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58,095 results on '"POLAT, A."'

1. LENS-XAI: Redefining Lightweight and Explainable Network Security through Knowledge Distillation and Variational Autoencoders for Scalable Intrusion Detection in Cybersecurity

Author

Yagiz, Muhammet Anil and Goktas, Polat

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Emerging Technologies
Abstract

The rapid proliferation of Industrial Internet of Things (IIoT) systems necessitates advanced, interpretable, and scalable intrusion detection systems (IDS) to combat emerging cyber threats. Traditional IDS face challenges such as high computational demands, limited explainability, and inflexibility against evolving attack patterns. To address these limitations, this study introduces the Lightweight Explainable Network Security framework (LENS-XAI), which combines robust intrusion detection with enhanced interpretability and scalability. LENS-XAI integrates knowledge distillation, variational autoencoder models, and attribution-based explainability techniques to achieve high detection accuracy and transparency in decision-making. By leveraging a training set comprising 10% of the available data, the framework optimizes computational efficiency without sacrificing performance. Experimental evaluation on four benchmark datasets: Edge-IIoTset, UKM-IDS20, CTU-13, and NSL-KDD, demonstrates the framework's superior performance, achieving detection accuracies of 95.34%, 99.92%, 98.42%, and 99.34%, respectively. Additionally, the framework excels in reducing false positives and adapting to complex attack scenarios, outperforming existing state-of-the-art methods. Key strengths of LENS-XAI include its lightweight design, suitable for resource-constrained environments, and its scalability across diverse IIoT and cybersecurity contexts. Moreover, the explainability module enhances trust and transparency, critical for practical deployment in dynamic and sensitive applications. This research contributes significantly to advancing IDS by addressing computational efficiency, feature interpretability, and real-world applicability. Future work could focus on extending the framework to ensemble AI systems for distributed environments, further enhancing its robustness and adaptability.

Published
2025

2. Continuous and Reversible Electrical Tuning of Fluorescent Decay Rate via Fano Resonance

Author

Polat, Emre Ozan, Artvin, Zafer, Şaki, Yusuf, Bek, Alpan, and Sahin, Ramazan

Subjects
Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Physics - Computational Physics, Quantum Physics
Abstract

Decay rate of an atomic or molecular dipole depends on the local density of optical states (LDOS) -- Purcell effect -- which can significantly be enhanced near a dielectric-core metal-shell nanoparticle (CSNP). On top of that, an auxiliary quantum object (QO) can introduce a Fano transparency in the plasmonic spectrum of the CSNP. Here, we show that an auxiliary QO, located at the hotspot of the CSNP, can modify the LDOS, hence the decay rate of an excited dipole. Moreover, by controlling the resonance of the auxiliary QO via an applied voltage, one can continuously and reversibly tune both the radiative and nonradiative decay rates of the dipole up to 2 orders-of-magnitude. This phenomenon emerges as an invaluable tool to implement in integrated quantum technologies, enabling realization of on-demand entanglement/single-photon sources, controlled execution of quantum gates and electrical-control of superradiant-like phase transitions. It also bears potential for application in super-resolution microscopy and surface-enhanced Raman spectroscopy (SERS)., Comment: 6 pages, 3 figures

Published
2024

3. Multimodal joint prediction of traffic spatial-temporal data with graph sparse attention mechanism and bidirectional temporal convolutional network

Author

Zhang, Dongran, Yan, Jiangnan, Polat, Kemal, Alhudhaif, Adi, and Li, Jun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Traffic flow prediction plays a crucial role in the management and operation of urban transportation systems. While extensive research has been conducted on predictions for individual transportation modes, there is relatively limited research on joint prediction across different transportation modes. Furthermore, existing multimodal traffic joint modeling methods often lack flexibility in spatial-temporal feature extraction. To address these issues, we propose a method called Graph Sparse Attention Mechanism with Bidirectional Temporal Convolutional Network (GSABT) for multimodal traffic spatial-temporal joint prediction. First, we use a multimodal graph multiplied by self-attention weights to capture spatial local features, and then employ the Top-U sparse attention mechanism to obtain spatial global features. Second, we utilize a bidirectional temporal convolutional network to enhance the temporal feature correlation between the output and input data, and extract inter-modal and intra-modal temporal features through the share-unique module. Finally, we have designed a multimodal joint prediction framework that can be flexibly extended to both spatial and temporal dimensions. Extensive experiments conducted on three real datasets indicate that the proposed model consistently achieves state-of-the-art predictive performance.

Published
2024

4. Recommender Systems for Sustainability: Overview and Research Issues

Author

Felfernig, Alexander, Wundara, Manfred, Tran, Thi Ngoc Trang, Polat-Erdeniz, Seda, Lubos, Sebastian, El-Mansi, Merfat, Garber, Damian, and Le, Viet-Man

Subjects
Computer Science - Information Retrieval, Computer Science - Artificial Intelligence
Abstract

Sustainability development goals (SDGs) are regarded as a universal call to action with the overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity for all people. In order to achieve these objectives, different AI technologies play a major role. Specifically, recommender systems can provide support for organizations and individuals to achieve the defined goals. Recommender systems integrate AI technologies such as machine learning, explainable AI (XAI), case-based reasoning, and constraint solving in order to find and explain user-relevant alternatives from a potentially large set of options. In this article, we summarize the state of the art in applying recommender systems to support the achievement of sustainability development goals. In this context, we discuss open issues for future research.

Published
2024
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5. PASTA-4-PHT: A Pipeline for Automated Security and Technical Audits for the Personal Health Train

Author

Welten, Sascha, Kindermann, Karl, Polat, Ahmet, Görz, Martin, Jugl, Maximilian, Neumann, Laurenz, Neumann, Alexander, Lohmöller, Johannes, Pennekamp, Jan, and Decker, Stefan

Subjects
Computer Science - Cryptography and Security, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

With the introduction of data protection regulations, the need for innovative privacy-preserving approaches to process and analyse sensitive data has become apparent. One approach is the Personal Health Train (PHT) that brings analysis code to the data and conducts the data processing at the data premises. However, despite its demonstrated success in various studies, the execution of external code in sensitive environments, such as hospitals, introduces new research challenges because the interactions of the code with sensitive data are often incomprehensible and lack transparency. These interactions raise concerns about potential effects on the data and increases the risk of data breaches. To address this issue, this work discusses a PHT-aligned security and audit pipeline inspired by DevSecOps principles. The automated pipeline incorporates multiple phases that detect vulnerabilities. To thoroughly study its versatility, we evaluate this pipeline in two ways. First, we deliberately introduce vulnerabilities into a PHT. Second, we apply our pipeline to five real-world PHTs, which have been utilised in real-world studies, to audit them for potential vulnerabilities. Our evaluation demonstrates that our designed pipeline successfully identifies potential vulnerabilities and can be applied to real-world studies. In compliance with the requirements of the GDPR for data management, documentation, and protection, our automated approach supports researchers using in their data-intensive work and reduces manual overhead. It can be used as a decision-making tool to assess and document potential vulnerabilities in code for data processing. Ultimately, our work contributes to an increased security and overall transparency of data processing activities within the PHT framework.

Published
2024

6. Class Distance Weighted Cross Entropy Loss for Classification of Disease Severity

Author

Polat, Gorkem, Çağlar, Ümit Mert, and Temizel, Alptekin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Assessing disease severity involving ordinal classes, where each class represents increasing levels of severity, benefit from loss functions that account for this ordinal structure. Traditional categorical loss functions, like Cross-Entropy (CE), often perform suboptimally in these scenarios. To address this, we propose a novel loss function, Class Distance Weighted Cross-Entropy (CDW-CE), which penalizes misclassifications more harshly when classes are farther apart. We evaluated CDW-CE on the Labeled Images for Ulcerative Colitis (LIMUC) dataset using various deep architectures. Its performance was compared against several categorical and ordinal loss functions. To analyze the quality of latent representations, we used t-distributed stochastic neighbor embedding (t-SNE) visualizations and quantified their clustering with the Silhouette Score. We also compared Class Activation Maps (CAM) generated by models trained with CDW-CE and CE loss, incorporating domain expert feedback to evaluate alignment with expert knowledge. Our results show that CDW-CE consistently improves performance in ordinal image classification tasks. It achieves higher Silhouette Scores, indicating better differentiation of class representations, and its CAM visualizations demonstrate a stronger focus on clinically significant regions, as confirmed by domain experts.

Published
2024

7. Evaluation of outbreak persistence caused by multidrug-resistant and echinocandin-resistant Candida parapsilosis using multidimensional experimental and epidemiological approaches

Author

Daneshnia, Farnaz, Floyd, Daniel J, Ryan, Adam P, Ghahfarokhy, Pegah Mosharaf, Ebadati, Arefeh, Jusuf, Sebastian, Munoz, Julieta, Jeffries, Nathan Elias, Yvanovich, Emma Elizabeth, Apostolopoulou, Anna, Perry, Austin M, Lass-Flörl, Cornelia, Birinci, Asuman, Hilmioğlu-Polat, Süleyha, Ilkit, Macit, Butler, Geraldine, Nobile, Clarissa J, Arastehfar, Amir, and Mansour, Michael K

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Microbiology, Clinical Sciences, Medical Microbiology, Clinical Research, Emerging Infectious Diseases, Women's Health, Infectious Diseases, Antimicrobial Resistance, Biodefense, 2.1 Biological and endogenous factors, 2.2 Factors relating to the physical environment, Infection, Good Health and Well Being, Animals, Mice, Humans, Candida parapsilosis, Antifungal Agents, Drug Resistance, Fungal, Echinocandins, Disease Outbreaks, Microbial Sensitivity Tests, Multidrug resistance, echinocandin resistance, mannan, chitin, Beta-glucan, Β-glucan, Clinical sciences, Epidemiology
Abstract

Candida parapsilosis is known to cause severe and persistent outbreaks in clinical settings. Patients infected with multidrug-resistant C. parapsilosis (MDR Cp) isolates were identified in a large Turkish hospital from 2017-2020. We subsequently identified three additional patients infected with MDR Cp isolates in 2022 from the same hospital and two echinocandin-resistant (ECR) isolates from a single patient in another hospital. The increasing number of MDR and ECR isolates contradicts the general principle that the severe fitness cost associated with these phenotypes could prevent their dominance in clinical settings. Here, we employed a multidimensional approach to systematically assess the fitness costs of MDR and ECR C. parapsilosis isolates. Whole-genome sequencing revealed a novel MDR genotype infecting two patients in 2022. Despite severe in vitro defects, the levels and tolerances of the biofilms of our ECR and MDR isolates were generally comparable to those of susceptible wild-type isolates. Surprisingly, the MDR and ECR isolates showed major alterations in their cell wall components, and some of the MDR isolates consistently displayed increased tolerance to the fungicidal activities of primary human neutrophils and were more immunoevasive during exposure to primary human macrophages. Our systemic infection mouse model showed that MDR and ECR C. parapsilosis isolates had comparable fungal burden in most organs relative to susceptible isolates. Overall, we observed a notable increase in the genotypic diversity and frequency of MDR isolates and identified MDR and ECR isolates potentially capable of causing persistent outbreaks in the future.

Published
2024

8. Heterozygous BTNL8 variants in individuals with multisystem inflammatory syndrome in children (MIS-C).

Author

Bellos, Evangelos, Santillo, Dilys, Vantourout, Pierre, Jackson, Heather, Duret, Amedine, Hearn, Henry, Seeleuthner, Yoann, Talouarn, Estelle, Hodeib, Stephanie, Patel, Harsita, Powell, Oliver, Yeoh, Sophya, Mustafa, Sobia, Habgood-Coote, Dominic, Nichols, Samuel, Estramiana Elorrieta, Leire, DSouza, Giselle, Wright, Victoria, Estrada-Rivadeneyra, Diego, Tremoulet, Adriana, Dummer, Kirsten, Netea, Stejara, Condino-Neto, Antonio, Lau, Yu, Núñez Cuadros, Esmeralda, Toubiana, Julie, Holanda Pena, Marisol, Rieux-Laucat, Frédéric, Luyt, Charles-Edouard, Haerynck, Filomeen, Mège, Jean, Chakravorty, Samya, Haddad, Elie, Morin, Marie-Paule, Metin Akcan, Özge, Keles, Sevgi, Emiroglu, Melike, Alkan, Gulsum, Tüter Öz, Sadiye, Elmas Bozdemir, Sefika, Morelle, Guillaume, Volokha, Alla, Kendir-Demirkol, Yasemin, Sözeri, Betul, Coskuner, Taner, Yahsi, Aysun, Gulhan, Belgin, Kanik-Yuksek, Saliha, Bayhan, Gulsum, Ozkaya-Parlakay, Aslinur, Yesilbas, Osman, Hatipoglu, Nevin, Ozcelik, Tayfun, Belot, Alexandre, Chopin, Emilie, Barlogis, Vincent, Sevketoglu, Esra, Menentoglu, Emin, Gayretli Aydin, Zeynep, Bloomfield, Marketa, AlKhater, Suzan, Cyrus, Cyril, Stepanovskiy, Yuriy, Bondarenko, Anastasiia, Öz, Fatma, Polat, Meltem, Fremuth, Jiří, Lebl, Jan, Geraldo, Amyrath, Jouanguy, Emmanuelle, Carter, Michael, Wellman, Paul, Peters, Mark, Pérez de Diego, Rebeca, Edwards, Lindsey, Chiu, Christopher, Noursadeghi, Mahdad, Bolze, Alexandre, Shimizu, Chisato, Kaforou, Myrsini, Hamilton, Melissa, Herberg, Jethro, Schmitt, Erica, Rodriguez-Palmero, Agusti, Pujol, Aurora, Kim, Jihoon, Cobat, Aurélie, Abel, Laurent, Zhang, Shen-Ying, Casanova, Jean-Laurent, Kuijpers, Taco, Burns, Jane, Levin, Michael, Hayday, Adrian, and Sancho-Shimizu, Vanessa

Subjects
Humans, COVID-19, Child, Systemic Inflammatory Response Syndrome, Male, Female, Butyrophilins, SARS-CoV-2, Child, Preschool, Heterozygote, Adolescent, Genetic Predisposition to Disease, Infant
Abstract

Multisystem inflammatory syndrome in children (MIS-C) is a rare condition following SARS-CoV-2 infection associated with intestinal manifestations. Genetic predisposition, including inborn errors of the OAS-RNAseL pathway, has been reported. We sequenced 154 MIS-C patients and utilized a novel statistical framework of gene burden analysis, burdenMC, which identified an enrichment for rare predicted-deleterious variants in BTNL8 (OR = 4.2, 95% CI: 3.5-5.3, P < 10-6). BTNL8 encodes an intestinal epithelial regulator of Vγ4+γδ T cells implicated in regulating gut homeostasis. Enrichment was exclusive to MIS-C, being absent in patients with COVID-19 or bacterial disease. Using an available functional test for BTNL8, rare variants from a larger cohort of MIS-C patients (n = 835) were tested which identified eight variants in 18 patients (2.2%) with impaired engagement of Vγ4+γδ T cells. Most of these variants were in the B30.2 domain of BTNL8 implicated in sensing epithelial cell status. These findings were associated with altered intestinal permeability, suggesting a possible link between disrupted gut homeostasis and MIS-C-associated enteropathy triggered by SARS-CoV-2.

Published
2024

9. Influence of oxygen orbitals and boundary conditions on the pairing behavior in the Emery model for doped ladders

Author

Polat, Gökmen and Jeckelmann, Eric

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Superconductivity
Abstract

We investigate the Emery model on several ladder-like lattices including two legs of copper d-orbitals and various numbers of oxygen p-orbitals. Pair binding energy, pair spatial structure, density distribution, and pairing correlation functions are calculated using the density matrix renormalization group (DMRG). We show that a Luther-Emery phase with enhanced pairing correlations can be found for hole doping as well as for electron doping with realistic model parameters. Ladder properties depend sensitively on model parameters, the oxygen p-orbitals taken into account, and boundary conditions. The pair binding energy is a more reliable quantity than correlation functions for studying pairing in ladders. Overall, our results for two-leg Emery ladders support the possibility of superconductivity in the hole-doped 2D model. The issue is rather to determine which of the various ladder structures and model parameters are appropriate to approximate the two-dimensional cuprates.

Published
2024

10. Transforming In-Vehicle Network Intrusion Detection: VAE-based Knowledge Distillation Meets Explainable AI

Author

Yagiz, Muhammet Anil, MohajerAnsari, Pedram, Pese, Mert D., and Goktas, Polat

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract

In the evolving landscape of autonomous vehicles, ensuring robust in-vehicle network (IVN) security is paramount. This paper introduces an advanced intrusion detection system (IDS) called KD-XVAE that uses a Variational Autoencoder (VAE)-based knowledge distillation approach to enhance both performance and efficiency. Our model significantly reduces complexity, operating with just 1669 parameters and achieving an inference time of 0.3 ms per batch, making it highly suitable for resource-constrained automotive environments. Evaluations in the HCRL Car-Hacking dataset demonstrate exceptional capabilities, attaining perfect scores (Recall, Precision, F1 Score of 100%, and FNR of 0%) under multiple attack types, including DoS, Fuzzing, Gear Spoofing, and RPM Spoofing. Comparative analysis on the CICIoV2024 dataset further underscores its superiority over traditional machine learning models, achieving perfect detection metrics. We furthermore integrate Explainable AI (XAI) techniques to ensure transparency in the model's decisions. The VAE compresses the original feature space into a latent space, on which the distilled model is trained. SHAP(SHapley Additive exPlanations) values provide insights into the importance of each latent dimension, mapped back to original features for intuitive understanding. Our paper advances the field by integrating state-of-the-art techniques, addressing critical challenges in the deployment of efficient, trustworthy, and reliable IDSes for autonomous vehicles, ensuring enhanced protection against emerging cyber threats.

Published
2024

11. Less is More: Towards Sustainability-Aware Persuasive Explanations in Recommender Systems

Author

Tran, Thi Ngoc Trang, Erdeniz, Seda Polat, Felfernig, Alexander, Lubos, Sebastian, El-Mansi, Merfat, and Le, Viet-Man

Subjects
Computer Science - Information Retrieval
Abstract

Recommender systems play an important role in supporting the achievement of the United Nations sustainable development goals (SDGs). In recommender systems, explanations can support different goals, such as increasing a user's trust in a recommendation, persuading a user to purchase specific items, or increasing the understanding of the reasons behind a recommendation. In this paper, we discuss the concept of "sustainability-aware persuasive explanations" which we regard as a major concept to support the achievement of the mentioned SDGs. Such explanations are orthogonal to most existing explanation approaches since they focus on a "less is more" principle, which per se is not included in existing e-commerce platforms. Based on a user study in three item domains, we analyze the potential impacts of sustainability-aware persuasive explanations. The study results are promising regarding user acceptance and the potential impacts of such explanations., Comment: The paper was accepted for publication and will be presented in the LBR track of RecSys 2024, 14.- 18. October 2024, Bari, Italy

Published
2024
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12. SPRING: an effective and reliable framework for image reconstruction in single-particle Coherent Diffraction Imaging

Author

Colombo, Alessandro, Sauppe, Mario, Haddad, Andre Al, Ayyer, Kartik, Babayan, Morsal, Dagar, Ritika, Fennel, Thomas, Hecht, Linos, Knopp, Gregor, Kolatzki, Katharina, Langbehn, Bruno, Maia, Filipe R. N. C., Mall, Abhishek, Mazumder, Parichita, Polat, Ihsan Caner, Schäfer-Zimmermann, Julian C., Schnorr, Kirsten, Schubert, Marie Louise, Sehati, Arezu, Sellberg, Jonas A., Shen, Zhou, Sun, Zhibin, Svensson, Pamela, Tümmler, Paul, Ussling, Carl Frederic, Veteläinen, Onni, Wächter, Simon, Walsh, Noelle, Weitnauer, Alex V., You, Tong, Zuod, Maha, Bostedt, Christoph, Galli, Davide Emilio, Patanen, Minna, and Rupp, Daniela

Subjects
Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Atomic and Molecular Clusters, Physics - Computational Physics, Physics - Data Analysis, Statistics and Probability
Abstract

Coherent Diffraction Imaging (CDI) is an experimental technique to gain images of isolated structures by recording the light scattered off the sample. In principle, the sample density can be recovered from the scattered light field through a straightforward Fourier Transform operation. However, only the amplitude of the field is recorded, while the phase is lost during the measurement process and has to be retrieved by means of suitable, well-established, phase retrieval algorithms. In this work we present SPRING, an analysis framework tailored on X-ray Free Electron Laser (XFEL) diffraction data that implements the Memetic Phase Retrieval method to mitigate the shortcomings of conventional algorithms. We benchmark the approach on experimental data acquired in two experimental campaigns at SwissFEL and European XFEL. Imaging results on isolated nanostructures reveal unprecedented stability and resilience of the algorithm's behavior on the input parameters, as well as the capability of identifying the solution in conditions hardly treatable so far with conventional methods. A user-friendly implementation of SPRING is released as open-source software, aiming at being a reference tool for the coherent diffraction imaging community at XFEL and synchrotron facilities., Comment: 30 pages, 13 figures. Software released as open source. Authors list updated. Using revtex document class. New section on comparison with conventional approaches. New supplemental material

Published
2024

13. Leveraging LLMs for the Quality Assurance of Software Requirements

Author

Lubos, Sebastian, Felfernig, Alexander, Tran, Thi Ngoc Trang, Garber, Damian, Mansi, Merfat El, Erdeniz, Seda Polat, and Le, Viet-Man

Subjects
Computer Science - Software Engineering
Abstract

Successful software projects depend on the quality of software requirements. Creating high-quality requirements is a crucial step toward successful software development. Effective support in this area can significantly reduce development costs and enhance the software quality. In this paper, we introduce and assess the capabilities of a Large Language Model (LLM) to evaluate the quality characteristics of software requirements according to the ISO 29148 standard. We aim to further improve the support of stakeholders engaged in requirements engineering (RE). We show how an LLM can assess requirements, explain its decision-making process, and examine its capacity to propose improved versions of requirements. We conduct a study with software engineers to validate our approach. Our findings emphasize the potential of LLMs for improving the quality of software requirements., Comment: Accepted for publication at the RE@Next! track of RE 2024

Published
2024
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14. The Relationship between Inclusive Leadership and Innovative Work Behavior: The Mediating Role of Inclusive Climate and Emotional Commitment

Author

Çaglar Çelik, Soner Polat, and Emre Esen

Abstract

This study explores how inclusive leadership shapes innovative work behavior, focusing on the intermediary effects of emotional commitment and an inclusive climate in Turkish public schools. Drawing on data from 364 teachers in Kocaeli, the research utilized a range of scales to assess aspects like inclusive leadership, emotional commitment, inclusive climate, and innovative work behavior. The analysis was conducted using descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show a positive impact of inclusive leadership on innovative work behavior. However, the impact is mediated through the presence of an inclusive climate and high levels of emotional commitment. The findings suggest that while inclusive leadership is necessary for fostering innovation, it is the combination of an emotionally supportive and inclusively diverse environment that truly enhances innovative behaviors among teachers. This comprehensive approach not only supports the innovative capacity of individuals but also contributes to a more dynamic and creative educational atmosphere. This study highlights the importance of adopting a holistic leadership strategy in educational institutions. It underscores the need for school administrators to not only practice inclusive leadership but also actively cultivate an environment that values diversity and fosters emotional commitment. By doing so, schools can become fertile grounds for innovation, benefiting educators and students alike. The research provides valuable insights into the mechanisms through which leadership can influence organizational behavior and offers a framework for fostering innovation in educational settings.

Published
2024

15. Teachers with a Refugee Background Work as Educators in Germany

Author

Yusuf Özdemir and Seyat Polat

Abstract

This study's focus is to determine refugee teachers' views regarding their ability to work as teachers in Germany, their initiatives, and the challenges they face. In this context, the study was conducted based on qualitative research methodology. In order to collect data a total of 265 teachers residing in the 16 states of Germany were reached. Upon examining the results, it is observed that the majority of participants express a desire to work as teachers in Germany, while only a few have actually obtained the opportunity to work as teachers in Germany. More than half of the participants who are currently working as teachers reside in the North Rhine-Westphalia state. When analyzing the results, it becomes evident that a significant portion of the participants are strongly inclined to pursue a teaching career in Germany. However, the data reveals that the actual attainment of employment as teacher in Germany remains relatively low among the respondents. Furthermore, it is noteworthy that a majority of the teachers currently employed in the profession are concentrated in the North Rhine-Westphalia state.

Published
2024

16. Integrating Technology in EFL: A Study on TPACK and Self-Efficacy among Turkish Educators

Author

Rabia Dinçer, Mustafa Polat, and Nazmi Dinçer

Abstract

This study explores the intersection of Technological Pedagogical Content Knowledge (TPACK) and Technology Integration Self-Efficacy (TISE) among EFL instructors in Turkey. Utilizing a quantitative approach, 101 EFL instructors were across various Turkish universities, employing the TPACK-EFL assessment and the TISE questionnaire. Our findings reveal a robust foundation in EFL educators' TPACK and a general confidence in technology integration. Obviously, a predictive relationship between TPACK levels and TISE beliefs was observed, indicating that educators' selfefficacy in technology integration significantly influences their TPACK proficiency. This research contributes to the understanding of EFL educators' capabilities in integrating technology into higher education and highlights areas for enhancing technology confidence and proficiency. The implications of these findings extend to the design of instructor training programs and curriculum development in EFL settings, advocating for an increased focus on technology integration competencies.

Published
2024

17. An Analysis of the Effect of Using Collaborative Story Maps on Story Writing Skills

Author

I?lhan Polat and Hakan Dedeoglu

Abstract

The aim of the study is to investigate the effect of story writing on the story writing skills of primary school students with the collaborative story map method. This quantitative study has a quasi-experimental design with a pretest-posttest comparison group. The study group consists of 131 primary school 2nd-grade students, 60 boys and 71 girls. There are two experimental groups and one control group in the study. The study lasted 12 weeks and 2 class hours per week. In the collaborative story map writing group, story writing was practiced with a collaborative story map. In the individual story map writing group, story writing work according to the individual story map. In the control group, a free story writing activity was conducted. The data were collected through the Story Grammar Elements Rating Scale. T-Test and ANOVA were used to analyze the data. In conclusion, writing stories with primary school students in the method of collaborative mapping and individual story mapping improves students' story writing skills. However, there is no difference between preparing a story map collaboratively or individually in terms of story writing skills.

Published
2024

18. Educational Technology in Inclusive Classrooms: Assessing Teacher Awareness and Needs

Author

Elif Polat, Simge Cepdibi Sibiç, Nazli Ceren Cirit-Isikligil, Sinan Hopcan, and Yunus Emre Bastug

Abstract

The aim of this research is to reveal the awareness of teachers working in inclusion environments and their use of educational technology. Specifically, in this mixed methods study, a needs analysis was conducted to determine the knowledge levels of teachers about inclusive education, their awareness and use of educational technologies, and what kind of support they need. Data were collected through a questionnaire with 133 teachers and focus group discussions with 5 groups of 30 teachers. Based on the analysis of quantitative data using descriptive analysis and qualitative data employing the constant comparison method, the findings showed that teachers' knowledge of special education needs (SEN) students is insufficient and they need support at this point. In addition, the qualitative data analysis unveiled social, academic, and environmental positive outputs of inclusive education alongside the identification of the psychological, academic, and environmental challenges of inclusive education. The findings are expected to benefit the literature, the field of inclusive education, and policymakers. [Note: The page range (115-131) and year shown on the PDF is incorrect. The correct page range is 116-131. The correct year is 2024.]

Published
2024

19. A Bibliometric Analysis of Research on ChatGPT in Education

Author

Hamza Polat, Arif Cem Topuz, Mine Yildiz, Elif Taslibeyaz, and Engin Kursun

Abstract

ChatGPT has become a prominent tool for fostering personalized and interactive learning with the advancements in AI technology. This study analyzes 212 academic research articles indexed in the Scopus database as of July 2023. It maps the trajectory of educational studies on ChatGPT, identifying primary themes, influential authors, and contributing institutions. By employing bibliometric indicators and network analysis, the study explores collaboration patterns, citation trends, and the evolution of research interests. The findings show the exponential growth of interest in leveraging ChatGPT for educational purposes and provide insights into the specific educational domains and contexts that have garnered the most attention. Furthermore, the study reveals the collaborative dynamics and intellectual foundations shaping the field by examining co-authorship and citation networks. This bibliometric analysis contributes to a comprehensive understanding of the current state of ChatGPT research in education, offering researchers and practitioners valuable insights into evolving trends and potential future directions for this innovative aspect of AI and learning.

Published
2024

20. The Effect of 8-Week Apparatus Technique Training on Hand and Foot Simple, Selective and Discrimination Reactions of Female Athletes

Author

Sezen Çimen Polat, Musab Çagin, and Halil Sarol

Abstract

Movement training is thought to be very important in terms of learning both basic motor skills and new techniques in sports branches. Rhythmic gymnastics apparatus technique applications, which is a widely used method in movement training; it aims to display predetermined choreography in harmony with various tools. In this context, the aim of this experimental study is to examine the effect of rhythmic gymnastics equipment technique, which is predicted to be a good tool to improve reaction performance for movement educators and athletes, on various hand and foot reaction parameters. A total of 42 female athletes, including 22 experimental group members who had not previously practiced rhythmic gymnastics and 20 control group members, were included in the study on voluntary basis. The reaction performances of the athletes were determined using the ÇAGIN Hand and Foot Reaction Test. Data were analyzed using the SPSS 26.0 package program using Repeated Measures-ANOVA and descriptive statistics. In the pretest-posttest results of the reaction time of the individuals, it was determined that the hand simple and discriminative reaction time and foot discriminative reaction time of the experimental group decreased significantly (p<0.05). In the pretest-posttest results regarding the individuals' correct reaction rates, it was determined that only the foot selective reaction correct rate of the experimental group increased significantly (p<0.05). As a result of the study, it was observed that the application of the apparatus technique generally positively affected the athletes' hand and foot reaction times and the accuracy of the reactions.

Published
2024

21. Voices of Primary School Teachers about the Intelligent Material System Developed for Inclusive Education

Author

Elif Polat, Yunus Emre Bastug, Sinan Hopcan, Simge Cepdibi Sibiç, and Nazli Ceren Isikligil

Abstract

This study investigates the primary school teachers' perceptions towards the Intelligent Material System (IMS), which was developed to enhance the quality of inclusive environments and support the academic skills of students with Special Educational Needs (SEN). Within this scope, IMS training was conducted with 84 classroom teachers who worked at primary schools in Istanbul. Following the training, an open-ended questionnaire and two focus group interviews were used to collect data. The findings revealed that IMS has the potential to support the students with SEN academically, as it provides motivating and rich content, has a user-friendly interface and a desired level of accessibility despite the system's limitations and the need for improvements noted by the participants.

Published
2024

22. Sustaining Undergraduate Students' Metacognitive Regulatory Actions during Online Flipped Programming Course

Author

Gamze Türkmen, Sinan Hopcan, and Elif Polat

Abstract

This research explores how metacognitive strategies influence the metacognitive awareness of undergraduate students enrolled in an online flipped programming course. It specifically focuses on regulatory actions crucial for success in programming instruction and distance education settings. The primary objective is to contribute to the existing literature by investigating the implementation of online flipped programming courses that integrate metacognitive-oriented approaches to support students' metacognitive regulatory actions. The study employed an explanatory sequential mixed methods design. A total of 29 university students enrolled in programming courses participated in the study, engaging with instructional videos provided before each 10-week lesson. They were administered the Metacognitive Awareness Scale and supplementary forms designed to assess their metacognitive awareness and regulatory actions. A detailed coding scheme was developed to analyze students' metacognitive regulation activities during programming lessons. The study also evaluated the impact of supportive activities on students' metacognitive awareness. While no statistically significant difference was found in the students' metacognitive awareness through quantitative analysis, qualitative data revealed that activities supporting metacognition significantly enhanced students' comprehension of the programming content.

Published
2024

23. Unethical Behaviors of School Principals According to Teachers' Views: Causes and Recommendations for Prevention

Author

Yaser Arslan, Soner Polat, Meriç Gürler, and I?Brahim Bulut

Abstract

This study aims to reveal school principals' unethical behaviours based on teachers' perceptions within schools, to reveal the causes for these behaviours and recommendations to prevent them. An interpretive qualitative approach was applied. Data were gathered via face-to-face interviews conducted with 17 public school teachers in Kocaeli Province of Turkey. The data was examined through content analysis technique. The participants listed the unethical behaviours of school principals in seven different themes as discrimination, favouritism, violation of the rules of courtesy, misconduct, mobbing and pressure, neglect of duty, and other behaviours. The causes of unethical behaviours of school principals were stated as the factors related to administrative qualifications, personal factors, institutional factors, the factors related to teachers, and environmental factors. To prevent unethical behaviours of school principals, the participants suggested some training activities as post-graduate education in educational administration and psychological guidance to school principals. They also suggested some activities to increase the professional development levels and human relations competences of school principals. It was also recommended to make some legal regulations regarding the appointment, assignment issues, reward, rotation, and supervision of administrators. In addition to these suggestions, it was recommended to organize social activities for preventing unethical behaviours of school principals.

Published
2024

24. The Relationship between Inclusive Leadership and Teachers' Perceptions of Organizational Trust: A Cross-Sectional Survey in Türkiye

Author

Murat Polat and Kübra Turhaner

Abstract

Significant scholarly attention has been devoted to investigating the relationship between school leadership and trust, with recent emphasis shifting towards inclusive leadership. This study specifically explores the connection between inclusive leadership and the level of trust within educational organizations. The main objective is to evaluate how administrators' Inclusive Leadership behaviors in public schools impact teachers' perceptions of Organizational Trust. To achieve this, the researchers engaged with teachers from various public schools in a city located in East Anatolia, Türkiye, employing a cross-sectional survey approach. A total of 273 teachers from diverse educational levels, including preschool, primary, secondary, and upper-secondary school, participated in the study, with a gender distribution of 143 females and 130 males. Data were collected through the Inclusive Leadership scale and Organizational Trust scale, and data analysis utilized regression analysis techniques. The findings reveal a robust and positive correlation between inclusive leadership practices in educational settings and the trust teachers place in their institutions. This implies that the level of inclusivity in leadership significantly contributes to an optimistic shift of approximately 68% in educators' perspectives on institutional trust. Additionally, it is noteworthy that male teachers report significantly higher levels of organizational trust compared to their female colleagues. In summary, this research highlights the importance of considering the educational context when examining the correlation between organizational trust and inclusive leadership in educational institutions.

Published
2024

25. Readiness, Resilience, and Engagement: Analyzing the Core Building Blocks of Online Education

Author

Mustafa Polat

Abstract

Contemporary educational research has increasingly highlighted the necessity and significance of online education and its effects on student engagement and academic success. However, it's noteworthy that there is still a gap in the growing literature regarding the student-related factors that influence individuals' engagement and achievement in online education. This study sought to investigate the effects of students' online learning readiness in online learning engagement with the mediating role of academic resilience in this relationship. A cross-sectional survey design was employed based on the data from a total of 3550 undergraduates studying at state universities in six provinces across the eastern, central, and western regions of Türkiye. Structural equation modeling was conducted to estimate the complex relationships proposed in the model through AMOS 26. The findings demonstrated that students' online learning readiness has a moderate but statistically significant direct effect on engagement in online learning, as well as had a significant and moderate effect on academic resilience. Furthermore, the results indicated that academic resilience plays a crucial role as a significant mediator in the relationship between students' online learning readiness and online learning engagement. The current study also confirmed the conceptual model built on the variables that have notable impacts on students' academic achievement. This research, one of the first in its field, furnishes empirical evidence on a conceptualized set of relationships and offers insights for policy makers, curriculum developers and practitioners to consider the significant student-related factors in terms of design, development, and delivery of online courses.

Published
2024
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26. Assessment of the Knowledge, Emotions and Behaviours of Secondary School Students towards the Environment and Recycling in Southeastern Türkiye

Author

Meryem Betül Polat, Izzettin Hakan Karaçizmeli, Ayse Dilek Atasoy, and Mehmet Irfan Yesilnacar

Abstract

Improving the scope of environmental education given in schools and establishing environmental awareness among students are the most important steps to be taken to transfer this awareness to the next generations. The aim of this study is to examine the knowledge, emotions and behaviours of secondary school students ranging from 11 to 13 for environmental health and environmental protection. The study was carried out in the district of Karaköprü, a metropolitan settlement in Sanliurfa for the 2020-2021 academic year, regarding environmental health and environmental protection, which has decreased with the effect of the pandemic. In this study, a questionnaire was applied to students and their attitudes were evaluated according to a 5-point Likert scale. The attitudes of the students were detailed on the basis of 'gender' and 'mother education level' factors. It was found that the male students in the study group had more knowledge about environmental health and protection compared to the female students. However, no relationship was detected between students' environmental awareness and their mothers' educational levels.

Published
2024
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27. Diagnostic and Prognostic Value of SCUBE-1 in COVID-19 Patients

Author

Ozer, Vildan, Gonenc Cekic, Ozgen, Bulbul, Ozlem, Aydın, Davut, Bulut, Eser, Aksoy, Firdevs, Pehlivanlar Kucuk, Mehtap, Karahan, Suleyman Caner, Sozen, Ebru Emel, Ozkaya, Esra, Kosucu, Polat, Karaca, Yunus, and Turedi, Suleyman

Subjects
Emergency Departments, COVID 19, SCUBE-1, Diagnosis, Hospitalization, patient discharge
Abstract

Introduction: The workload of physicians increased due to the number of patients presenting with suspicion of coronavirus 2019 (COVID-19) and the prolonged wait times in the emergency department during the COVID-19 pandemic. Signal peptide-CUB-EGF domain-containing protein 1 (SCUBE-1) is a protein present in platelets and endothelial cells; it is activated by inflammation from COVID-19 and may be associated with COVID-19’s known thrombotic risk. We aimed to determine whether SCUBE-1 levels are diagnostically correlated in suspected COVID-19 patients, and whether SCUBE-1 correlated with severity of disease and, therefore, might be useful to guide hospitalization/discharge decisions.Methods: The suspected COVID-19 patients cared for at tertiary healthcare institutions for one year between May 2021–May 2022 were examined in this study. The subjects were both suspected COVID-19 patients not ultimately found to have COVID-19 and those who were diagnosed with COVID-19. By modifying the disease severity scoring systems present in COVID-19 guidelines in 2021, the COVID-19-positive patient group was classified as mild, moderate, severe, and critical, and compared using the SCUBE-1 levels. Moreover, SCUBE-1 levels were compared between the COVID-19 positive group and the COVID-19 negative group.Results: A total of 507 patients were considered for the present study. After excluding 175 patients for incomplete data and alternate comorbid organ failure. we report on 332 patients (65.5%). Of these 332 patients, 80 (24.0%) were COVID-19 negative, and 252 (76.0%) were COVID-19 positive. Of 252 (100%) patients diagnosed with COVID-19, 74 (29.4%) were classified as mild, 95 (37.7%) moderate, 45 (17.8%) severe, and 38 (15.1%) critical. The SCUBE-1 levels were statistically different between COVID-19 positive (8.48 ± 7.42 nanograms per milliliter [ng/mL]) and COVID-19 negative (1.86 ± 0.92 ng/mL) patients (P < 0.001). In the COVID-19 positive group, SCUBE-1 levels increased with disease severity (mild = 3.20 ± 1.65 ng/mL, moderate = 4.78 ± 2.26 ng/mL, severe = 13.68 ± 3.95 ng/mL, and critical = 21.87 ± 5.39 ng/mL) (P < 0.001). The initial SCUBE-1 levels of discharged patients were significantly lower than those requiring hospitalization (discharged = 2.89 ng/mL [0.55–8.60 ng/mL]; ward admitted = 7.13 ng/mL [1.38–21.29 ng/mL], and ICU admitted = 21.19 ng/mL [10.58–37.86 ng/mL]) (P < 0.001).Conclusion: The SCUBE-1 levels were found to be differentiated between patients with and without COVID-19 and to be correlated with the severity of illness.

Published
2024

28. The Origin of Photoplasticity in ZnS

Author

Genlik, Sevim Polat, Myers, Roberto C., and Ghazisaeidi, Maryam

Subjects
Condensed Matter - Materials Science
Abstract

ZnS is a brittle material but shows extraordinary plasticity during mechanical tests performed in complete darkness. This phenomenon is known as the photoplastic effect, whose underlying mechanisms have long been unclear. We study the impact of light, via photoexcited charge carriers, on the dislocation core structure and mobility using first-principles calculations. We calculate the core structure and the charge-dependent Peierls barriers of the glide set of Shockley partial dislocations in ZnS. Our findings reveal that locally charged dislocations capture excess carriers in the system, leading to core reconstructions that alter the Peierls barrier, resulting in higher barriers and lower mobility for these dislocations. This altered and asymmetric mobility, depending on dislocation character (edge or mixed) and local stoichiometry (Zn or S rich), is responsible for the brittle behavior of ZnS under light exposure and will be reversed in complete darkness.

Published
2024

29. Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

Author

Aamir, M., Adamov, G., Adams, T., Adloff, C., Afanasiev, S., Agrawal, C., Ahmad, A., Ahmed, H. A., Akbar, S., Akchurin, N., Akgul, B., Akgun, B., Akpinar, R. O., Aktas, E., Kadhim, A. Al, Alexakhin, V., Alimena, J., Alison, J., Alpana, A., Alshehri, W., Dominguez, P. Alvarez, Alyari, M., Amendola, C., Amir, R. B., Andersen, S. B., Andreev, Y., Antoszczuk, P. D., Aras, U., Ardila, L., Aspell, P., Avila, M., Awad, I., Aydilek, O., Azimi, Z., Pretel, A. Aznar, Bach, O. A., Bainbridge, R., Bakshi, A., Bam, B., Banerjee, S., Barney, D., Bayraktar, O., Beaudette, F., Beaujean, F., Becheva, E., Behera, P. K., Belloni, A., Bergauer, T., Besancon, M., Bylund, O. Bessidskaia, Bhatt, L., Bhattacharya, S., Bhowmil, D., Blekman, F., Blinov, P., Bloch, P., Bodek, A., Boger, a., Bonnemaison, A., Bouyjou, F., Brennan, L., Brondolin, E., Brusamolino, A., Bubanja, I., Perraguin, A. Buchot, Bunin, P., Misura, A. Burazin, Butler-nalin, A., Cakir, A., Callier, S., Campbell, S., Candemir, Y. B., Canderan, K., Cankocak, K., Cappati, A., Caregari, S., Carron, S., Carty, C., Cauchois, A., Ceard, L., Cerci, S., Chang, P. J., Chatterjee, R. M., Chatterjee, S., Chattopadhyay, P., Chatzistavrou, T., Chaudhary, M. S., Chen, J. A., Chen, J., Chen, Y., Cheng, K., Cheung, H., Chhikara, J., Chiron, A., Chiusi, M., Chokheli, D., Chudasama, R., Clement, E., Mendez, S. Coco, Coko, D., Coskun, K., Couderc, F., Crossman, B., Cui, Z., Cuisset, T., Cummings, G., Curtis, E. M., D'Alfonso, M., Döhler-Ball, J., Dadazhanova, O., Damgov, J., Das, I., Gupta, S. Das, Dauncey, P., Mendes, A. David Tinoco, Davies, G., Davignon, O., de Barbaro, P., De La Taille, C., De Silva, M., De Wit, A., Debbins, P., Defranchis, M. M., Delagnes, E., Devouge, P., Di Guglielmo, G., Diehl, L., Dilsiz, K., Dincer, G. G., Dittmann, J., Dragicevic, M., Du, D., Dubinchik, B., Dugad, S., Dulucq, F., Dumanoglu, I., Duran, B., Dutta, S., Dutta, V., Dychkant, A., Dünser, M., Edberg, T., Ehle, I. T., Berni, A. El, Elias, F., Eno, S. C., Erdogan, E. N., Erkmen, B., Ershov, Y., Ertorer, E. Y., Extier, S., Eychenne, L., Fedar, Y. E., Fedi, G., De Almeida, J. P. Figueiredo De Sá Sousa, Alves, B. A. Fontana Santos, Frahm, E., Francis, K., Freeman, J., French, T., Gaede, F., Gandhi, P. K., Ganjour, S., Garcia-Bellido, A., Gastaldi, F., Gazi, L., Gecse, Z., Gerwig, H., Gevin, O., Ghosh, S., Gill, K., Gingu, C., Gleyzer, S., Godinovic, N., Goettlicher, P., Goff, R., Gok, M., Golunov, A., Gonultas, B., Martínez, J. D. González, Gorbounov, N., Gouskos, L., Gray, A., Gray, L., Grieco, C., Groenroos, S., Groner, D., Gruber, A., Grummer, A., Grönroos, S., Guerrero, D., Guilloux, F., Guler, Y., Gungordu, A. D., Guo, J., Guo, K., Guler, E. Gurpinar, Gutti, H. K., Guvenli, A. A., Gülmez, E., Hacisahinoglu, B., Halkin, Y., Machado, G. Hamilton Ilha, Hare, H. S., Hatakeyama, K., Heering, A. H., Hegde, V., Heintz, U., Hinton, N., Hinzmann, A., Hirschauer, J., Hitlin, D., Hoff, J., Hos, İ., Hou, B., Hou, X., Howard, A., Howe, C., Hsieh, H., Hsu, T., Hua, H., Hummer, F., Imran, M., Incandela, J., Iren, E., Isildak, B., Jackson, P. S., Jackson, W. J., Jain, S., Jana, P., Jaroslavceva, J., Jena, S., Jige, A., Jordano, P. P., Joshi, U., Kaadze, K., Kachanov, V., Kafizov, A., Kalipoliti, L., Tharayil, A. Kallil, Kaluzinska, O., Kamble, S., Kaminskiy, A., Kanemura, M., Kanso, H., Kao, Y., Kapic, A., Kapsiak, C., Karjavine, V., Karmakar, S., Karneyeu, A., Kaya, M., Topaksu, A. Kayis, Kaynak, B., Kazhykarim, Y., Khan, F. A., Khudiakov, A., Kieseler, J., Kim, R. S., Klijnsma, T., Kloiber, E. G., Klute, M., Kocak, Z., Kodali, K. R., Koetz, K., Kolberg, T., Kolcu, O. B., Komaragiri, J. R., Komm, M., Kopsalis, I., Krause, H. A., Krawczyk, M. A., Vinayakam, T. R. Krishnaswamy, Kristiansen, K., Kristic, A., Krohn, M., Kronheim, B., Krüger, K., Kudtarkar, C., Kulis, S., Kumar, M., Kumar, N., Kumar, S., Verma, R. Kumar, Kunori, S., Kunts, A., Kuo, C., Kurenkov, A., Kuryatkov, V., Kyre, S., Ladenson, J., Lamichhane, K., Landsberg, G., Langford, J., Laudrain, A., Laughlin, R., Lawhorn, J., Dortz, O. Le, Lee, S. W., Lektauers, A., Lelas, D., Leon, M., Levchuk, L., Li, A. J., Li, J., Li, Y., Liang, Z., Liao, H., Lin, K., Lin, W., Lin, Z., Lincoln, D., Linssen, L., Litomin, A., Liu, G., Liu, Y., Lobanov, A., Lohezic, V., Loiseau, T., Lu, C., Lu, R., Lu, S. Y., Lukens, P., Mackenzie, M., Magnan, A., Magniette, F., Mahjoub, A., Mahon, D., Majumder, G., Makarenko, V., Malakhov, A., Malgeri, L., Mallios, S., Mandloi, C., Mankel, A., Mannelli, M., Mans, J., Mantilla, C., Martinez, G., Massa, C., Masterson, P., Matthewman, M., Matveev, V., Mayekar, S., Mazlov, I., Mehta, A., Mestvirishvili, A., Miao, Y., Milella, G., Mirza, I. R., Mitra, P., Moccia, S., Mohanty, G. B., Monti, F., Moortgat, F., Murthy, S., Music, J., Musienko, Y., Nabili, S., Nelson, J. W., Nema, A., Neutelings, I., Niedziela, J., Nikitenko, A., Noonan, D., Noy, M., Nurdan, K., Obraztsov, S., Ochando, C., Ogul, H., Olsson, J., Onel, Y., Ozkorucuklu, S., Paganis, E., Palit, P., Pan, R., Pandey, S., Pantaleo, F., Papageorgakis, C., Paramesvaran, S., Paranjpe, M. M., Parolia, S., Parsons, A. G., Parygin, P., Pastika, J., Paulini, M., Paus, C., Castillo, K. Peñaló, Pedro, K., Pekic, V., Peltola, T., Peng, B., Perego, A., Perini, D., Petrilli, A., Pham, H., Podem, S. K., Popov, V., Portales, L., Potok, O., Pradeep, P. B., Pramanik, R., Prosper, H., Prvan, M., Qasim, S. R., Qu, H., Quast, T., Trivio, A. Quiroga, Rabour, L., Raicevic, N., Rao, M. A., Rapacz, K., Redjeb, W., Reinecke, M., Revering, M., Roberts, A., Rohlf, J., Rosado, P., Rose, A., Rothman, S., Rout, P. K., Rovere, M., Roy, A., Rubinov, P., Rumerio, P., Rusack, R., Rygaard, L., Ryjov, V., Sadivnycha, S., Sahin, M. Ö., Sakarya, U., Salerno, R., Saradhy, R., Saraf, M., Sarbandi, K., Sarkisla, M. A., Satyshev, I., Saud, N., Sauvan, J., Schindler, G., Schmidt, A., Schmidt, I., Schmitt, M. H., Sculac, A., Sculac, T., Sedelnikov, A., Seez, C., Sefkow, F., Selivanova, D., Selvaggi, M., Sergeychik, V., Sert, H., Shahid, M., Sharma, P., Sharma, R., Sharma, S., Shelake, M., Shenai, A., Shih, C. W., Shinde, R., Shmygol, D., Shukla, R., Sicking, E., Silva, P., Simsek, C., Simsek, E., Sirasva, B. K., Sirois, Y., Song, S., Song, Y., Soudais, G., Sriram, S., Jacques, R. R. St, Leiton, A. G. Stahl, Steen, A., Stein, J., Strait, J., Strobbe, N., Su, X., Sukhov, E., Suleiman, A., Cerci, D. Sunar, Suryadevara, P., Swain, K., Syal, C., Tali, B., Tanay, K., Tang, W., Tanvir, A., Tao, J., Tarabini, A., Tatli, T., Taylor, R., Taysi, Z. C., Teafoe, G., Tee, C. Z., Terrill, W., Thienpont, D., Thomas, P. E., Thomas, R., Titov, M., Todd, C., Todd, E., Toms, M., Tosun, A., Troska, J., Tsai, L., Tsamalaidze, Z., Tsionou, D., Tsipolitis, G., Tsirigoti, M., Tu, R., Polat, S. N. Tural, Undleeb, S., Usai, E., Uslan, E., Ustinov, V., Uzunian, A., Vernazza, E., Viahin, O., Viazlo, O., Vichoudis, P., Vijay, A., Virdee, T., Voirin, E., Vojinovic, M., Vámi, T. Á., Wade, A., Walter, D., Wang, C., Wang, F., Wang, J., Wang, K., Wang, X., Wang, Y., Wang, Z., Wanlin, E., Wayne, M., Wetzel, J., Whitbeck, A., Wickwire, R., Wilmot, D., Wilson, J., Wu, H., Xiao, M., Yang, J., Yazici, B., Ye, Y., Yerli, B., Yetkin, T., Yi, R., Yohay, R., Yu, T., Yuan, C., Yuan, X., Yuksel, O., YushmanoV, I., Yusuff, I., Zabi, A., Zareckis, D., Zehetner, P., Zghiche, A., Zhang, C., Zhang, D., Zhang, H., Zhang, J., Zhang, Z., Zhao, X., Zhong, J., Zhou, Y., and Zorbilmez, Ç.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract

A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated.

Published
2024
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30. Formulas of special polynomials involving Bernoulli polynomials derived from matrix equations and Laplace transform

Author

Polat, Ezgi and Simsek, Yilmaz

Subjects
Mathematics - General Mathematics, 05A15, 11B68, 44A10, 47L05
Abstract

The main purpose and motivation of this article is to create a linear transformation on the polynomial ring of rational numbers. A matrix representation of this linear transformation based on standard fundamentals will be given. For some special cases of this matrix, matrix equations including inverse matrices, the Bell polynomials will be given. With the help of these equations, new formulas containing different polynomials, especially the Bernoulli polynomials, will be given. Finally, by applying the Laplace transform to the generating function for the Bernoulli polynomials, we derive some novel formulas involving the Hurwitz zeta function and infinite series., Comment: 17 pages

Published
2024

31. Model-Driven Engineering for Quantum Programming: A Case Study on Ground State Energy Calculation

Author

Polat, Furkan, Tuncer, Hasan, Moin, Armin, and Challenger, Moharram

Subjects
Quantum Physics, Computer Science - Programming Languages, Computer Science - Software Engineering
Abstract

This study introduces a novel framework that brings together two main Quantum Programming methodologies, gate-based Quantum Computing and Quantum Annealing, by applying the Model-Driven Engineering principles. This aims to enhance the adaptability, design and scalability of quantum programs, facilitating their design and operation across diverse computing platforms. A notable achievement of this research is the development of a mapping method for programs between gate-based quantum computers and quantum annealers which can lead to the automatic transformation of these programs. Specifically, this method is applied to the Variational Quantum Eigensolver Algorithm and Quantum Anneling Ising Model, targeting ground state solutions. Finding ground-state solutions is crucial for a wide range of scientific applications, ranging from simulating chemistry lab experiments to medical applications, such as vaccine development. The success of this application demonstrates Model-Driven Engineering for Quantum Programming frameworks's practical viability and sets a clear path for quantum Computing's broader use in solving intricate problems.

Published
2024
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32. Emergent Ferromagnetism at LaFeO3/SrTiO3 Interface Arising from Strain-induced Spin-State Transition

Author

Zhu, Menglin, Lanier, Joseph, Genlik, Sevim Polat, Flores, Jose G., Barbosa, Victor da Cruz Pinha, Randeria, Mohit, Woodward, Patrick M., Ghazisaeidi, Maryam, Yang, Fengyuan, and Hwang, Jinwoo

Subjects
Condensed Matter - Materials Science
Abstract

Creating new interfacial magnetic states with desired functionalities is attractive for fundamental studies and spintronics applications. The emergence of interfacial magnetic phases demands the fabrication of pristine interfaces and the characterization and understanding of atomic structure as well as electronic, magnetic, and orbital degrees of freedom at the interface. Here, we report a novel interfacial insulating ferromagnetic order in antiferromagnetic LaFeO3 grown on SrTiO3, characterized by a combination of electron microscopy and spectroscopy, magnetometry, and density functional theory. The epitaxial strain drives a spin-state disproportionation in the interfacial layer of LaFeO3, which leads to a checkerboard arrangement of low- and high-spin Fe3+ ions inside smaller and larger FeO6 octahedra, respectively. Ferromagnetism at the interface arises from superexchange interactions between the low- and high-spin Fe3+. The detailed understanding of creation of emergent magnetism illustrates the potential of designing and controlling orbital degrees of freedom at the interface to realize novel phases and functionalities for future spin-electronic applications.

Published
2024

33. Measurement of hadronic cross sections via initial state radiation at BABAR

Author

Polat, Léonard

Subjects
High Energy Physics - Experiment
Abstract

The BABAR experiment participates to the global endeavor for a precise prediction of the anomalous magnetic moment of the muon by evaluating the contribution of hadronic processes to the vacuum polarization. After its last result published in 2009 and 2012, BABAR is preparing a new independent measurement of the $e^+e^- \rightarrow \pi^+\pi^-(\gamma)$ cross section via initial state radiation, with full data statistics and improved uncertainties. A first milestone was reached with the recent study of additional radiations in $e^+e^- \rightarrow \pi^+\pi^-(\gamma)$ and $e^+e^- \rightarrow \mu^+\mu^-(\gamma)$, which uncovered shortcomings of the Phokhara Monte Carlo generator in one-photon rates and angular distributions. This has practically no effect on the previous BABAR measurement, but could explain longstanding discrepancies with other experiments., Comment: 6 pages, 6 figures, Contribution to the 2024 Electroweak session of the 58th Rencontres de Moriond

Published
2024

40. A Multicenter Randomized Double-Blind Vehicle-Controlled Parallel Group Phase 2 Study Evaluating the Efficacy and Safety of GN-037 Cream in Patients with Mild-to-Moderate Plaque Psoriasis

Author

Engin, Burhan, Güler Özden, Müge, Karstarlı Bakay, Özge Sevil, Kartal, Selda Pelin, Zindancı, İlkin, Çınar, Salih Levent, Dursun, Recep, Pehlivan Ulutaş, Gizem, Özkök Akbulut, Tuğba Özkök, Hapa, Fatma Aslı, Bülbül Başkan, Emel, Melikoğlu, Mehmet, Polat Ekinci, Algün, Demirel Öğüt, Neslihan, Hızlı, Pelin, Türkoğlu, Zafer, Küçük, Özlem Su, Topkarcı, Zeynep, Türsen, Ümit, Canpolat, Filiz, Uçgun, Hanife, Yaşar, Şirin, Temiz, Selami Aykut, Doğramacı, Asena Çiğdem, Altuğ, Sedat, Kozlu, Serhat, Ulu, Nadir, and Serdaroğlu, Server

Published
2024
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43. Epidemiological analysis of the victıms wıth crush syndrome in earthquakes of southeastern Turkey

Author

Ozturk, Ilyas, Gungor, Ozkan, Ozturk, Savas, Olmaz, Refik, Keskin, Ayse Jini Gunes, Kocyigit, Ismail, Sipahioglu, Murat Hayri, Dede, Fatih, Ulu, Sena, Turgutalp, Kenan, Torun, Dilek, Sahutoglu, Tuncay, Erdur, Fatih Mehmet, Altunoren, Orcun, Danis, Ramazan, Yildiz, Gursel, Gurel, Ali, Horoz, Mehmet, Kucuksu, Mehmet, Karakose, Suleyman, Yildirim, Tolga, Altiparmak, Mehmet Riza, Ayli, Mehmet Deniz, Tugcu, Murat, Eren, Zehra, Eroglu, Eray, Yavuz, Yasemin Coskun, Akcali, Esra, Sit, Dede, Polat, Mehmet, Yildirim, Saliha, Alagoz, Selma, Bek, Sibel Gokcay, Pembegul, Irem, Karaaslan, Tahsin, Keles, Mustafa, Sari, Funda, Yilmaz, Ustun, Gorgulu, Numan, Sahin, Gulizar, Aydin, Zeki, Yadigar, Serap, Ulutas, Ozkan, Selcuk, Nedim Yilmaz, Ayar, Yavuz, Turgut, Didem, Oto, Ozgur Akin, Koc, Mehmet, Yıldız, Alaattin, Tuglular, Serhan, and Sever, Mehmet Sukru

Published
2024
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