in general, including the milder levels exhibited by typically developing children. Milder disruptive behaviors (e.g., whining, arguing, rule-breaking and fighting) in peer contexts might relate to normative variations in socio-cognitive and emotional skills like ToM, emotion knowledge and empathy. To illuminate whether the same pattern of relations observed in clinical samples would arise in typical development, this study aims to examine the role of ToM, emotion knowledge and empathy in typically developing preschoolers’ disruptive behaviors.WOS:000510437900014Scopus - Affiliation ID: 60105072Social Sciences Citation IndexQ3 - Q4ArticleOcak2020YÖK - 2019-2

The Khaldun-Laffer Curve Revisited: A Personal Income Tax-Based Analysis for Turkey

The objective of this paper is to revisit as well as empirically examine an old but still discussed postulate, the Khaldun-Laffer curve, on the basis of personal income tax by making use annual time-series data for Turkey for the period 1970-2015. The findings of the paper confirm the validity of the Khaldun-Laffer curve hypothesis. In addition, we infer that the optimal tax rate that maximizes the tax revenue generated from personal income taxation in Turkey is 15.03 percent. This rate is well-below than the current rate which we estimate as 15.37 percent, implying that Turkey’s current tax rate for personal income tax takes place in the prohibitive range of the Khaldun-Laffer curve. These findings suggest that the current tax rate should be lowered and to its optimal level to collect more tax revenue. Getting down the current rate to its revenue-maximizing rate not only would it enable the Turkish authorities to collect more revenues with a relatively lower rate, but also would allow them to minimize the substitution effects of personal income tax while maximizing the income revenues from it

Discovering inconsistencies between requested permissions and application metadata by using deep learning

This is an accepted manuscript of an article published by IEEE in 2020 International Conference on Information Security and Cryptology (ISCTURKEY), available online at https://ieeexplore.ieee.org/document/9308004 The accepted version of the publication may differ from the final published version.Android gives us opportunity to extract meaningful information from metadata. From the security point of view, the missing important information in metadata of an application could be a sign of suspicious application, which could be directed for extensive analysis. Especially the usage of dangerous permissions is expected to be explained in app descriptions. The permission-to-description fidelity problem in the literature aims to discover such inconsistencies between the usage of permissions and descriptions. This study proposes a new method based on natural language processing and recurrent neural networks. The effect of user reviews on finding such inconsistencies is also investigated in addition to application descriptions. The experimental results show that high precision is obtained by the proposed solution, and the proposed method could be used for triage of Android applications