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Investigation of Salinity Tolerance Related Gene Expression in Rice (Oryza sativa L.)
No full textRice ranks second with the highest consumption rate after corn in world production. As a result of various biotic and abiotic stress factors exposed during production, plants quit normal growth. Under such conditions, plants have developed survival mechanisms at the molecular level in order to maintain their existence. Phenotypic data is widely used to evaluate plant tolerance with assistance of gene expression analysis that interprets the source of tolerance. In this study, Osmancık-97 rice variety which is extensively cultivated in Türkiye was grown under four different salt (NaCl) concentrations (60, 90, 120 mM and control) in in vivo conditions. The study aimed to determine the expression differences of the TPS1, NHX1, SOS1 and HKT2;1 genes under increasing salinity conditions. In the highest applied NaCl concentration (120 mM), TPS1, NHX1, SOS1 and HKT2;1 gene expression decreased 78.2, 74.0, 78.3, and 73.5% compared to the control, respectively. In the same concentration, parameters of photosynthetic pigment content, average plant length, fresh and dry weight, and root length decreased significantly. In contrast, proline accumulation and TBARS content presented significant increases. The difference in ion homeostasis and salt tolerance among species or varieties is related to the expression of regulatory genes. Rice, a moderately salt sensitive crop, has complex responses to salt stress and its sensitivity varies according to species, variety, growth and development stages and the duration of stress to which it is exposed
Tailored Multibody Tibiofemoral Joint Model for Precision Care
No full textKnee motion involves intricate coordination among various anatomical structures. Effective treatment of knee pathologies requires precise identification of deformities and accurate surgical interventions, which often involve rapid tissue modification based on established knowledge. However, motion disorders are typically detected long after surgery. To address this, a simulation environment is proposed to plan and analyze surgical impacts on knee motion. Comprehensive knee joint modeling is crucial for a successful simulation. Clinically accepted movement procedures based on passive knee motion make tibiofemoral articulation modeling sufficient. Proposed model tibiofemoral articulation, incorporating 15 ligaments, tibial and femoral bones, and cartilages. Ligaments' tensile, bones', and cartilages' contact forces (CFs) define internal force interactions. Anatomical structures, their shapes, positions, and attachment points are identified from MRI, ensuring patient-specific modeling. Simulation results are compared to cadaver data using passive knee motion. Two rotational and three translational dependent joint motions (JMs) are compared pairwise. The results are highly correlated with the clinical benchmark. Pearson's correlation show a strong association between experimental and simulated passive knee flexions (PKFs; r > 0.89). The comparison is statistically significant with p < 0.05. Anterior-posterior translation showed the highest correlation (R-2 = 0.994). The findings indicate that the simulated model closely replicates actual knee responses
Critiquing Gender and Islam-Transnational Intersectional and Queer Perspectives
No full textBook Series; Critiquing Gender and Islam-Transnational Intersectional and Queer Perspectives
Web Application Firewall Based On Machine Learning Models
No full textThe increasing reliance on web applications for storing sensitive data and financial transactions has elevated the importance of web application security. A machine learning-based web application firewall was designed to protect web applications against injection vulnerabilities. A hybrid dataset, including CISC 2010, HTTPParams 2015, and real-time Hypertext Transfer Protocol (HTTP) requests, was employed. The study evaluated five classification algorithms-K-nearest neighbors, logistic regression, na & iuml;ve Bayes, support vector machine, and decision tree-for detecting cross site scripting (XSS), Structured Query Language (SQL) Injection, Operating System Command Injection, and Local File Inclusion attacks. Decision tree was identified as the algorithm with the highest precision, accuracy, recall, F1-score, receiver operating characteristic (ROC), and area under the curve (AUC) values. According to the confusion matrix analysis, the real-time tested web application firewalls (WAF) achieved a remarkably high F1 score of 93.13% and accuracy of 93.27%. The findings indicate that machine learning-based WAFs effectively protect web applications against injection threats. Future work includes expanding the WAF to cover other attack types and testing it on different datasets
İstanbul Kültür Üniversitesi, 2024 Yılı Sürdürülebilirlik Raporu
No full text2024 yılı boyunca SKA odaklı yürütülen etkinlikler, bilimsel yayınlar, ders içerikleri ve uluslararası sıralamalardaki gelişmelerin yer aldığı bu rapor, sürdürülebilirlik çalışmalarının kapsamlı bir özetini sunmaktadır.
Sürdürülebilirlik bir kültürdür
Single-Crystal Polarized Raman Spectra of 6-Bromopyridine-2-Carbaldehyde
No full textThe room temperature (RT) single-crystal polarized Raman spectra of 6-bromopyridine-2-carbaldehyde (BPCA) have been obtained and interpreted based on fully periodic DFT calculations for the P21/a (No. 14; monoclinic) crystal of the compound. The calculations, performed with the CRYSTAL software employing the Becke three parameters Lee, Yang, and Parr (B3LYP) functional and the polarization-consistent triple-zeta valence plus polarization basis set (pob-TZVP), were able to reproduce very well the experimental data, thus allowing a detailed assignment of the Raman active Ag and Bg modes to individual bands. The isotropic non-polarized Raman spectrum of BPCA was also calculated and shown to agree very well with the corresponding experimental Raman spectrum. Finally, the RT infrared spectrum of BPCA was also revisited in light of the performed periodic calculations, improving on previously reported interpretation based on extrapolation of the interpretation of the spectra obtained for the isolated molecule of the compound to the crystalline phase. In this crystalline system, intermolecular interactions exert only a minor influence on the intramolecular vibrational potential. As such, this study also serves as a benchmark for the employed computational approach, demonstrating its ability to capture the effects of both crystallographic periodicity and symmetry on the polarization features of vibrational spectra.European Research Executive Agency
European Research Agency (European Union
6th International Interdisciplinary Chaos Symposium on Chaos and Complex Systems: May 8–10
No full textThis book contains the programme and abstracts of the presentations delivered at the 6th International Interdisciplinary Chaos Symposium on Chaos and Complex Systems (SCCS2025), held on May 8–10, 2025, in Istanbul. It provides concise summaries of the research papers presented, offering readers an overview of the key topics and findings discussed during the event
The Image of the "Chaotic Child" in Folk Beliefs and Rituals
No full textThe concept of childhood is a multifaceted one, both cross-culturally and within national cultures. Perspectives associated with this concept have varied across historical processes and different geographical regions. In the past, children were often perceived as anonymous, uncategorized beings, frequently considered equivalent to adults. However, in contemporary societies, children are viewed as valuable individuals, nurtured and educated with care as the adults of the future, with all available resources used to meet their needs to the fullest extent. The subject and aim of our study, which evaluates data obtained through qualitative research and document analysis, is to explore the image of the child that emerges in folk beliefs, narratives, and rituals from a broad perspective. To achieve this, a comparative approach has been adopted, examining the depiction of children from the past to the present and in comparison with Western societies. In order to make this distinction, the image of the child has been analyzed as a recurring and varied motif in folk narratives, such as the Dede Korkut Kitab & imath;, which reflects the Turkish identity of the Middle Ages, and the Alevi-Bektashi velayetname (hagiographies), which provide a realistic portrayal of the traditional perspective. Doubtlessly, although a wide range of sources can be consulted to critically examine the image of the child, for the specific objectives of this study, two primary sources have been selected to facilitate a historical analysis. In our study, after the introduction, definitions and evaluations regarding the chaotic image of the child are provided. Then, the perspectives of societies, considered traditional, towards this image are examined, and the place and significance of the child image in transition rituals such as birth, circumcision, marriage, and death are deepened with examples.Later, the role and status of the child encountered in oral folk narratives, which are records of popular beliefs and rituals, are examined in detail. Understanding the changes in the concept of childhood throughout history and their effects on this concept is considered crucial for the future of societies. In this context, we believe that harmonizing tradition with globalization will positively contribute to the construction of society's future
A Comparative Analysis of CNN Architectures, Fusion Strategies, and Explainable AI for Fine-Grained Macrofungi Classification
No full textThis study was motivated by the persistent difficulty of accurately identifying morphologically similar macrofungi species, which remains a significant challenge in fungal taxonomy and biodiversity monitoring. This study presents a deep learning framework for the automated classification of seven morphologically similar coprinoid macrofungi species. A curated dataset of 1692 high-resolution images was used to evaluate ten state-of-the-art convolutional neural networks (CNNs) and three novel fusion models. The Dual Path Network (DPN) achieved the highest performance as a single model with 89.35% accuracy, a 0.8764 Matthews Correlation Coefficient (MCC), and a 0.9886 Area Under the Curve (AUC). The feature-level fusion of Xception and DPN yielded competitive results, reaching 88.89% accuracy and 0.8803 MCC, demonstrating the synergistic potential of combining architectures. In contrast, lighter models like LCNet and MixNet showed lower performance, achieving only 72.05% accuracy. Explainable AI (XAI) techniques, including Grad-CAM and Integrated Gradients, confirmed that high-performing models focused accurately on discriminative morphological structures such as caps and gills. The results underscore the efficacy of deep learning, particularly deeper architectures and strategic fusion models, in overcoming the challenges of fine-grained visual classification in mycology. This work provides a robust, interpretable computational tool for automated fungal identification, with significant implications for biodiversity research and taxonomic studies
International Symposium for Production Research
No full textPart of the book series: Lecture Notes in Mechanical Engineering ((LNME)).This study investigates the factors affecting agricultural productivity in Turkey from 1990 to 2023 using factor analysis. As the global population increases, understanding the variables that influence crop yields becomes crucial for sustaining the food supply. The research examines data such as average temperature, rainfall, inflation rates, and fuel prices, sourced primarily from the Turkish Statistical Institute. By applying factor analysis, the study groups these variables into meaningful clusters that reveal the underlying correlations between them and agricultural outputs like wheat, barley, rice, and corn. The results indicate that certain economic and environmental factors, such as consumer inflation and annual average temperature, consistently influence multiple crops. This research contributes a new perspective to the literature by identifying the key factors that drive agricultural productivity in Turkey, providing insights that can inform future agricultural policies. The study concludes with suggestions for further analysis involving a broader range of variables to enhance understanding of the complex dynamics in Turkish agriculture