Author: "Yaman, A." - Searchworks@Jio Institute Digital Library Search Results

33,090 results on '"Yaman, A."'

151. The Role of Glyoxal, an Advanced Glycation Product, in Diabetic and Non-diabetic Patients with COVID-19

Author: Nilgün IŞIKSAÇAN, Gülçin ŞAHİNGÖZ ERDAL, Duygu TEKSÖZ, Pınar KASAPOĞLU, Mustafa YAMAN, Halime UĞUR, and Kadriye KART YAŞAR
Subjects: advanced glycation end-products, covid-19, diabetes, glyoxal, length of stay in hospital, Medicine (General), R5-920
Abstract: Objective: The aim of this study was to investigate the effect on coronavirus disease-2019 (COVID-19) of glyoxal (GO), which is a precursor of advanced glycation end-products, in diabetic and non-diabetic patients, treated in hospital for COVID-19 who were of similar age and disease severity with similar comorbidities. Methods: The study included 57 patients. Measurement of GO was made with the high-performance liquid chromatography method. Results: The GO values were found to be higher in the diabetic group than in the non-diabetic group (p=0.001, p
Published: 2024
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152. Can DNA Barcode Study be Done from a Museum Specimen Fixed in a Formaldehyde Solution? A Case of Emys orbicularis (Linnaeus, 1758)

Author: Ulvi Kerem Günay, Batuhan Yaman Yakın, Atakan Pipilos, Emre Keskin, and C. Varol Tok
Subjects: cytochrome oxidase i, european pond turtle, dna barcoding, collection, türkiye, Aquaculture. Fisheries. Angling, SH1-691
Abstract: DNA barcoding, a molecular taxonomy technique, has been increasingly used by herptile taxonomists in recent years. In DNA barcoding studies with museum specimens, there are difficulties in achieving success in specimens that have been exposed to formaldehyde, which is usually used as a fixative, for a long time and intensively. Here we studied the effect of formaldehyde on the application of the DNA barcode method in Emys orbicularis specimens stored in 4% formaldehyde and 70% ethanol solution since 2008 and 2014. Sanger sequence analysis of tissues taken from samples stored in both ethanol and formaldehyde solution successfully yielded sequences of 623 bp. In conclusion, the use of ethanol solutions should be preferred for mid or long-term sample storage, especially in the context of molecular studies. In cases where the use of formaldehyde is unavoidable, it may be advisable to use extremely low concentrations to increase success in molecular research
Published: 2024
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153. Synthesis and Structure of Novel Phenothiazine Derivatives, and Compound Prioritization via In Silico Target Search and Screening for Cytotoxic and Cholinesterase Modulatory Activities in Liver Cancer Cells and In Vivo in Zebrafish

Author: Mehmet Murat Kisla, Murat Yaman, Fikriye Zengin-Karadayi, Busra Korkmaz, Omer Bayazeid, Amrish Kumar, Ravindra Peravali, Damla Gunes, Rafed Said Tiryaki, Emine Gelinci, Gulcin Cakan-Akdogan, Zeynep Ates-Alagoz, and Ozlen Konu
Subjects: Chemistry, QD1-999
Published: 2024
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154. Exploring the Impacts of Financial Failure Risk on Sustainable Growth Policies: Evidence from the BIST Sustainability Index Companies

Author: Fatih Güzyurdu and Serdar Yaman
Subjects: sürdürülebilir büyüme, finansal başarısızlık riski, bist sürdürülebilirlik endeksi, panel veri analizi, sustainable growth, financial failure risk, bist sustainability index, panel data analysis, Finance, HG1-9999
Abstract: This study investigates the impacts of financial failure risk on firms' sustainable growth policies using econometric analysis and aims to identify suitable financial failure models for the sustainable growth policies developing process. The study covers data from 38 non-financial firms listed in the Borsa Istanbul Sustainability Index (XUSRD) for 2010-2022. Sustainable growth is calculated by Higgins's (1977) sustainable growth rate (HSGR), while financial failure risks are assessed through Altman's (1983) Z'-score, Springate (1978) S-score, Taffler (1983) T-score, Fulmer et al. (1984) H-score and Legault (1987) CA-score models. The econometric approach employs a five-stage panel data methodology, including the pre-tests of multi-collinearity, cross-sectional dependency, slope homogeneity, stationarity, autocorrelation, and heteroskedasticity. Panel regression results reveal positive relationships between financial success and sustainable growth. However, the statistical significance of these relationships varies across different financial failure models. The effects of T and H-scores are statistically significant, whereas Z', S, and CA-scores do not exhibit statistically significant effects. Consequently, the findings suggest that T and H-score models should be prioritized in sustainable growth policy development.
Published: 2024
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155. Dermoscopy and In Vivo Confocal Microscopy Findings of Basal Cell Carcinomas in Xeroderma Pigmentosum Patients

Author: Nilay Duman, Göktürk Oraloğlu, Banu Yaman, and Işıl Karaarslan
Subjects: basal cell, carcinoma, confocal microscopy, dermatoscopy, xeroderma pigmentosum, Dermatology, RL1-803
Abstract: Background: Xeroderma pigmentosum (XP) is a rare inherited disorder with a high incidence of malignant tumours. Literature data on dermoscopic and in vivo reflectance confocal microscopy (RCM) findings in patients with XP are very limited. Methods: Dermoscopic findings in 32 biopsy-proven BCCs and RCM findings in 10 biopsy-proven BCCs developed in seven XP patients were reviewed. Results: Of 32 BCCs, 28 were pigmented. On dermoscopy, BCCs exhibited multiple grey-blue globules/dots (81, 3%), short-fine telangiectasias/fine arborising vessels (65, 6%), multiple grey-blue ovoid nests (53, 1%), white structures (white-red structureless areas/shiny white areas/lines/strands) (56, 3%), arborising vessels (37, 5%), brown nests/globules/dots (28, 1%), spoke-wheel structures (9, 4%), leaf-like areas (9, 4%), ulceration (28, 1%), peripheral network (21, 9%), and multiple aggregated yellow-white globules (3, 1%). In 10 lesions in which further imaging with RCM was performed, RCM findings differentiated BCC from other tumours, including primary melanoma. Conclusions: Although the dominancy of pigmented structures may imitate melanoma clinically, dermoscopy is a valuable tool in the early diagnosis of BCCs in patients with XP. For suspicious lesions, RCM can help in differentiating pigmented BCC from primary melanoma.
Published: 2024
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156. Mu‘tezilî Âlim Kâdî Abdülcebbâr Şâfiî miydi?

Author: Bahaddin Karakuş and Ahmet Yaman
Subjects: Islam. Bahai Faith. Theosophy, etc., BP1-610
Abstract: Genel olarak İslam düşüncesini özel olarak da fıkıh düşüncesini derinden etkileyen isimlerden biri de hiç şüphesiz Kâdî Abdülcebbâr’dır (öl. 415/1025). Hayatının çoğu hicrî 4./11. yüzyılda geçen ve Basra Mu’tezilesi’nin Cübbâî’lerden sonra en önemli temsilcisi olan Abdülcebbâr, hem kelam hem de fıkıh usûlü alanındaki eserleriyle sadece Mu’tezilî çevrelerde değil Sünnî muhitlerde de çığır açıcı bir âlim olarak görülmüştür. Birçok Sünnî usûlcünün ortak kanaatine göre İmam Şâfiî’den sonra fıkıh usulü alanındaki en önemli isimlerden biri Abdülcebbâr’dır. Teoloji ve metodoloji alanlarında bu denli etkili olan Kâdî Abdülcebbâr’ın amelî hayatını hangi sistematik çerçevede sürdürdüğü ve öğrenciliği sırasında benimsemiş olduğu Şâfiî mezhebine bağlılığını devam ettirip ettirmediği merak konusu olmuştur. İlgili literatürde Kâdî Abdülcebbâr’ın hayatı boyunca Şâfiî mezhebini benimsediği iddiası çokça dillendirilmiştir. Öyle ki Şâfiî fakihlerin tanıtıldığı tabakât eserlerinde Abdülcebbâr’a bir Şâfiî olarak yer verilmiştir. Günümüze kadar devam eden bu anlayış akademik çalışmalarda da devam eden bir kabul halini almıştır. Acaba gerçek böyle midir? Bu sorunun peşine düşen elinizdeki araştırma, şu adımlarla konuyu incelemiştir: Önce Kâdî Abdülcebbâr’ın fıkıhta takip ettiği yol ile ilgili olarak literatürde zikredilen iddialar sergilenmiş, ardından Abdülcebbâr’ın Mu‘tezile usûlündeki konumu ortaya konmuştur. Mu’tezilî bir âlimin benimsediği iddia edilen mezhebin kurucu imamının yani Şâfiî’nin (öl. 204/820) Mu‘tezile’ye olan mesafesi ve hatta onunla mücadelesine değinildikten sonra Kâdî Abdülcebbâr’ın İmam Şâfiî’nin meşhur usûl görüşlerine muhalif tavırları tespit edilmiştir. Abdülcebbâr’ın usûl görüşlerini İmam Şâfiî’nin usûl görüşleriyle mukayese ederek ilerleyen işbu araştırma, onun amelî sahada Şâfiî mezhebini benimsemiş olduğu iddiasının çok isabetli olmadığı sonucuna ulaşmıştır. Mukayeseyi, Şâfiî usûl düşüncesinin en ayırt edici 6 (altı) meselesi üzerinden yürüten araştırma Abdülcebbâr’ın İmam Şâfiî’ye ve Şâfiî usûlcülere açıkça muhalefet ettiğini göstermektedir. İslam hukuk metodolojisinin en önemli tartışma konuları arasında yer alan bu altı mesele şunlardır: Kur’ân ve Sünnet’in birbirilerini nesh edip edemeyeceği, Peygamber’den nakledilen söz ve fiillerin kabulünün ön şartı olarak bunların Kur’an’a arzı yani delil olabilmesi için Kur’an’ın ilgili düzenlemesiyle uyumlu olup olmadığının tespiti hususu, kıyas sonucu ulaşılan hükmü bir gerekçeye dayanarak terk edip başka bir hüküm koymak demek olan istihsân, çözüm bekleyen yeni meselenin iki veya daha fazla asla/makîsün aleyhe birden benzemesi halinde birçok açıdan en çok benzediği düşünülen aslı dikkate alarak söz konusu yeni meseleye bu aslın hükmünü vermek demek olan şebeh kıyası, mefhûmu’l-muhâlefenin yani bir sözün ters anlamının o sözdeki meselenin tam tersi olup hükmü belirtilmeyen meseleye aktarımı anlamına gelen karşıt kavram kanıtının sahih bir istidlal sayılıp sayılmaması ve emir kipinin hangi anlama geleceği konusu.
Published: 2024
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157. How Do WE Address the Instructors in the Expanding Circle? Perspectives from Turkish EFL Speakers

Author: Ahmet Can Uyar and İsmail YAMAN
Subjects: address forms, turkish english, world englishes, Philology. Linguistics, P1-1091
Abstract: This paper explores the linguistic forms preferred by Turkish speakers of English to address instructors in academic settings. Far from the norm-referenced approach which focuses on labeling non-native-like practices as failures, this study casts light on the underlying mechanisms of the identified address preferences from a variationist point of view. To this end, 140 Turkish speakers of English as a foreign language reported the address forms they preferred on a discourse completion task. Next, ten participants were semi-structurally interviewed to reveal the motives behind their preferences. The results yielded that Turkish language and culture were mirrored on L2 English address practices through code-switching and translating. Along with the finding that the participants repudiated the address norms of the Inner Circle varieties of English, it was discussed that this can be a sign of a developing system of addressing in Turkish English as a variety in the Expanding Circle.
Published: 2024
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158. A tree-based explainable AI model for early detection of Covid-19 using physiological data

Author: Manar Abu Talib, Yaman Afadar, Qassim Nasir, Ali Bou Nassif, Haytham Hijazi, and Ahmad Hasasneh
Subjects: XAI, Interpretability, Physiological data, Classification, Boosting, Deep neural network, Computer applications to medicine. Medical informatics, R858-859.7
Abstract: Abstract With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges. Various studies have emerged utilizing Artificial Intelligence (AI) and Data Science techniques for disease detection. Although COVID-19 cases have declined, there are still cases and deaths around the world. Therefore, early detection of COVID-19 before the onset of symptoms has become crucial in reducing its extensive impact. Fortunately, wearable devices such as smartwatches have proven to be valuable sources of physiological data, including Heart Rate (HR) and sleep quality, enabling the detection of inflammatory diseases. In this study, we utilize an already-existing dataset that includes individual step counts and heart rate data to predict the probability of COVID-19 infection before the onset of symptoms. We train three main model architectures: the Gradient Boosting classifier (GB), CatBoost trees, and TabNet classifier to analyze the physiological data and compare their respective performances. We also add an interpretability layer to our best-performing model, which clarifies prediction results and allows a detailed assessment of effectiveness. Moreover, we created a private dataset by gathering physiological data from Fitbit devices to guarantee reliability and avoid bias. The identical set of models was then applied to this private dataset using the same pre-trained models, and the results were documented. Using the CatBoost tree-based method, our best-performing model outperformed previous studies with an accuracy rate of 85% on the publicly available dataset. Furthermore, this identical pre-trained CatBoost model produced an accuracy of 81% when applied to the private dataset. You will find the source code in the link: https://github.com/OpenUAE-LAB/Covid-19-detection-using-Wearable-data.git .
Published: 2024
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159. Interactions between Cetyltrimethylammonium Bromide Modified Cellulose Nanocrystals and Surfaces: An Ellipsometric Study

Author: Xiaoyu Gong, Md Farhad Ismail, and Yaman Boluk
Subjects: cellulose nanocrystals, cetyltrimethylammonium bromide, ellipsometry, Physics, QC1-999
Abstract: The tailoring of the surface properties of cellulose nanocrystals (CNCs) to meet various requirements in environmental, food, and material areas has always been of great interest. In this study, the surface chemistry of CNCs was noncovalently modified by cetyltrimethylammonium bromide (CTAB), followed by characterizations and an investigation into its application as a coating material for interfacial interaction over various substrates. Due to the CTAB modification, the surface charge of the CNCs was neutralized, resulting in an increased size of each nanocrystal at the aqueous status and the aggregated microfibers when dried up. The CTAB modification not only decreased the crystallinity of the samples from 48.57% to 9.12%, but also reasonably hydrophobized the CNCs and decreased their total surface energy. Finally, the adsorption behavior of the CNCs and CTAB-CNCs over nonionic, anionic, and cationic polymers was investigated by ellipsometry. Based on the thickness of the CNC and CTAB-CNC layers over 2-Hydroxyethyl cellulose (HEC), carboxymethyl cellulose (CMC), and polyethyleneimine (PEI), we proposed that the adsorption behavior was overall influenced by electrostatic interaction, hydrogen bonding, and van der Waals forces, and the thickness of the adsorbed layers could be impacted by both the surface charge and the size of the crystals.
Published: 2024
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160. Rapid detection of FadA in Fusobacterium nucleatum using the quantitative LAMP colorimetric phenol red method in stool samples from colorectal cancer patients

Author: Abdulrahman A. Zuraik, Yaman Daboul, M. Ayman Awama, Haitham Yazigi, Moh’d Azzam Kayasseh, and Michael Georges
Subjects: QLAMP, Phenol red, Fusobacterium nucleatum, FadA, Colorectal cancer (CRC), Medicine, Science
Abstract: Abstract The study aimed to develop a quantitative colorimetric loop-mediated isothermal amplification technique using the phenol red indicator (QLAMP-PhR) for detecting Fusobacterium nucleatum (Fn) levels in colorectal cancer (CRC) patients and healthy individuals. QLAMP-PhR assays were conducted on 251 stool samples specific for the Fn FadA gene. Six primers were synthesized and utilized with master mix reagents, and a phenol red indicator was employed to enhance the QLAMP-PhR technique. A standard quantitative analysis curve was generated using a logarithmic function (absorbance vs. concentration) by serially diluting the copy number of genomic DNA templates (Fn ATCC25586). The CRC group exhibited a significantly higher abundance of Fn compared to the healthy control group (P
Published: 2024
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161. Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis

Author: Alireza Baniasadi, Jeeban P. Das, Conor M. Prendergast, Zahra Beizavi, Hong Y. Ma, Muhammad Yaman Jaber, and Kathleen M. Capaccione
Subjects: Cancer, Fibrosis, Imaging techniques, Diagnosis, Tumor microenvironment, Medicine
Abstract: Abstract Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.
Published: 2024
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162. Unveiling genetic signatures associated with resilience to neonatal diarrhea in lambs through two GWAS approaches

Author: Yalçın Yaman, Yiğit Emir Kişi, Serkan S. Şengül, Yasin Yıldırım, and Veysel BAY
Subjects: Neonatal diarrhea, Single-locus GWAS, Multi-locus GWAS, Genetic resilience, Medicine, Science
Abstract: Abstract Neonatal diarrhea presents a significant global challenge due to its multifactorial etiology, resulting in high morbidity and mortality rates, and substantial economic losses. While molecular-level studies on genetic resilience/susceptibility to neonatal diarrhea in farm animals are scarce, prior observations indicate promising research directions. Thus, the present study utilizes two genome-wide association approaches, pKWmEB and MLM, to explore potential links between genetic variations in innate immunity and neonatal diarrhea in Karacabey Merino lambs. Analyzing 707 lambs, including 180 cases and 527 controls, revealed an overall prevalence rate of 25.5%. The pKWmEB analysis identified 13 significant SNPs exceeding the threshold of ≥ LOD 3. Moreover, MLM detected one SNP (s61781.1) in the SLC22A8 gene (p-value, 1.85eE-7), which was co-detected by both methods. A McNemar’s test was conducted as the final assessment to identify whether there are any major effective markers among the detected SNPs. Results indicate that four markers—oar3_OAR1_122352257, OAR17_77709936.1, oar3_OAR18_17278638, and s61781.1—have a substantial impact on neonatal diarrhea prevalence (odds ratio: 2.03 to 3.10; statistical power: 0.88 to 0.99). Therefore, we propose the annotated genes harboring three of the associated markers, TIAM1, YDJC, and SLC22A8, as candidate major genes for selective breeding against neonatal diarrhea.
Published: 2024
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163. Assessment of the implementation status of best available techniques for cleaner production in the textile industry

Author: Yaman, Mehmet Eren, Ozturk, Emrah, Yetis, Ulku, and Kitis, Mehmet
Published: 2024
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164. Correction: Comparative analysis of SPI, SPEI, and RDI ındices for assessing spatio-temporal variation of drought in Türkiye

Author: Yaman Öz, Fatma, Özelkan, Emre, and Tatlı, Hasan
Published: 2024
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165. An Examination of the Studies on Arabic Language Teaching (ALT): A Bibliometric Mapping Analysis

Author: Sen Yaman, Gül
Abstract: This study aims to use the bibliometric analysis method to examine the scientific articles published between 2000-2022 in the field of Arabic Language Teaching (ALT) and to visualize the obtained data with visual mapping technique. The dataset consists of 861 educational research articles indexed in the "Web of Science" database and containing the terms Arabic teaching or Arabic learning or Arabic education. Content analysis and bibliometric analysis were used in the analysis of the data. In the research, the distribution of publications by language, years, countries, journals, organizations, publications and keywords were accessed. In addition, the data obtained were presented by creating visual maps with common word analysis. The results showed that the most used keywords "Arabic", "higher education", "Arabic language" and "bilingualism". Most of the web of science indexed studies in the field of Arabic Language Teaching (ALT) are from the USA and Israel. The journals that publish the most papers in the field of Arabic Language Teaching (ALT) are "Reading and Writing" and "Foreign Language Annals". This study provides a guide for new studies, to identify the trends in the field of Arabic teaching and to compare the existing research on the topic.
Published: 2022

166. Preservice Mathematics Teachers' Achievement and Evaluation of Mathematical Modelling

Author: Boz-Yaman, Burçak
Abstract: The aim of the study was to understand preservice mathematics teachers' improvement of their knowledge of mathematical modeling and knowledge for teaching modeling postintervention. A total of 57 preservice mathematics teachers voluntarily participated in the study, which lasted for a period of five weeks. Data sources included three separate measurements; Mathematical Modeling Test, a questionnaire about the meaning of mathematical modeling, and model-eliciting activities. A quantitative and qualitative data analysis approach was employed in order to better understand the intervention achievement. The Mathematical Modeling Test data was examined with paired sample t-test, and the other two datasets were examined using thematic analysis to identify the preservice teachers' pedagogical content knowledge through mathematical modeling and their performance at each step of the mathematical modeling. Data analysis revealed that although the preservice teachers increased their mathematical modeling knowledge, they experienced difficulties during the interpretation and adaptation of the mathematical modeling results into the real life situations.
Published: 2022

167. Opinions of Teacher Candidates on the Effects of Emergency Distance Education Implementations during the COVID-19 Pandemic Period on Learning-Teaching Process, Metacognition and Social Skills: A Case Study

Author: Ortas, Banu Yaman and Demir, Ozden
Abstract: The aim of this study is to examine the effects of emergency distance education implementations carried out during the COVID-19 process on metacognition, social skills, active participation, communication with faculty members, as well as learning and teaching processes based on the views of education faculty teacher candidates. The research is a case study. The study was carried out in the Education Faculty of the Kafkas (n:31) and Education Faculty of the Trakya (n:20) in the 2020-2021 Fall semester. Opinions about the process were taken from 51 volunteer participants using a semi-structured interview form. Data was analyzed using content analysis and inductive analysis. As a result of the research, the elements that prospective teachers think that emergency distance education applications increase the effectiveness of the learning-teaching process were obtained in the themes of metacognition, social skills, active participation, effective communication with faculty members, and learning-teaching process. The factors that have a negative impact on the emergency distance education process are again expressed as increasing homework load, insufficient explanation of educational tasks, problems caused by the pandemic, problems originating from the internet, systemic-technological problems, inadequacies in gaining metacognition skills, and uniformity in methods and techniques.
Published: 2022

168. Need Analysis of a Web 2.0 Tool to Be Developed for Measurement and Evaluation in Education

Author: Tatli, Zeynap, Turan, Seyma, Yaman, Havva, and Er-Nas, Sibel
Abstract: The aim of this research is to reveal the features of a Web 2.0 tool for measurement and evaluation that will be developed for primary education teachers, in line with the opinions of experts from the Department of Computer Education and Instructional Technology (CEIT) and Primary Education (PE). Case study is one of the qualitative research methods used in this research. Participants consisted of 20 (CEIT: 10, PE: 10) field experts, with professional experiences ranging from 1 to 27 years. The opinions of the field experts were received through semistructured interviews. The findings obtained in the research were evaluated in general. It has been determined that the measurement and evaluation Web 2.0 tool to be developed for the use of primary education teachers, should not only have a question/answer design with multimedia support, but also include awards/competition and teamwork' interaction in order to be preferred by students. Additionally, it should provide ease of use and be supported by stakeholders in order to be preferred by teachers. It is recommended that the specified Web 2.0 tool should include outcome-based and graphical-based reporting features. Especially in the Covid-19 pandemic, in order for parents to support their child and follow the student's progress, it is recommended that a detailed statistical development report be included in the parent interface limited to their children only.
Published: 2022

169. Arabic Teacher Candidates' Perceptions of the 'Ideal Arabic Teacher'

Author: Sen Yaman, Gül
Abstract: In this study, prospective Arabic teacher's opinions about the ideal Arabic teacher characteristics were examined. The study was carried out according to the phenomenology study pattern, which is one of the qualitative research methods. The study group of this research, which was carried out in the 2021-2022 academic year, was determined by convenience sampling; The study consisted of 63 freshmen and sophomore teacher candidates, 25 male and 38 female, studying in the Arabic Language Teaching Program of the Faculty of Education at Süleyman Demirel University. Document was used as a data collection tool in the research. Teacher candidates were asked to write an essay about the ideal Arabic teacher. The compositions of the students formed the documents of the research. Interpretation of the data was done by content analysis. The findings of the study showed that pre-service teachers' views on the ideal Arabic teacher were divided into three themes: "Personal Characteristics "Professional Characteristics" and "Field Competence."
Published: 2022

170. H-AES: Towards Automated Essay Scoring for Hindi

Author: Singh, Shubhankar, Pupneja, Anirudh, Mital, Shivaansh, Shah, Cheril, Bawkar, Manish, Gupta, Lakshman Prasad, Kumar, Ajit, Kumar, Yaman, Gupta, Rushali, and Shah, Rajiv Ratn
Subjects: Computer Science - Computation and Language
Abstract: The use of Natural Language Processing (NLP) for Automated Essay Scoring (AES) has been well explored in the English language, with benchmark models exhibiting performance comparable to human scorers. However, AES in Hindi and other low-resource languages remains unexplored. In this study, we reproduce and compare state-of-the-art methods for AES in the Hindi domain. We employ classical feature-based Machine Learning (ML) and advanced end-to-end models, including LSTM Networks and Fine-Tuned Transformer Architecture, in our approach and derive results comparable to those in the English language domain. Hindi being a low-resource language, lacks a dedicated essay-scoring corpus. We train and evaluate our models using translated English essays and empirically measure their performance on our own small-scale, real-world Hindi corpus. We follow this up with an in-depth analysis discussing prompt-specific behavior of different language models implemented., Comment: 9 pages, 3 Tables, To be published as a part of Proceedings of the 37th AAAI Conference on Artificial Intelligence
Published: 2023

171. Synthesizing Human Gaze Feedback for Improved NLP Performance

Author: Khurana, Varun, Singla, Yaman Kumar, Hollenstein, Nora, Kumar, Rajesh, and Krishnamurthy, Balaji
Subjects: Computer Science - Human-Computer Interaction, Computer Science - Computation and Language
Abstract: Integrating human feedback in models can improve the performance of natural language processing (NLP) models. Feedback can be either explicit (e.g. ranking used in training language models) or implicit (e.g. using human cognitive signals in the form of eyetracking). Prior eye tracking and NLP research reveal that cognitive processes, such as human scanpaths, gleaned from human gaze patterns aid in the understanding and performance of NLP models. However, the collection of real eyetracking data for NLP tasks is challenging due to the requirement of expensive and precise equipment coupled with privacy invasion issues. To address this challenge, we propose ScanTextGAN, a novel model for generating human scanpaths over text. We show that ScanTextGAN-generated scanpaths can approximate meaningful cognitive signals in human gaze patterns. We include synthetically generated scanpaths in four popular NLP tasks spanning six different datasets as proof of concept and show that the models augmented with generated scanpaths improve the performance of all downstream NLP tasks., Comment: Accepted at European Chapter of the Association for Computational Linguistics (EACL)
Published: 2023

172. The LuViRA Dataset: Synchronized Vision, Radio, and Audio Sensors for Indoor Localization

Author: Yaman, Ilayda, Tian, Guoda, Larsson, Martin, Persson, Patrik, Sandra, Michiel, Dürr, Alexander, Tegler, Erik, Challa, Nikhil, Garde, Henrik, Tufvesson, Fredrik, Åström, Kalle, Edfors, Ove, Malkowsky, Steffen, and Liu, Liang
Subjects: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract: We present a synchronized multisensory dataset for accurate and robust indoor localization: the Lund University Vision, Radio, and Audio (LuViRA) Dataset. The dataset includes color images, corresponding depth maps, inertial measurement unit (IMU) readings, channel response between a 5G massive multiple-input and multiple-output (MIMO) testbed and user equipment, audio recorded by 12 microphones, and accurate six degrees of freedom (6DOF) pose ground truth of 0.5 mm. We synchronize these sensors to ensure that all data is recorded simultaneously. A camera, speaker, and transmit antenna are placed on top of a slowly moving service robot, and 89 trajectories are recorded. Each trajectory includes 20 to 50 seconds of recorded sensor data and ground truth labels. Data from different sensors can be used separately or jointly to perform localization tasks, and data from the motion capture (mocap) system is used to verify the results obtained by the localization algorithms. The main aim of this dataset is to enable research on sensor fusion with the most commonly used sensors for localization tasks. Moreover, the full dataset or some parts of it can also be used for other research areas such as channel estimation, image classification, etc. Our dataset is available at: https://github.com/ilaydayaman/LuViRA_Dataset, Comment: 7 pages, 7 figures, Accepted to ICRA 2024
Published: 2023

173. Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study

Author: Pasareanu, Corina S., Mangal, Ravi, Gopinath, Divya, Yaman, Sinem Getir, Imrie, Calum, Calinescu, Radu, and Yu, Huafeng
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Formal Languages and Automata Theory, Computer Science - Machine Learning
Abstract: Deep neural networks (DNNs) are increasingly used in safety-critical autonomous systems as perception components processing high-dimensional image data. Formal analysis of these systems is particularly challenging due to the complexity of the perception DNNs, the sensors (cameras), and the environment conditions. We present a case study applying formal probabilistic analysis techniques to an experimental autonomous system that guides airplanes on taxiways using a perception DNN. We address the above challenges by replacing the camera and the network with a compact probabilistic abstraction built from the confusion matrices computed for the DNN on a representative image data set. We also show how to leverage local, DNN-specific analyses as run-time guards to increase the safety of the overall system. Our findings are applicable to other autonomous systems that use complex DNNs for perception.
Published: 2023

174. RGB Arabic Alphabets Sign Language Dataset

Author: Al-Barham, Muhammad, Alsharkawi, Adham, Al-Yaman, Musa, Al-Fetyani, Mohammad, Elnagar, Ashraf, SaAleek, Ahmad Abu, and Al-Odat, Mohammad
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: This paper introduces the RGB Arabic Alphabet Sign Language (AASL) dataset. AASL comprises 7,856 raw and fully labelled RGB images of the Arabic sign language alphabets, which to our best knowledge is the first publicly available RGB dataset. The dataset is aimed to help those interested in developing real-life Arabic sign language classification models. AASL was collected from more than 200 participants and with different settings such as lighting, background, image orientation, image size, and image resolution. Experts in the field supervised, validated and filtered the collected images to ensure a high-quality dataset. AASL is made available to the public on Kaggle., Comment: Reference for the dataset that has inspired us to create our dataset: https://data.mendeley.com/datasets/y7pckrw6z2/1
Published: 2023

175. Design of Arabic Sign Language Recognition Model

Author: Al-Barham, Muhammad, Jamal, Ahmad, and Al-Yaman, Musa
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Deaf people are using sign language for communication, and it is a combination of gestures, movements, postures, and facial expressions that correspond to alphabets and words in spoken languages. The proposed Arabic sign language recognition model helps deaf and hard hearing people communicate effectively with ordinary people. The recognition has four stages of converting the alphabet into letters as follows: Image Loading stage, which loads the images of Arabic sign language alphabets that were used later to train and test the model, a pre-processing stage which applies image processing techniques such as normalization, Image augmentation, resizing, and filtering to extract the features which are necessary to accomplish the recognition perfectly, a training stage which is achieved by deep learning techniques like CNN, a testing stage which demonstrates how effectively the model performs for images did not see it before, and the model was built and tested mainly using PyTorch library. The model is tested on ArASL2018, consisting of 54,000 images for 32 alphabet signs gathered from 40 signers, and the dataset has two sets: training dataset and testing dataset. We had to ensure that the system is reliable in terms of accuracy, time, and flexibility of use explained in detail in this report. Finally, the future work will be a model that converts Arabic sign language into Arabic text.
Published: 2023

176. An Investigation of Parents' Use of Digital Media

Author: Yaman, Fatih, Çubukçu, Ahmet, Küçükali, Mustafa, and Yurdakul, Isil Kabakçi
Abstract: As the use of digital tools and the Internet becomes widespread and easier, the age of use is also decreasing. The decrease in the age of use makes opportunities as well as risks an important factor in digital environments. Children who are not aware of the risks in these environments may be exposed to various risks, especially as the age of Internet usage decreases. Parents are primarily responsible for protecting their children from risks in these environments. Parents can protect their children if they use digital media consciously and safely. In this context, the aim of this study is to investigate the parent's conscious and safe use of the Internet across Turkey. In accordance with this purpose, the study was designed as a survey study and the data of the study were collected from 9581 parents from 26 provinces with the Conscious and Safe Use of the Internet questionnaire developed by the researchers in the study. Descriptive statistics (%, f, X[bar], SS), t-test for independent samples, one-way analysis of variance (ANOVA), and correlation were used in the analysis of the data. As a result of the analysis of the data, it was determined that the parents' use of the Internet on weekdays and weekends was similar, but this situation differed in children. It has also been determined that the leading situations that worry parents in digital environments are the harmful and illegal content and excessive time spent in these harmful and illegal environments.
Published: 2021

177. Comparative seismic assessment of existing structures using P-delta effect in Indian context

Author: Chakrawarty, Manish, primary, Goyal, Pradeep K., additional, and Hooda, Yaman, additional
Published: 2024
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178. Paw{\l}ucki-Pl\'esniak Extension Operator For Non-Markov Sets

Author: Goncharov, Alexander and Paksoy, Yaman
Subjects: Mathematics - Functional Analysis
Abstract: We show that Pawlucki-Pl\'esniak operator is bounded for some non-Markov sets.
Published: 2022

179. Differentiated Science Instruction in the Metaverse with Gifted Students: Let’s Visit Kaz Mountains National Park!

Author: Yunus Emre Avcu and Yavuz Yaman
Subjects: gifted student, differentiation, SDG-15, Metaverse, immersive virtual reality, Education (General), L7-991
Abstract: A differentiated science activity was created for gifted students. The focus is on Sustainable Development Goal 15 (SDG-15) for life on land, enhancing engagement, self-regulated learning skills, and scientific creativity in gifted students. The activity spanned eight lesson hours, with tasks encouraging observation, inquiry, and creative thinking. Evaluation included achievement, process, and product forms, along with teacher observations and student feedback. Differentiating the learning environment and process through the utilization of Metaverse and immersive virtual reality technologies is crucial as it affords gifted students the chance to explore novel strategies in differentiated science education. In this particular context, three 3D scenes were created and imported into the Imedu Metaverse platform. Students used laptops to view 3D scenes at three separate occasions. During their visits, they examined living and non-living components of the forest ecosystem, including natural life and environmental conditions. Students experienced immersion with Oculus Quest 2 VR headsets. Following this encounter, they participated in querying procedures. Before and after utilizing applications within the Metaverse, efforts were made to enhance awareness of SDG-15 and foster scientific creativity.
Published: 2024

180. Defining the Traditional Mediterranean Lifestyle: Joint International Consensus Statement

Author: Labros S Sidossis, Rob Lawson, Emmanuel Aprilakis, Bernardo C. Barata, Alicja Baska, Anastasia Beneka, Robert Bird, Fraser Birrell, Charistoula Chatzinikola, Maria Chondronikola, George P Chrousos, Russell Conduit, Constantina Constantinou, Barbora deCourten, Jelena Helene Cvejic, Andrew M Davis, Christiana A. Demetriou, Linda Errington, Jack Feehan, Catalina Figueroa, Mary M. Flynn, Beth Frates, Robel Hussen Kabthymer, Leonidas G Karagounis, Leila Karimi, Gerard A. Kennedy, Ourania Kolokotroni, Darinka Korovljev, Antigone Kouris‐Blazos, Mehdi Kushkestani, Tassos C. Kyriakides, Emanuela Mercore Hutanu, Maria Cecilia Mosquera, Elena Nikiphorou, Nicola O'Brien, Elena Philippou, Karolina Piątek, Simon Poole, Dana Popescu‐Spineni, Sue Radd‐Vagenas, Amalia Sidossis, Magdalena Simonis, Helen Soultanakis, Aleksandra Telinga, Audrey Tierney, Anna Tkacz, Dimitris Vlachopoulos, Gulnur Yaman‐Dent, Yang Yap, Zoe Zervides, and Catherine Itsiopoulos
Subjects: diet, exercise, lifestyle choices, sleep pattern, social/emotional support, Public aspects of medicine, RA1-1270
Abstract: ABSTRACT Introduction The term “Mediterranean lifestyle” has gained increasing prominence in recent years, yet a specific definition remains elusive. In response, the Mediterranean Lifestyle Medicine Institute Board of Directors convened a multidisciplinary panel comprising international experts and leaders in lifestyle medicine. Their goal was to review existing literature and formulate a consensus definition of the “traditional Mediterranean lifestyle (tMedL),” referring to the historical way of living of the people in the Mediterranean region. This paper presents the agreed consensus statement and a comprehensive holistic definition of the term “traditional Mediterranean lifestyle.” Methods Major medical and social sciences electronic databases from inception to February 2023 were searched, employing keywords relevant to the Mediterranean lifestyle and its constituent elements (diet, physical activity, sleep, stress, socialization). Subsequently, definitions for each pillar were created and synthesized to derive a comprehensive definition of the “traditional Mediterranean lifestyle.” Results This proposed definition received ratification from the Mediterranean Lifestyle Medicine Institute's expert working group during the First International Mediterranean Lifestyle Medicine Conference held in June 2023 on the island of Leros, Greece. “The traditional Mediterranean lifestyle is characterized by its diverse and adaptable nature. Key facets encompass conviviality, lifelong social connectedness, purposeful living, strong community and familial bonds, harmony with nature and the environment, profound spirituality, adherence to religious practices, preservation of local customs, resilience cultivated through adversity, and a commitment to moderation across all spheres of life.” Conclusions This definition comprehensively outlines the primary lifestyle factors ingrained in Mediterranean inhabitants across generations. Its holistic nature furnishes a crucial conceptual framework for directing lifestyle medicine practitioners in assisting patients to mitigate diseases, promote overall well‐being, devise research initiatives to investigate the health ramifications of this lifestyle, and inform curriculum development.
Published: 2024
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181. Ansiedad y alfabetización en salud electrónica de pacientes que se someterán a cirugía torácica

Author: Sema N. Yaman-Çelik and Aylin Durmaz-Edeer
Subjects: Cirugía torácica. Alfabetización en salud electronica. Ansiedad pre-operatoria., Surgery, RD1-811
Abstract: Objetivo: Examinar la relación entre los niveles de ansiedad pre-operatoria de los pacientes que se someterán a una cirugía torácica y la alfabetización en salud electrónica, como encontrar y evaluar información de salud electrónica sobre problemas de salud. Métodos: Estudio descriptivo y relacional. Para recopilar datos se utilizaron la Escala de Ansiedad e Información Pre-operatoria de Amsterdam (APAIS), la Escala de Ansiedad Analógica Visual (EVA-A) y la Escala de Alfabetización en Esalud, y un formulario de información descriptiva del paciente. Resultados: Según la EVA-A, los niveles de ansiedad de los pacientes fueron de 6.02 ± 2.51. La puntuación APAIS fue de 18.73 ± 5.85. La puntuación de la escala de alfabetización en salud electrónica de los pacientes fue de 24.84 ± 9.21. No hubo una relación significativa entre los niveles de ansiedad de los pacientes y su alfabetización en salud electrónica. Se encontró una diferencia significativa entre los niveles de alfabetización en salud electrónica de los pacientes según su edad y el motive de la cirugía. Conclusiones: Los pacientes que serán sometidos a cirugía torácica experimentan ansiedad moderada y se determinó que necesitan información moderada . También se descubrió que los pacientes tenían niveles moderados de conocimientos sobre cibersalud. No hubo una relación significativa entre la ansiedad y los niveles de alfabetización en salud electrónica de los pacientes.
Published: 2024
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182. Deep venous arterialization in critical limb-threatening ischemia (CLTI): Case series and literature review

Author: Yaman Alsabbagh, Young Erben, Santh Prakash Lanka, Camilo Polania-Sandoval, and Houssam Farres
Subjects: Lower extremity, Limb salvage, Vein arterialization, CLTI, Case series, Diseases of the circulatory (Cardiovascular) system, RC666-701, Surgery, RD1-811
Abstract: Introduction: Chronic Limb-Threatening Ischemia (CLTI) represents a severe form of peripheral arterial disease characterized by ischemic rest pain, non-healing wounds, and/or gangrene. Deep Venous Arterialization (DVA) is an option when there is inadequate distal inline flow to allow for wound healing (No Option CLTI). There is a paucity of data on DVA; which prompted our interest in presenting our experience with DVA. Methods: We performed a retrospective review on all patients undergoing DVA from January 2022 through February 2024. The procedure was indicated for patients with CLTI as a last resort for limb salvage. Patient demographics, surgical techniques, and postoperative variables were recorded. Outcomes included were mortality, time to wound healing, minor and major amputations. All other operative complications were also recorded. Outcomes: There were eleven patients with a total of thirteen DVAs performed. Two DVAs were performed on the same limb. The mean age was 67.4 ± 11.3 years, with seven patients (63.6 %) being male. Comorbidities included were hypertension in nine (81.8 %), coronary artery disease in seven (63.6 %), hyperlipidemia in six (54.5 %), and type 2 diabetes mellitus in three (27.3 %) patients, respectively. At a median follow-up of 112.5 days (range: 76- 742 days), limb salvage was achieved in eight (66.7 %) and complete wound healing in four limbs (33.3 %). Seven (58.3 %) limbs required minor amputations. Four (33.3 %) limbs required major amputation including two (16.7 %) due to occluded bypass and two (16.7 %) due to uncontrolled infection. Two (18.2 %) deaths were recorded during the follow-up period. Conclusion: DVA has acceptable short outcomes with good limb salvage and wound healing rates. Timing to achieve mobility with associated deconditioning, quality of life, and cost are areas to be explored in larger studies in comparison to those patients undergoing primary amputation with immediate rehabilitation.
Published: 2024
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183. Chronic limb threatening ischemia due to radiation-induced arteriopathy 30 years after soft tissue sarcoma resection and radiation therapy: Case report and review of the literature

Author: Camilo Polania Sandoval, Houssam Farres, Yaman Alsabbagh, and Young Erben
Subjects: Radiation-induced peripheral artery disease, Femoral artery, Soft-tissue sarcoma, Bypass surgery, Diseases of the circulatory (Cardiovascular) system, RC666-701, Surgery, RD1-811
Abstract: Introduction: Peripheral artery disease (PAD) affects over 200 million people globally. A small subset of PAD patients are a result of radiation-induced peripheral artery disease (RIPAD). Radiation changes affect vascular physiology and cause arteriopathy with vessel damage and subsequent occlusion. This report details a case of common femoral and superficial femoral artery RIPAD with a review of the existing literature. Case report: A 40-year-old male patient presented with a six-month history of left leg rest pain. He had 30 years prior synovial cell sarcoma of the thigh treated with chemo- and radiation therapy with chronic residual lymphedema managed with compression therapy. Preoperative non-invasive studies demonstrated an ankle-brachial index of 0.42. Computed tomography angiography of the leg demonstrated a small caliber external iliac artery and occlusion of the common femoral and superficial femoral arteries. A left external iliac to above-the-knee popliteal artery bypass using a contralateral great saphenous vein was performed. Six weeks after operative intervention, the groin wound broke down and became infected. He required emergent repair of this bypass using 4 cm cryopreserved vein interposition graft. Intraoperative cultures were positive for Staphylococcus epidermidis and Finegoldia magna. At a 4.5-year follow-up, the patient remains active with a patent bypass and continues to manage his leg lymphedema with thigh-high elastic compression stockings. Conclusion: Clinical expertise is required to detect RIPAD early on. There is a high risk for post-operative complications due to radiation damage to surrounding tissues. Open surgical repair is the preferred treatment strategy. Lymphedema and wound healing complications are key to managing patients affected by RIPAD.
Published: 2024
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184. Behind the designs: An exploration of sustainability attitudes among interior design students in Jordan

Author: Yaman Sokienah
Subjects: Sustainability, Interior design, Design education, Ecological responsibility, Middle East, Curriculum development, Science (General), Q1-390, Social sciences (General), H1-99
Abstract: This research is an attempt to understand where interior design students in Jordan and the Middle East Region stand in the sustainable thinking process through education and practice and if their education on sustainability and environmental issues is enough or if it needs more development in terms of interior design programs curriculums to be more effective sustainable interior designers. The survey instrument was used to assess the attitudes of interior design students toward ecological responsibility and environmental sustainability; a modified New Ecological Paradigm Scale (NEP) was used in this research. Students enrolled in interior design programs at a Northern Jordanian university were surveyed. The sample comprised 160 interior design students from different levels of an interior design program at a public university in Jordan. In the study’s sample, the students showed more interest in the negative effect of human usage of many of the planet's resources and how this will impact the planet's ecological system. This attitude provides insight into the students’ minds regarding where they have those ideas. As design students, this can motivate them to take a proactive stand toward sustainability, which may be done through their projects in the future. However, many participants did not understand sustainable practices and strategies. This can be due to the lack of sustainability training at the university level.Based on the NEP score distribution in each section, it can be concluded that students support the concept of sustainability and reject the destruction happening to the planet. This data shows an increased awareness of environmental and ecological problems, which can positively push design students and future designers to adapt sustainable design strategies to their projects.
Published: 2024
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185. Characteristics of medically attended influenza infection across age groups before the COVID-19 pandemic in Lebanon

Author: Amani Haddara, Zeina Houry, Nada Zahreddine, Mark Atallah, Celina F. Boutros, Joseph Tannous, Christian Sadaka, Sarah Wehbe, Tamara Kadi, Ahmad Ibrahim, Rihab Ahmadieh, Tala Kardas, Nadia Soudani, Habib Al Kalamouni, Youssef Zgheib, Noha El Yaman, Sarah Khafaja, Mireille Lteif, Rouba Shaker, Aia Assaf Casals, Yolla Youssef, Nour Youssef, Zeinab El Zein, Sarah Chamseddine, Ahmad Chmaisse, Magda Haj, Danielle Fayad, Shereen Kiblawi, Imad Isaac, Hind Anan, Najwa Radwan, Rima Hanna Wakim, Hassan Zaraket, Souha S. Kanj, and Ghassan S. Dbaibo
Subjects: Influenza, Burden, Seasonality, Vaccination, COVID-19 pandemic, Lebanon, Infectious and parasitic diseases, RC109-216, Public aspects of medicine, RA1-1270
Abstract: Background: Influenza represents a significant global health burden for individuals and society. This study assessed the burden of medically attended influenza at a tertiary medical center in Lebanon to describe the demographics, risk factors, and outcomes prior to the COVID-19 pandemic. Methods: This was a retrospective review of patients who tested positive for the influenza virus during three seasons between July 1, 2016 to June 30, 2019, at the American University of Beirut Medical Center. Results: A total of 2049 patients who tested positive for influenza were analyzed. Influenza A accounted for 79.6 % of cases, and influenza B for 19.7 %, with influenza activity starting in October/November and peaking in December/January. Older age above 65 years (AOR=3.584), obesity (AOR=2.183), and chronic conditions such as chronic lung diseases (AOR=1.832), and bacterial co-infection (AOR= 2.834) were found to be independent risk factors for developing complications. Viral co-infection increased the likelihood of death tenfold. Vaccinated patients had a shorter mean hospital stay duration and a lower intensive care unit admission rate. Conclusion: The burden of medically attended influenza at our tertiary medical center in Lebanon prior to the COVID-19 pandemic was high. Vaccination decreased the likelihood of complications leading to intensive care unit admission in patients at risk.
Published: 2024
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186. Dual origin of the left vertebral artery: a rare anatomic variation

Author: Yaman, Vedat, Duzgun, Selin Ardali, and Hazirolan, Tuncay
Published: 2024
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187. Access to and quality of elective care: a prospective cohort study using hernia surgery as a tracer condition in 83 countries

Author: Dönmez, A Eylül, Goswami, Aakansha Giri, Raheja, Aashna, Bhadani, Aayush, El Kady, Abd Elrahman Safwat, Alniemi, Abdalaziz, Awad, Abdalkarim, Aladl, Abdalla, Younis, Abdalla, Alwali, Abdallah, Khalil, Abdallah, Mansour, Abdallah, Elkhouly, Abdallah Mohamed, Rashad Temerik, Abdallah, Hasan, Abdallatef, Chied, Abdelhafid, Abdraba, Abdelhamid, Hrora, Abdelmalek, Abdelshafi, Abdelrahman, Alwali, Abdelrahman, Maraqa, Abdelrahman, Ghaffar, Abdul, Chekfa, Abdul Jabar, Al Balushi, Abdul Majeed, Quddus, Abdul, Hammadieh, Abdul Rahman, Muntaka, Abdul-Jalilu Mohammed, Asekun, Abdulazeez, Alshahrani, Abdulaziz, Jowharji, Abdulaziz, Alshukre, Abdulbaset, Khair Etareig, Abdulhafid, Abubakar Abdulkarim, Abdulhafiz, Ashiru, Abdulhafiz, Alailesh, Abdulhamid, Al-Mallah, Abdullah, Baydoun, Abdullah, Chaudhry, Abdullah, Askin, Abdullah Emre, Almutairi, Abdulmjeed, Belkhair, Abdulmunem, Abdllah, Abdulrahman, Alhammali, Abdulrahman, Basalim, Abdulrahman, Abouelnagah, Abdulrahman Galal Mohamed Mostafa, Ghazal, Abdulrahman, Mohammed, Abdulrahman, Qasem, Abdulrahman, Anadani, Abdulrazak, Jimoh, Abdulrazaq, Lawal, Abdulrazzaq Oluwagbemiga, Khaity, Abdulrhman, Lawal, Abdulwahab, Elzoubi, Abdurrahim Esseid, Sheshe, Abdurrahman Abba, Cetişli, Abdurrahman Furkan, Oyedele, Abeeb, Aljahdali, Abeer, Aboelnasr, Abeer Gamal Elsyed, Demessie, Abel, Bhargava, Abhilasha, Sonkar, Abhinav Arun, Bavaharan, Abhirame, Khan, Abid, Campbell, Abigail, Oyelekan, Abimbola Adeola Akintunde, Okunlola, Abiodun Idowu, Ojewuyi, Abiodun, Ekerin, Abiola, Saleh, Abobakr, Khairy, Abouelatta, Muthunayagam, Abraham Benjamin, Botha, Abraham, Teshome Sahilemariam, Abraham, Nawawi, Abrar, Muhammad, Abubakar Bala, Dahiru, Abubakar, Yahaya, Abubakar, Abdelmalik, Abubaker, Anuar, Abul Akmal Arif, Ousseini, Adakal, Leon -Del- Angel, Adalberto, Frankel, Adam, Gyedu, Adam, Lim, Adam, Lukáč, Adam, Peckham-Cooper, Adam, Sabbah, Adam, Varga, Adam, Sanou, Adama, Issaka, Adamu, Ningi, Adamu, Yeshitila, Addis, Yingess, Addisu, Olugbami, Adebayo, Moses, Damola-Okesiji, Adebola, Lawal, Adedayo, Ojo, Adedoyin, Hashmi, Adeel, Fakoya, Adegbolahan, Ishola, Adegoke, Abiodun, Adekunle, Ajayi, Adekunle, Mouffokes, Adel, Bonelli, Adele, Adekoya, Adeleke, Akeem Aderogba, Adeleke, Özcan, Adem, Ayoade, Ademidun, Adeyeye, Ademola, Agbaje, Ademola, Talabi, Ademola, Ademuyiwa, Adesoji, Adewumiya, Adesoji, Ademuyiwa, Adesoji O, Aderounmu, Adewale, Adisa, Adewale, Oke, Adewale, Ragab, Adham, Alzadjali, Adil, Baksi, Aditya, Jayapalan, Aditya, Md Yunos, Adnan, Pisanu, Adolfo, Salazar, Adolfo, Salinas Barragan, Adrian Alberto, Fox, Adrian, Stollberg, Adrian, Franco, Adriana, Neves, Adriana, Vricheva, Adriana, Hodonou, Adrien Montcho, Aghayeva, Afag, Liaquat, Affifa, Alsultan, Afnan, Morad, Afnan, Kalidis, Afroditi Angella, Gkouniaroudi, Agathi, Karakosta, Agathi, Lovi, Agbenya, Yevide, Agossou Barthélémy, Duro, Agustin, Rodriguez Gonzalez, Agustin, Tariq, Ahbala, Abaidalla, Ahmad, Abuhammad, Ahmad, Abuhantash, Ahmad, Mansour, Ahmad Adel, Ahmad Zaidi, Ahmad Al Hafeez, Alahmad Alismael, Ahmad, Alayed, Ahmad, Alfarwan, Ahmad, Alhaj, Ahmad, Ali, Ahmad, Alroobi, Ahmad, Alsheikh, Ahmad, Alusef, Ahmad, Alzu'Bi, Ahmad, Kayali, Ahmad Amir, Bouhuwaish, Ahmad, Doghaim, Ahmad, El-Sherbiney, Ahmad, Ghazal, Ahmad, Ramly, Ahmad Nasir, Raza, Ahmad, Qureshi, Ahmad Uzair, Arnaout, Ahmad Yamen, Abdelhamid, Ahmed, Abuthaher, Ahmed, Adel, Ahmed, Ahmayda, Ahmed, Al-Mouahhed, Ahmed, Alagha, Ahmed, Albalawi, Ahmed, Albhaisi, Ahmed, Alrifaee, Ahmed, Azam, Ahmed, Barakat, Ahmed, Al-Hajjaj, Ahmed Basim Abed, Dawoud, Ahmed, El Shamarka, Ahmed, El-Bastwesy, Ahmed, Elghrieb, Ahmed, Elkhalifa, Ahmed, Elmosalamy, Ahmed, Elshazli Mahmoud, Ahmed, Montaser, Ahmed G., Gbeadese, Ahmed, Haty, Ahmed, K. Ali, Ahmed, Awad, Ahmed K., Kedwany, Ahmed, Khalleefah, Ahmed, Abbas, Ahmed M., Allam, Ahmed M., Maher, Ahmed, Elsayed, Ahmed Mohamed, Mohamed Ibrahim Mohamed, Ahmed, Mostafa, Ahmed, Nabil, Ahmed, Nada, Ahmed, Ragheb, Ahmed, Abdelrahman, Ahmed Saber Mohamed, Sabry, Ahmed, Sakr, Ahmed, Elkhodary, Ahmed Salah, Shaheen, Ahmed, Ammar, Ahmed Siddique, Hameed, Ahmer, Akmercan, Ahmet, Aslan, Ahmet, Barcin, Ahmet, Ciftci, Ahmet Burak, Bozkurt, Ahmet Çağlar, Sarı, Ahmet Can, Yaşar, Ahmet Can, Develioğlu, Ahmet, Öztürk, Ahmet Mücteba, Sanli, Ahmet Necati, Rencuzogullari, Ahmet, Yildiz, Ahmet, Kaan, Ahmet Zahit, Toi, Ahouefa Chourika Sakinath, Aljamoudi, Aida, Cheung, Aiden Chak Kei, Gkoutoula, Aikaterini, Kalogeropoulou, Aikaterini, Sarafi, Aikaterini, Abo Al Shamat, Aiman, Sanon, Aimé Serge Titianma, Sanon, Aimée Florence, Hiller, Aimée, Costas-Chavarri, Ainhoa, Lombardero, Ainhoa, Fraile, Ainoa, Bojazyah, Aisha, Kamal, Aisha, Gill, Aisling, Hada, Aïssatou, Gulla, Aiste, Mačiulaitytė, Aistė, Sukumar, Aiswarya, Landaluce-Olavarria, Aitor, Sainz Lete, Aitor, Pal, Ajay Kumar, Malik, Ajaz Ahmad, Horiguchi, Akihiko, Kocaay, Akin Firat, Akinkuolie, Akinbolaji, Olabode, Akingunloye, Fadipe, Akinniyi, Akinmade, Akinola, Darkwa Boateng, Akosua, Appiah-Kubi, Akosua Yeboaa, Alkaseek, Akram, Kadamani Abiyomaa, Akram, Anand, Akshay, Oppong, Akua, Opoku-Agyapong, Akwasi, Asharaf, Al Ameen, Ahmed, Al Samoul, Andani, Al-Hassan Dasana, Alkharusi, Al-Salt, Abd Elsattar, Alaa, Alragheai, Alaa, Alsalahat, Alaa Atta, Hawarah, Alaa, Aldirani, Alaa Nasib, Shabkah, Alaa, Nixon Fulli, Alafi Francis, Nguyen, Alain, Mustafa, Alamin, Joseph, Alan, Huws, Alaw, Aregawi, Alazar Berhe, Sanchez Gallego, Alba, Torroella, Alba, Vazquez Melero, Alba, Dauksa, Albertas, Abreu Da Silva, Alberto, Brun-Peressut, Alberto, Barranquero, Alberto G, Gegúndez Simón, Alberto, Gerundo, Alberto, Navarrete-Peón, Alberto, Viacava, Alberto, Vilar, Alberto, Adam, Albushra Altayeb, Jarimba, Aldo, Johnson, Aleena, Nuñez Venzor, Alejandra, Gonzalez Ojeda, Alejandro, Romero De Diego, Alejandro, Karamarkovic, Aleksandar, Butyrskii, Aleksandr, Edmundson, Aleksandra, Sidorova, Aleksandra, Thomas, Alen, Tomazic, Ales, Giuliani, Alessandra, Iodice, Alessandra, Marano, Alessandra, Marello, Alessandra, Ongaro, Alessandra, Saba, Alessandra, Anastasi, Alessandro, Borello, Alessandro, Broglia, Alessandro, Carta, Alessandro, Finocchio, Alessandro, Francia, Alessandro, Iacomino, Alessandro, Izzo, Alessandro, Ottaiano, Alessandro, Spaziani, Alessandro, Strumia, Alessandro, Biancafarina, Alessia, D'Ignazio, Alessia, Davolio, Alessia, Morello, Alessia, Licciardello, Alessio, Mazzoni, Alessio, Wilkins, Alex, Arekhandia, Alexander, Barlas, Alexandros, Chamzin, Alexandros, Demetriou, Alexandros, Giakoustidis, Alexandros, Kozadinos, Alexandros, Kyriakidis, Alexandros, Sarakatsanos, Alexandros, Rojas, Alexei, Saridaki, Alexia, Litchinko, Alexis, Arnaud, Alexis P, Binder, Alf-Dorian, Yakubu, Alfa, Kavalakat, Alfie, Shamsutdinova, 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N, Felix, Alahmad, Feras, Alnimri, Feras, Haddad, Feras, Gool, Ferhana, Castro, Fernanda, Diaz, Fernanda, Lucero, Fernanda, Vovola, Fernanda, Mahnic, Fernando, Mercado Sanchez, Fernando, Prieto La Noire, Fernando, Soggiu, Fiammetta, Tsige, Fikreab, Brzeszczyński, Filip, Rudisch, Filip, Valente Costa Pinto, Filipa, Ramalho De Almeida, Filipe, Banchini, Filippo, Palomino Escalante, Fiorella, Fadzlullah, Fitri, Terefe, Fitsum, Sulo, Fjorenta, Ciccarone, Flavia, Tirelli, Flavio, Krämer, Florian, Grama, Florin, Spanos, Foivos, Solimene, Folco, Akinwande, Foluso, Osman, Forzia, Stefou, Foteini, Kyramargios, Fotios, Stavratis, Fotios, Alassani, Fousseni, Ascari, Francesca, Cammelli, Francesca, D'Agostino, Francesca, Tropeano, Francesca Paola, Peters, Francesca, Ré, Francesca, Brucchi, Francesco, Casti, Francesco, Coratti, Francesco, Ferrara, Francesco, Floris, Francesco, Izzo, Francesco, Maffei, Francesco, Palmieri, Francesco, Pata, Francesco, Porcelli, Francesco, Selvaggi, Francesco, 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Judy, Mühlhäusser, Julia, Sidorovskaia, Julia, Carrizo, Julian, Napoli, Juliana, Pereira-Macedo, Juliana, Ribeiro, Juliana, De Deken, Julie, Nnoli, Juliet, Paredes, Julieta, Zevallos-Quiroz, Julio Cesar, Gonzalez Garcia, Julio, Adjei, Julius, Olaogun, Julius, Kutkevičius, Juozas, Metzger, Jürg, Košir, Jurij Aleš, Kosir, Jurij, Seyi-Olajide, Justina, Zajac, Justyna Karolina, Dhima, Jyoti, Dhiman, Jyoti, Shreyas, K, Türker, Kadir Yağız, Lee, Kai, Khutsishvili, Kakhi, Yu, Kam Keung Auston, Das, Kamala, Özdoğan, Kamil, Reddy, Kamireddy Madana Raghava, Kabulov, Kamran, Nahar, Kamrun, Rajaratnam, Kanapathippillai, Wijesinghe, Kanchana, Sevnaran, Kapil, Khalil, Karam, Singh, Karanbir, Fayed, Kareem, Booyse, Karien, Geiger-Timm, Karin, Maharaj, Karl, Bhutia, Karma, Richter, Karolina, Komorowska, Katarzyna, Urbańska, Katarzyna, Waddell, Kate, Kambouri, Katerina, Tata, Katerina, Richetti, Katharina, Griffin, Katherine, McKenzie, Katherine, Tambudze, Katherine, Hall, Katheryn, Chu, Kathryn, Theodoropoulou, Katina, Kröning, Katrin, Bozada-Gutiérrez, Katya, Raghuwanshi, Kaustubh, J B, Kavitha, Ahmed Ibrahim, Kefah, Bwala, Kefas John, Iles, Kelly, Jasso García, Kelvin, Oğur, Kemal, Fretwell, Kenneth, Oluchukwu, Kenneth, Onyekachi, Kenneth, Voon, Kenneth, Oderoha, Kevin Ewomazino, Nieto Yrigoin, Kevin, Quispe De La Roca, Kewin, Anaam, Khadega, Bensmain, Khadija, Shwail, Khadija, Akter, Khadiza, Sawaftah, Khaled Ahmad, Shamiyah, Khalid Adnan, Bhatti, Khalid, Mohammed, Khalid Miftah Ghuraybeel, Ayyoub, Khalil, Cholah, Khalil, Rahman, Khandakar Rezwanur, Abdulrahman, Khawla, Al-Shami, Khayry, Hayat, Khizar, Al Hinai, Khulood, Taghavi, Kiarash, Shodunke, Kikelomo, Abo Zaal, Kinaz, Ewool, Kingsley, Gaikwad, Kiran, Shemyatovsky, Kirill, Dey, Kirsty Elaine, Mishra, Kirti Kumar, Rathod, Kirtikumar J, Senanayake, Kithsiri Janakantha, Noguchi, Kiyonari, Kordeni, Kleoniki C., Dembele, Klétigui Samuel, Spassov, Kolyo, Khalid, Komal, Petrenko, Konstantin, Bekiaridou, Konstantina, Rekouna, Konstantina, Athanassiou, Konstantinos, Avgerinos, Konstantinos, Bouchagier, Konstantinos, Bouliaris, Konstantinos, Bramis, Konstantinos, Iliakopoulos, Konstantinos, Kontzoglou, Konstantinos, Ntatsis, Konstantinos, Pavlopoulos, Konstantinos, Perivoliotis, Konstantinos, Polychronopoulos, Konstantinos, Giannakopoulos, Konstantinos S., Zakkas, Konstantinos, Zapsalis, Konstantinos, Koumarelas, Konstantinos-Eleftherios, Mori, Krinal, Ooi, Krisada, Ascencio Diaz, Kriscia Vanessa, Jasaitis, Kristijonas, Nieuwenhuys, Kristin, Atherton, Kristy, Smith, Kristy, Sharma, Kruti, Jaffry, Kumail, Lehmann, Kuno, Ayad, Kusay, Luthra, Kush Kumar, Nanayakkara, Kushan, Agbedinu, Kwabena, Oduro-Boateng, Kwaku Boakye, Boakye-Acheampong, Kwame, Sim, Kwang Kiat, Yalley, Kwekuma, Collins, Kyeremeh, Muscat, Kyle, Hofmann, Kyra, Lambri, Kyriaki, Bananis, Kyriakos, Nassim, Kyrillos, Allan, Lachlan, Codina Corrons, Laia, Hijazein, Laith, Moolla, Laith, Sweidan, Laith, Rai, Lajpat, Devi, Lakshmi, Fountoulis, Lampros, Andreski, Lara, Bonello, Lara, Rodrigues Madeira, Lara, Tafesh, Lara, Yasin, Lara, Martinez, Laura, Fortuna, Laura, Peña Balboa, Laura Gabriela, García-Zambrano, Laura, Bolaños, Laura Isabela, Jiménez, Laura, Lely, Laura, Ortega Lechuga, Laura, Rossi, Laura, Rubin, Laura, Ruiz-Villa, Laura, Sequi, Laura, Sahan, Laura-Ann, Johnstone, Lauren, Monteiro, Lauren, Abdullahi, Lawal Barau, Jovcheski, Lazo, Siragusa, Leandro, Kang, Leannedra, Elgebaly, Leenah, Mansour, Lefteris, Robine-Durnell, Lélia, Bray, Lemuel Davies, Mohammed, Lena, Licari, Leo, Onyebulu, Leonard, Chieng, Leonard Ron, Solaini, Leonardo, Chardalias, Leonidas, Fountarlis, Leonidas Ilias, Van Den Hil, Leontine, Tapia Moral, Leopoldo, Petashvili, Leri, Heeren, Letícia, Laface, Letizia, Niyidukunda, Lewis, Barnard, Liam, Torres Bavestrello, Lidice Veronica, Hasan, Lilav, Dyab, Lima, Venclauskas, Linas, Beukes, Linda, Gabellini, Linda, Liepa, Linda, Zeng, Lingjuan, Dubs, Linus, Rampersad, Lisa, Catozzi, Livio, Castro, Lizeth, Milic, Ljiljana, Shawesh, Lobna, Anyanwu, Lofty-John, Khalifa, Lojina, Cheng, Lok Pong, Manoj Joshua, Lokavarapu, Shammas, Lora, Fuentes Rivera Lau, Lorena, Rodríguez Gómez, Lorena, Capello, Lorenzo, Epis, Lorenzo, Fatucchi, Lorenzo Maria, Rende, Lorenzo, Ripamonti, Lorenzo, Ackam, Louis, Moniz, Lourenço, Bains, Lovenish, Alriyami, Lubna, Alokshi, Lubnah, Martinek, Lubomir, Tulinsky, Lubomir, Samison, Luc, Lo Piccolo, Luca Benedetto, Cardinali, Luca, Nespoli, Luca Carlo, Casingena, Luca, Degrate, Luca, Bonomo, Luca Domenico, Morelli, Luca, Ottaviani, Luca, Resca, Luca, Scaravilli, Luca, Schiavone, Luca, Theuil, Luca, Casalduero, Lucas, Lee, Lucas D., Granero, Lucas, Caram, Lucas Jose, Barni, Lucia, Cidade Costa, Luciana, Paredes, Luciana, Poggi, Luciano, Marquez, Lucila, Garciandia, Lucio, Taglietti, Lucio, Pramod, Ludiya, Stella, Ludovica, Carbone, Ludovico, Bracciano, Luigi, Cobellis, Luigi, Conti, Luigi, Fedele, Luigi, Ragazzini, Luigi, Simonelli, Luigi, Verre, Luigi, Flores Chávez, Luis Adrián, Rea Bocanegra, Luis Alberto, Pelayo Orozco, Luis Ángel, Asensio Gomez, Luis, Bravo, Luis, Flores Chávez, Luis Manuel, Poggi, Luis, Cabezudo, Luis Ramón, Sante Serna, Luis, Tallon-Aguilar, Luis, Talé-Rosales, Luis-Fernando, Chantada, Luisa, Moreira, Luísa, Hasan, Lujain, M Mheidat, Lujain, Eisner, Lukas, Gantner, Lukas, Havranek, Lukas, Majerčák, Lukáš, Pánči, Lukáš, Nawacki, Łukasz, Adagrah Aniakwo, Luke, Bromley, Luke, Green, Luke, Paterson, Luke, Peters, Luke, Abdur-Rahman, Lukman, Omomeji, Lukman, Amosu, Lukmon, Kolongi, Lungushinga Christopher, Bin Aizan, Luqman Naim, Imchen, Lurong, Chang, Lydia, Mukamazera, Lydie, Katsiaras, Lykoyrgos, Al-Boukhari, Lynn, Chong, Lynn, Karydakis, Lysandros, Peris, M. Roosindu, Cancelas, Mª Dolores, Kariem, Maahir, Amoako-Boateng, Mabel, Alshamikh, Mabroukah, Ishak, Mabruok, Narayanan, Machingal, Matyja, Maciej, Walędziak, Maciej, Zounon, Mack-Arthur, Trindade, Madalena, Shahid, Madeeha, Kelly, Madeleine, Bajwa, Madiha, Bowles, Madison, Roussos, Madison, Sampaio-Alves, Mafalda, Manfredini, Magda, Kołomańska, Magdalena, Redynk, Magdalena, Farooq, Maham, Ali, Mahamudu Ayamba, Rodha, Mahaveer Singh, Alsalawi, Mahdi, Lodha, Mahendra, Sethi, Mahesh Kumar, Khalil, Mahfoud, Singh, Mahima, Abdualqader, Mahmmoud yehia, Abdelhafez, Mahmood, Sersarah, Mahmood, Abdelreheem, Mahmoud, Abu Al Amrain, Mahmoud, Barbarawi, Mahmoud, Diab, Mahmoud, Eissa, Mahmoud, ElFiky, Mahmoud, Elmesalmi, Mahmoud, Elmousili, Mahmoud, Fahmy, Mahmoud, Faisal, Mahmoud, Jabal, Mahmoud, Saad, Mahmoud M., Mahafdah, Mahmoud, Marei, Mahmoud Marei Abdelaziz, Mostafa, Mahmoud, Reda, Mahmoud, Zahran, Mahmoud, Suleman, Mahmowd, Genç, Mahmut Salih, Haghighat Ghahfarokhi, Mahta, Abubakar, Maimuna, Haimona, Mairarangi, Camuera, Maite, H. Oweidat, Majd, Mansour, Majd, Kalabić, Majda, MohammedAli, Majdeddin, Abu Daoud, Majdi, Almahjoub, Majdolin, Bilfaqirah, Majed, Yigah, Makafui, Akkawe, Malak, Dery, Malcolm, West, Malcolm, Rius, Malena, Nandasena, Malith, Aljarawn, Mallak, Masaaod, Mallak, Manangi, Mallikarjuna, Windsouri, Mamadou, Battili, Mamata, Rakotonaivo, Mamisoa Judicaël, Benghazi, Manaji, Al-Dhaheri, Manal, Almaqrahi, Manal, Katif, Manal, Alshami, Manar, Ibrahim, Manar, Ramazanov, Manas, Kaur, Mandeep, Agrawal, Manish Kumar, Pathak, Manish, Aggarwal, Manisha, Chandrasegaram, Manju, Anandan, Manoj, K S D, Manoj Kishan Lal, Kumar, Manoj, Sarda, Manoj, K B, Manojkumar, Jokubauskas, Mantas, Moreno Gonzales, Manuel Arturo, Cruz, Manuel, Diez Alonso, Manuel, Garcia, Manuel, Perez, Manuel, Mosquera Paz, Manuel Santiago, Cammelli, Manuela, Mercurio, Manuela, Singh, Manvinder, Taamreh, Manwa, Canals Sin, Mªpilar, Carbonell Pradas, Mar, Nunes, Mara, Sawaftah, Marah Ahmad, Khalil, Maram, Schneider, Marcel André, Steffani, Marcella, Pisano, Marcello, Doniquian, Marcelo Alejandro, Martínez Bareiro, Marcelo Nicolás, Pagani, Marcelo, Scortechini, Marcelo, Carvalho, Márcia, Sánchez Audelo, Marco Antonio, Brizzolari, Marco, Ceresoli, Marco, De Prizio, Marco, Amisano, Marco Francesco, Gramellini, Marco, Marcianò, Marco, Mariani, Marco, Milone, Marco, Montagna, Marco, Piccino, Marco, Santos, Marco, Dyer, Marcus, Kang, Marcus, Mahadi, Mardhiana, Zawadzki, Marek, Yinusa, Margaret, Bernardo, Margarida, Nunes Luís, Margarida, Gambelli, Margherita, Flint, Margot, Aggelidou, Maria, Bequis, Maria Agustina, Sotiriou, Maria Aikaterini, Ñañez, Maria Alejandra, Tahir, Maria Ambreen, Gascón Domínguez, María Ángeles, Asimakidou, Maria, Mourato, Maria Beatriz, Blanco, Maria, Christou, Maria, Coronas Soucheiron, Maria, Pignanelli, Maria Costanza, Kalaydjian, María Cristina, Martí-Ejarque, Maria del Mar, Olmedo Reinoso, María Del Mar, Cebollero, María Del Pilar, Derattani, Maria, Gama Caldeira, Maria Do Carmo, Drogouti, Maria, Gonzalez-Gonzalez, Maria Elena, Muñoz Fernández, María Elena, Muriel, María Emilia, Duran, María Eugenia, Zarate Casas, María Fernanda, Florou, Maria, Piacentini, Maria Gaia, Seixo, Maria Inês, Bellini, Maria Irene, Peña Soria, Maria Jesús, Martínez, María José, Medina, Maria José, Rueda Medécigo, María José, Karakeke, Maria, Kausar, Maria, Kyriazi, Maria, Marqueta De Salas, Maria, Modolo, Maria Marta, Mateu, Maria, Mavri, Maria, El Ghoul Miliotou, Maria Melina, Moreno Gijon, Maria, Papadoliopoulou, Maria, Proclamà, Maria Pia, Picciochi, Maria, Reis, Maria, Rennis, Maria, D'Anna, Maria Rosa, Ruffoli, Maria, Ruiz Soriano, María, Sánchez Ramirez, Maria, Sánchez-Rubio, María, Schüler, Maria, Sotiropoulou, Maria, Barrio Renteria, Maria Teresa, Tsopozidi, Maria, Vasconcelos, Maria, Facchino, Maria Vittoria, Wikar, Maria, Aguilera-Arevalo, Maria-Lorena, Abdu, Mariam, Asarbakhsh, Mariam, Elmiesiry, Mariam, Ashong, Marian Esi, Gomes, Mariana, Capuano, Marianna, Lill, Marianne, Nieto Galvan, Mariano, Osso, Mariasara, Olivos, Maricarmen, Sacdalan, Marie Dione, Weber, Marie-Christin, Gonzalez, Marijose De Cristo, Ferreira, Marília, Infantes Ormad, Marina, Kouliou, Marina Nektaria, Ransome, Marina, Vicario Bravo, Marina, Cuesta Argos, Mario, Faletar, Mario, Giuffrida, Mario, Lainez Escribano, Mario, Pacilli, Mario, Pannullo, Mario, Rodriguez-Lopez, Mario, Trejo-Avila, Mario, Merrakos, Marios, Tello Jimenez, Marisol, Kalisvaart, Marit, Quaunine, Marium, Perera, Mariyan, Harris, Mark, Youssef, Mark Melad Thabet, Peter, Mark, Philipp, Mark, Portelli, Mark, Jesudason, Mark Ranjan, Sammut, Mark, Tomlinson, Mark, Zammit Vincenti, Mark, Despotidis, Markos, Albertsmeier, Markus, Quante, Markus, Löffler, Markus W., Gurung, Markush, Gumsheimer, Marlena, Benamrouche, Maroua, Chaccour, Maroun, Ahmed, Marriam, Farooqui, Marryam Riaz, Angelini, Marta, Ortega Escudero, Marta, Martin Gimenez, Marta Pilar, Reia, Marta, Scricciolo, Marta, Caramantin Obando, Martha Maria, Gosselink, Martijn, Bertrand, Martin, Dum, Martin, Kajic, Martin, Karamanliev, Martin, Kyereh, Martin, Lucchini, Martin, Schön, Martin, Morna, Martin Tangnaa, Binda, Martina, Ceolin, Martina, Martorana, Martina, Zambon, Martina, Shams, Marvi, Alansary, Marwa, Alnuwayli, Marwa, Khalifa, Marwa, Bahnacy, Marwan, Iqreewi, Marway, Nnabagulanyi, Mary, Saleem, Marya, Alhimyar, Maryam, Kamal, Maryam, Masood, Maryam, Razaq, Maryam, Siddique, Maryam, Lazo Ramírez, Maryzela, Edeeb, Masaoud, Solkar, Maseera, Adetoyi, Mashood, Adeniyi, Caccetta, Massimiliano, Casati, Massimiliano, Veroux, Massimiliano, Dugo, Massimo, Bevanda, Mateo, Santillan, Mateo, Mietła, Mateusz, Pryt, Mateusz, Muir, Mathew, Bei, Matilda, McGuinness, Matt, Aulicino, Matteo, Castrovillari, Matteo, Filardo, Matteo, Palmeri, Matteo, Pisano, Matteo, Rottoli, Matteo, Gjoka, Mattheus, Binks, Matthew, Corcos, Matthew, Kwon, Matthew, Maybury, Matthew, Sammut, Matthew, Tutton, Matthew, Watson, Matthew, Biebl, Matthias, Janda, Matthias, Maak, Matthias, Wichmann, Matthias, Berselli, Mattia, Gritti, Mattia, Molteni, Mattia, Pacilli, Maurizio, Favoriti, Mauro, Garino, Mauro, Podda, Mauro, Santarelli, Mauro, Alfaid, Mawada, Albert, Mawadri Jimmy Isaac, Oyortey, Mawuenyo Attawa, Enßlin, Max, Berlet, Maximilian, Brunner, Maximilian, Kießler, Maximilian, Scheiterle, Maximilian, Sohn, Maximilian, Busch, Maximiliane, Perkins, Maya, Sabboh, Maya, Badkur, Mayank, Okudero, Mayowa, Mohamedshafee, Maysoon, Al-Juaifari, Maytham Aqeel, Elesseily, Mazen, Mohammad, Mazen, Nikberg, Maziar, Jean Claude, Mbonicura, Şermet, Medeni, Chisthi, Meer, Luthra, Meera, Sulciner, Megan, Kaple, Meghali, Bhat, Meghana, Koç, Mehmet Ali, Avci, Mehmet Alperen, Kizilkaya, Mehmet Celal, Kara, Mehmet Emin, Ozcelik, Mehmet Faik, Ozsoy, Mehmet Sait, Zaigham, Mehreen, Mesfin, Mekdelawit, Kalender, Mekselina, Mellado Tellez, Mel Paul, González De Miguel, Melania, Farrugia, Melanie, Theodoridou, Melanie, Barcelona, Melden Darrell, Aktas, Melik Kagan, Fernández Zurita, Melissa Andrea, Bautista, Melissa, Park, Melissa, Rodríguez-Ordoñez, Melissa-Zohemia, Yashar, Meltem, Worku, Mengistu, Al-Fraijat, Meran, Estaire Gómez, Mercedes, Shoshkova, Meri Danailova, Kruščica, Merima, Tanal, Mert, Çuhadar, Merve, Tokocin, Merve, Agyapong, Meshach Manu, Erkaya, Metincan, Okechukwu, Mgbako, Adinku, Michael, Bickford, Michael, Ediale, Michael, Issa, Michael, Konstantinidis, Michael K., Lie, Michael, M. Nathan, Michael, Maclean, Michael, Nortey, Michael, Pellen, Michael, Pham, Michael, Pitiakoudis, Michael, Singh, Michael Prodip, Spartalis, Michael, Van Der Colf, Michael, Wilson, Michael, Billis, Michail, Karanikas, Michail, Papamichail, Michail, Vailas, Michail, Kisielewski, Michał, Kusiński, Michał, Nycz, Michał, Święch, Michał, Fagbayimu, Micheal, Adamina, Michel, Fiogbe, Michel, Prudhomme, Michel, Angelucci, Michela, Campanelli, Michela, Cricrì, Michele, Grande, Michele, Manigrasso, Michele, Scopelliti, Michele, George, Michelle, Mozel, Michelle, Galasyuk, Mick, Chevallay, Mickael, Giuliano, Micol, Dobón Rascón, Miguel Ángel, Fernandez Romero, Miguel Angel, García Ureña, Miguel Ángel, Zaragoza Mendieta, Miguel Ángel, Bejarano Serrano, Miguel, Brito, Miguel, Calderon, Miguel, Jurado Román, Miguel, Palas, Miguel, Li Valencia, Miguel Roberto, Sebastián-Mendoza, Miguel-Julián, Muresan, Mihai-Stefan, Slavchev, Mihail, Agapov, Mikhail, Milentijević, Milica, Catterall, Millie, Stjepanovic, Milos, Doss, Mina, Natey, Mina, Aikins, Minas, Mattis, Minca, Ekanayake, Minoli Tharushika, Tora, Mir Mehrab Sharmin, Alsharayri, Mira, Shalaby, Mira, Boras, Miran, Riba Martínez, Mireia, Mogiatti, Mirella, Salibašić, Mirhan, Biancu, Miriam, Cappiello, Miriam, Koschke, Miriam Luise, Sadek, Mirna, Szura, Miroslaw, Horga, Miruna, Dason, Mishael, Tayyab, Mishal, Imirski, Mitko, Pejović, Mladen, Tabaza, Mo'Ath, Alneasan, Moaaz, Shalkamy, Moamen, Issa, Moammad Issa, Erfan, Moatasem, Ewedah, Moataz, Srour, Moayad, Beletachew, Moges, Abbas, Mohamad, Farho, Mohamad Ali, Marawy, Mohamad Kher, Klib, Mohamad, Morjan, Mohamad, Sawas, Mohamad Nabhan, Elghriani, Mohamed Abdelbaset Masoud, Abdelmaboud, Mohamed, Abdelmaksoud, Mohamed, Abdullahi, Mohamed, Abo Abdo, Mohamed, Ahmed, Mohamed, Ahmoud, Mohamed, Al Sayed, Mohamed, Suliman, Mohamed Almouafaq, Alsori, Mohamed, Altajouri, Mohamed, Assalhi, Mohamed, Berrakkouch, Mohamed, Elnour, Mohamed, Abdelsalam, Mohamed Elsayed Elaraby Abdelrahim, Elsayed Metwally, Mohamed, Hajalamin, Mohamed, Kamal Matter, Mohamed, Khaled, Mohamed, Kouta, Mohamed, Masoud, Mohamed, Almihashhish, Mohamed Miftah, Mokhtar, Mohamed, Mostafa, Mohamed, Yassin, Mohamed Musa, Bouhafs, Mohamed Nedjmeddine, Herdan, Mohamed Omar, Omer, Mohamed, Osman, Mohamed, Zaazou, Mohamed, Zahed Abdalla, Mohamed, Melouane, Mohamed-Sami, Abed, Mohammad, Sawaftah, Mohammad Ahmad Mohammad, Al-Masri, Mohammad, Al-Qannas, Mohammad, Ali-Hassanzadeh, Mohammad, Yunus, Mohammad Alif, Aloulou, Mohammad, Alrantisi, Mohammad, Araydah, Mohammad, Bani Hani, Mohammad, Barakat, Mohammad, Durrani, Mohammad, Khan, Mohammad Faisal, Dwikat, Mohammad Fuad, Hasan, Mohammad, Nabhan, Mohammad Hassan, Hijazi, Mohammad, Abu Albahrain, Mohammad Karam, Barakat, Mohammad Mounzer, Mubarak, Mohammad, Omar, Mohammad, Pourfridoni, Mohammad, Mslmani, Mohammad Rabee, Salah, Mohammad, Tanashat, Mohammad, Yahmad, Mohammad, Elmujtaba, Mohammed, Abd Al-Fattah, Mohammed, Abdelkabir, Mohammed, Abosedra, Mohammed, Sarker, Mohammed Abu Kawsar, Abudabbous, Mohammed, Abuwarda, Mohammed, Elgak, Mohammed Ahmed, Al Hinai, Mohammed, Al Zebda, Mohammed, Al-Shehari, Mohammed, Alharthi, Mohammed, Ali, Mohammed, Ismael Alamin, Mohammed Ali, Alqadasi, Mohammed, Alshanwani, Mohammed, Alshehri, Mohammed, Asaad, Mohammed, Bashir, Mohammed, Bohlala, Mohammed, Meghaizerou, Mohammed El Amine, Albanna, Mohammed Emad Hashem, Ghunaim, Mohammed, Goga, Mohammed, Hajhamad, Mohammed, Hamada Takrouney, Mohammed, Hammoda, Mohammed, Hamoud Almahly, Mohammed, Muragi, Mohammed, Mohammed, Mohammed Mustafa Hassan, Obaid, Mohammed, Omar, Mohammed, Said, Mohammed, Salah, Mohammed, Saleh Khatab, Mohammed, Aliyu, Mohammed Salele, Shakhshir, Mohammed, Sheriff, Mohammed, Tageldin, Mohammed, Abdelfattah, Mohanad, Daher, Mohanad, Lotfy, Mohanad, Alqedrh, Mohannad, Nasani, Mohannad, Mohd Shah, Mohd Shahrulsalam, Madany, Mohie El-Din Mostafa, Mobolaji-Ojibara, Mojisola, Nkogatse, Moleseng, Alazabi, Mona, Gupta, Money, Bogdan, Monica, Guerrero, Monica, Noguez Castillo, Monica, Gureh, Monika, Kacem, Montasser Jamaleddine, Tarar, Moosa Feroze, Seto, Morel, Steinruecke, Moritz, Edena, Morrison, Abdulsalam, Moruf, Abdelhadi Suliman Adam, Mosab, Saleh, Mosab, Anati, Mosaikah, Dokurugu, Moses Abdulai, Agunloye, Moses, Ibadin, Moses, Momoh, Moses, Abdelkarim, Mostafa, Kamar, Mostafa, Kotb, Mostafa, Mahran, Mostafa, Mohamad Amin, Mostafa, Shalaby, Mostafa, Waseem, Mostafa, Almaletti, Motasem, Saifi, Motaz, Tsuruta, Motohisa, Agbadebo, Mouhamed, Arnaout, Moumen, Ojo, Moyosoluwa, Sharma, Mrthyunjayani, Azzuz, Muad Mohamed Ramadan, Haj Hussein, Mudar, Ameen, Muftiat Omolola, Nkoronko, Mugisha, Fitri, Muhamad, Abdullah, Muhammad, Bashir, Muhammad Ahmad, Sadiq, Muhammad Ahmad, Ahmed, Muhammad, Ali, Muhammad, Al-Yusuf, Muhammad Ali, Haider, Muhammad Aliyan, Alshaar, Muhammad, Mirza, Muhammad Bilal, Che Yaacob, Muhammad, Daniyan, Muhammad, Elzayat, Muhammad, Butt, Muhammad Faizan, Sadiq, Muhammad Hamza, Chishti, Muhammad Haris, Ismail, Muhammad Izzat Shufphi, Kashif, Muhammad, Khalid, Muhammad, Mansoor Iqbal, Muhammad, Bin Khalid, Muhammad Moaz, Rafique, Muhammad Nouman, Raheem, Muhammad, Khalid, Muhammad Saud, Usama, Muhammad, Usman Malik, Muhammad, Saqib, Muhammad Waleed, Elhadi, Muhammed, Ateş, Muhammed Ikbal, Demirpolat, Muhammed Taha, Ergenç, Muhammer, Bello, Muideen, Kulimbet, Mukhtar, Nyirenda, Mulinda, Taeme, Mulugeta, Denini, Muna, Aziz, Munazzah, Yahaya, Mundashiru, Eugene, Muneza, Amadu, Munira, Chauhan, Munish, Acar, Murat, Teressa, Murti, Dauphin, Muryango, Arafat, Musa, Althomali, Musab, Rayzah, Musaed, Husain, Musharraf, Tolani, Musliu Adetola, Abu Jayyab, Mustafa, Al-Attraqchi, Mustafa, Kara, Mustafa Alper, Seker, Mustafa Ege, Gün, Mustafa, Hamed, Mustafa, Mehanny, Mustafa, Oncel, Mustafa, Sabri Massadi, Mustafa, Uyanik, Mustafa Safa, Uzunoglu, Mustafa Yener, Abdullahi, Mustapha, Saidani, Mustapha, Nofal, Mutaz, San, Myat, Ishak, Myrna, Keramida, Myrto D., Nik Burhanuddin, N.M. Syahrin, Talat, Nabila, Shehata, Nada, Alasbahi, Nadeen, Marcos, Nádia, Al Amri, Nadiah, Absy, Nadine, Parker, Naeelah, Lindi, Naeimah, Omer, Nafisa, Papadogianni, Nafsika, Rawal, Nagendra, Ismaiel, Nahar, Ben Hasan, Najat, Albahloul, Najla, Gokhare Viswanath, Nakul, Srinivas, Namitha, Christian, Nana Ama, Obuobi, Nana Kwame Asare, Beharry, Naomi, Yousefzadeh Kandevani, Naser, Alnamari, Nashwan, Oyelowo, Nasir, Oloko, Nasirudeen, Alzerwi, Nasser, Mosbah, Nasser, Shulman, Nastassia, Andrade, Natacha, Boumas, Natacha, Cobeño Tamayo, Natalia, Barrera Lopez, Natalia Guadalupe, Palamara, Natalia, Blencowe, Natalie, Marzouqa, Natalie, Blencowe, Natalie S, Salgadoe, Natalie, Techapongsatorn, Nathakorn, Paez, Nathaly, Ekwo, Nathan, Saini, Navdeep, Malik, Naveed Akhtar, Sharma, Naveen, Kumar, Navin, Chaudhry, Navneet Kumar, Karimbocus, Nawaaz, Rasool, Nazeerah, Lodhi, Nazia, Kavak, Nazli, Ildephonse, Ndayiragije, Diomede, Nduwimana, Bayleyegn, Nebiyou S., S.Bayleyegn, Nebiyou, Jović, Nediljko, Mosleh, Neebal, Aruldas, Neerav, Kapur, Neeti, Paul Sigamony, Negine Paul, Karthikeyan, Neha, Tabatabaian, Nelia, Affram, Nelson, Agboadoh, Nelson, Tran, Nelson, Lalovic, Nenad, Agugua-Obianyo, Nene, Kullab, Nermen, Lahmer, Nesrin, Raiq, Neven, Soldo, Neven, Spiteri, Neville, Chen, Nevin, Al Rabadi, Nezar, Christian, Ngarambe, Cabrel, Ngongang Ngansop, Leonelle Lore, Nguefack Noudem, Furbetta, Niccolò, Ensor, Nicholas, Tsantikos, Nick, Seeger, Nico, Cillara, Nicola, Eardley, Nicola, Petrarota, Nicola, Tartaglia, Nicola, Feijoo, Nicolas, Finocchiaro, Nicole, Koter, Nicole, De Santis, Nicolò, Fabbri, Nicolò, Schiavon, Nicolò, Tamini, Nicolò, Sharma, Nidhi, Sánchez Fuentes, Nieves, Solomon, Nigus, Bugdayci, Nihat, Lekiashvili, Nika, Gupta, Nikhil, Narain, Nikhil, Uttam, Nikita, Kłos, Nikola, Ververidis, Nikolaos Adrianos, Arkadopoulos, Nikolaos, Dimitrokallis, Nikolaos, Garmpis, Nikolaos, Gouvas, Nikolaos, Kalampokis, Nikolaos, Kopanakis, Nikolaos, Kydonakis, Nikolaos, Machairas, Nikolaos, Memos, Nikolaos, Michalopoulos, Nikolaos, Mathioudakis, Nikolaos Nestor, Roukounakis, Nikolaos, Stamos, Nikolaos, Tasis, Nikolaos, Tsakiridis, Nikolaos, Vlachakos, Nikolaos, Zampitis, Nikolaos, Kouzakos, Nikolas, Börner, Nikolaus, Dimitriou, Nikoletta, Dafnios, Nikos, Banerjee, Niladri, Klammer, Nils, Maharjan, Nima, Rabai, Nimah, Oscar, Nimpaye, Harrison, Nina, Kheyrbek, Nina, Kansakar, Nirajan, Bhat, Nisar, Krishnappa, Nischal, Pahuja, Nisha, Paul Ambrose, Nitin, Renovat, Niyongabo, Musawa, Nizar, Nwanne, Njideka, Steve, Nkurunziza, Chidumije, Nnaemeka, Nwafulume, Nnaemeka, Celestine, Nnamani, Duru, Nnamdi, López Bernal, Noelia Esthela, Laquatra, Noemi, Pasqua, Noemi, Awwad, Noor Al-Deen, Ali, Nora, Hielscher, Nora, Trabulsi, Nora, Hüser, Norbert, Muñoz Montes, Norberto, Eshak, Norma-Sol, Rajab, Nosaiba, Lahnaoui, Nouhaila, Ouachou, Nouhaila, Ali, Nour, Dadoush, Nour, Fazili, Noureen, Theophile, Ntahompagaze, Ntanzi, Ntuthuko, Bibila, Nubia Samuel, Alwaer, Nuhay, Naabo, Nuhu, Jiagge, Nuna, Freitas Oliveira, Nuno Miguel, Pratas, Nuno, Morricone, Nunzia, Franco, Nunzio Francesco, Binti Yusri, Nur Aima, Ramli, Nur Natasya, Abd Ghani, Nur Suriyana, Umar, Nura, Aly, Nuran Khaled, Lakhanov, Nurgali, Al-Hroub, Nurhan, Kiziltoprak, Nurhilal, Chavarrias, Nuria, Maulenov, Nurlan, Akinbami, Nurudeen, Abdulraheem, Nurudeen Toyin, Karunaratne, Nuwanthika, Jeannette, Nyiransabiyera, Altobaishat, Obieda, Egwuonwu, Ochonma Amobi, Enciu, Octavian, Cohen-Arazi, Oded, Pheiffer, Odette, Okoye, Odili Aloysius, Omoike, Ofure, čančar, Ognjen, Ekwunife, Okechukwu Hyginus, Emuze, Okundayo, Eljizoly, Ola Abdallah, Al Hamdani, Ola, Emadeldeen, Ola, Morgan, Ola, Olajumoke, Oladapo, Popoola, Olakunle, Ajiboye, Olalekan, Olasehinde, Olalekan, Jolayemi, Olamide, Babatunde, Olanrewaju, Balogun, Olanrewaju, Olajide, Olawumi, Lisin, Oleg, Bellou, Olga, Jurić, Oliver, Ladlow, Oliver, Whitehurst, Oliver, Camilleri, Olivia, Montaño Angeles, Olivia, Pryer, Olivia, Ray, Olivia, Gabom, Olivier, Ndizeye, Olivier, Ojewuyi, Olufemi, Oluyemi, Olukayode, Elebute, Olumide, Ogunsua, Oluseyi, Fasiku, Olushola Kayode, Fasoro, Olusola, Fatudimu, Oluwafemi, Osunlusi, Oluwafemi, Owolanke, Oluwagbenga, Oso, Oluwarotimi, Alaba, Oluwaseun, Ojo, Oluwaseun, Oluseye, Oluwaseun, Oyinloye, Oluwaseun, Al Alyani, Omaima, Okrah, Omane, Agha, Omar, Al-Fahel, Omar, Almomani, Omar, Alruwaili, Omar, Ibarra, Omar, Ibrahim, Omar, Khalil, Omar, Kouli, Omar, Lima Azurdia, Omar, Mansour, Omar, Mohamed Mokbel, Omar, Omar, Omar, Bedak, Omer, Ozkan, Omer Faruk, Yalkın, Omer, Mohamed, Omnia, Ayandipo, Omobolaji, Faboya, Omolara, Williams, Omolara Modupe, Irowa, Omorodion, Attawodi, Onuche, Salako, Opeyemi, Ioannidis, Orestis, Agcaoglu, Orhan, Martin Sole, Oriol, Webster, Orla, Abouhiekal, Osama, Al Shaqran, Osama, Bahsas-Zaky, Osama, Nubi, Osama Gamal, Hany, Osama, Matar, Osama, Mahafdah, Osama R., Sarhan, Osama, Osagie, Osasumwen, Soublett Rivas, Óscar Alexander, Gülcicek, Osman Bilgin, Cuenca Torres, Osmar Manuel, Carpineto Samorani, Osvaldo, Arsalan, Othman, Coyoy-Gaitán, Otto, Nouhail, Oumaima, Boujidi, Oumama, Dicko, Ousmane A A, Ahmad, Owais, Christianah, Oyegbola, Küpçüoğlu, Özge, Zanbak Mutlu, Özgecan Pırıl, Chadha, P, Prabhu, P Santosh, Carmignani, Pablo, Arteaga Asensio, Pablo Cesar, Del Val Ruiz, Pablo, Royo Dachary, Pablo, Sancho Pardo, Pablo, Vásquez, Pablo, Sukhvibul, Pakkapol, Assouto, Pamphile, Evangelou, Panagiota, Dorovinis, Panagiotis, Kapsampelis, Panagiotis, Kokoropoulos, Panagiotis, Kostoglou, Panagiotis, Manikis, Panagiotis, Sakarellos, Panagiotis, Lykoudis, Panagis, Kumar, Pankaj, Patel, Panna, Paraskeva, Panoraia, Vassiliu, Panteleimon, Antonakis, Pantelis, De Nardi, Paola, Marongiu, Paola, Kamenova, Paolina, Venturelli, Paolina, Belotti, Paolo, Ubiali, Paolo, Grivas, Paraskevas, Stamopoulos, Paraskevas, Chatzikomnitsa, Paraskevi, Trakosari, Paraskevi, Tekam Wadje, Parfait Stéphane, Manjunath, Parikshith, Gupta, Pariza, Dhamija, Parth, Haque, Parvez, Haque, Parvez David, Haque, Parwez Waseemul, Nze Obiang, Pascal Christian, Probst, Pascal, Chiacchio, Pasquale, Cianci, Pasquale, Favoriti, Pasqualino, Koggoh, Patience, Bernardo, Patrícia, Omwansa, Patricia, Serrano Méndez, Patricia, Owens, Patrick, Tang, Patrick, Walker, Patrick, Chimezie Andrew, Paul, Trinity, Paul, Wilson, Paul, George, Paul Yohan, Artigot, Paula, Devlin, Paula, Vladova, Paulina, Cabrera Rivera, Paulo Andrés, Arunachalam, Pavai, Glushkov, Pavel, Levíček, Pavel, Lal, Pawanindra, Panahi, Pedram, David Santos, Pedro, Laranjo, Pedro, Palazon Bellver, Pedro, Rego Ponte, Pedro, Salas Núñez, Pedro, Sornoza, Pedro, Chloropoulou, Pelagia, Correia, Penélope, Limani, Perparim, Agbonrofo, Peter, Boateng, Peter Agyekum, Elemile, Peter, Francúz, Peter, Riedl, Peter, Tschann, Peter, Yuide, Peter, Hudáč, Petr, Ostruszka, Petr, Zimmermann, Petra, Nambala, Petrus, Shimbulu, Petrus, Thomas, Phebey A, Kumassah, Philemon, Alexander, Philip, Mensah, Philip, Taah-Amoako, Philip, Horvath, Philipp, Garcia-Dubus, Philippe, Holt, Phillip, Lapolla, Pierfrancesco, Cicerchia, Pierfranco Maria, Palumbo, Piergaspare, Anoldo, Pietro, Calò, Pietro Giorgio, Grondona, Pietro, Masseria, Pietro, Riva, Pietro, Milewski, Piotr Jan, Kowalewski, Piotr, Kasetsermwiriya, Pohpdham, Patel, Poojan, Leungon, Poramet, Kaur, Prabhjot, Arya, Prafull Kumar, Shivashankar, Pranav, Kothari, Prashant, Dummala, Prashanth, Shukla, Prateek, John, Pravin, Adebayo, Precious, Andrejevic, Predrag, Thambi, Prem, Anandan, Premkumar, Idjerhe, Prince, Boateng, Prince Kwame, Ntem, Prince, Waghchoure, Prince, Yeboah Owusu, Prince, Moodley, Priyanka, Suresh, Priyanka, Kanavidis, Prodromos, Odigie, Vincent, Christodoulou, Prokopis, Nashidengo, Pueya Rashid, Patel, Puja, Dolatzay, Qayom Khan, Mashlah, Qusai, Sabbah, Qutaiba, Sethi, R, Robitsek, R. Jonathan, Jubran, Ra'Ed, Raheem Attallah Al-obaidy, Raad, Michael, Rabha, Abela, Rachel, Colbran, Rachel, Geow, Rachel, Titcombe, Rachel, Soglonou, Rachelle, Ait Ben Addi, Rachid, Jayakrishnan, Radhakrishnan, Acharya, Radhika, Salim, Radhwan, Guzmán Lambert, Radisnay, Donchev, Radoslav, Drasovean, Radu, Andreou, Rafael, Perez-Soto, Rafael Humberto, Santana Ortiz, Rafael, Villalobos Mori, Rafael, Sokratous, Rafailia, Smolinski Kurek, Rafal Ludwik, Solecki, Rafal, Basile, Raffaele, Abd Elkareem, Raghad, Yousef Yassin, Raghad, Faisal, Raghdah, Abd Alkareem, Rahaf, Hegy, Rahma, Jaba'Teh, Rahmah, Sharma, Rahul Deo, Gupta, Rahul, Saxena, Rahul, Sinha, Rahul, Varshney, Rahul, Ripoll I Palmés, Raimon, Lunevicius, Raimundas, Raghunath, Rajat, Redkar, Rajeev, Sharma, Rajeev, Philip Sridhar, Rajeevan, Krishna Raj, Rajesh, Nathani, Rajesh, Kottayasamy Seenivasagam, Rajkumar, Ahmed, Rakesh, Handa, Rakesh, Vakil, Rakesh, Armah, Ralph, Attaf, Ram, Elazary, Ram, Alkhatib, Rama, Alzu'Bi, Rama, Raddad, Rama, Kaur, Ramanjot, Kaur, Ramanpreet, Nataraja, Ramesh, Hussam Yacoub Hattar, Ramez, Ben Hmida, Rami, Chaudhary, Ramkaran, Ramirez Calas, Ramon Andres, Soliva Domínguez, Ramón, Ghaleb, Ramzi, Batir, Rana, Haddad, Rana, Sugair, Rana, Suleiman, Rand, Perera, Ranga, Altayargh, Rania, Joumaa, Ranim, Ellawala, Ranjith, Elaifia, Rany, Eloka, Raphael, Hernandez Rodriguez, Raquel Angelica, Diaz, Raquel, Lalanda, Raquel, Rodríguez-Uria, Raquel, Olatunji, Rasheed, Wani, Rauf, Díaz Pedrero, Raúl, Ubiñas, Raul, Lertnamvongwan, Raunika, Hiary, Rawan, Almahadin, Rawan Khalid Za'al, Radwan, Rawan, Issa, Rawand, Dar, Rayees Ahmad, Nyirenda, Raymond, Eghonghon, Raymond Atah, Oppong, Raymond, Govindaraju, Rayshini, Kalouk, Razan, Abad, Rebeca, Akankoatuesi Apatewen, Rebecca, Bradley, Rebecca, Enejo, Rebecca Eboshogwe, Hauwa Sani, Rebecca, Jurdon, Rebecca, Sönmez, Recep Erçin, Belouz, Reda, Abhinaya, Reddy, Abu Salah, Reem, Alatawi, Reem, Alqahtani, Reem, Sayad, Reem, Adel Diab, Rehab, Függer, Reinhold, Madi, Reman, Pajtak, Renata, Barradas, Renato, Díaz-Ruiz, Renato, Patrone, Renato, Palacios Huatuco, René M., Casma Bustamante, Renzo, Ranadive, Reuben Rajappa, Askari, Reza, Sulce, Rezart, Liang, Rhea, Tummon, Rhea, Roberts, Rhianna, Mcclen, Rhys, Duvenage, Riaan, Kattini, Ribal, Alvarado Hurtado, Ricardo, Tenfen Carneiro, Ricardo Augusto, Castro Lara, Ricardo Jesús, Silva Borges, Ricardo, Souto, Ricardo, Vaz Pereira, Ricardo, Barone, Riccardo, Fratarcangeli, Riccardo, Guercio, Riccardo, Magarini, Riccardo, Malatesti, Riccardo, Tripathi, Richa, Crawford, Richard, Kpangkpari, Richard, Marlin, Richard, McGee, Richard, Nesco, Richard, Spence, Richard, Akpaka, Richfield, Alinde, Rigobert, Khalid, Rija, Sato, Rikiya, Kitamura, Riley, Baldan, Rino, Agyei Boakye, Rita, Branquinho, Rita, Hleyhel, Rita, Miranda Pera, Rita, Pinheiro Duque, Rita, Ribeiro Dias, Rita, Bhatia, Riya, Rabah, Rnad, Damseh, Ro'Ya, Alzughayyar, Roa, Daradkeh, Roa'A, Bassam, Roaa, Refaie, Roaa, Bethune, Rob, Elshennawy, Roba, Cachia, Robert, Franz, Robert, Grützmann, Robert, Kibuuka, Robert, Laskowski, Robert, Mazurkiewicz, Robert, Munyaneza, Robert, Parker, Robert, Sagoe, Robert, Sucher, Robert, Granata, Roberta, Ruccella, Roberta, Tutino, Roberta, Badra, Roberto, Mares País, Roberto, Sampietro, Roberto, Scola, Roberto, Mackay, Robyn, Tumolo, Rocco, Figueroa, Rodrigo, Doamba, Rodrigue, Habib, Rohan, Gujjuri, Rohan R, Anjum T Siddeek, Rohik, Mittal, Rohin, Kumar, Rohit, Goudou, Roland, Rüdrich, Roland, Senin, Roman, Moukarzel, Romika, Ferlini, Romina Lorena, Ribeiro, Rómulo, Schmidt-Branden, Romy, Zerna Encalada, Ronald, Ferreira Acosta, Rosa, Lopatriello, Rosanna, Perez, Rosario, Hall, Rosie, Alloni, Rossana, Arena, Rossella, Gioco, Rossella, Polo, Roxy, Shen, Ru, Doherty, Ruairi, Rivas, Ruben, Oppong-Amoah, Ruby, Ooi, Rucira, Radojković, Rudolf, Herrera, Rudy, Bernardino, Rui, Ediru, Rukevwe, Al Shehhi, Ruqaiya, Masri, Ruqaya, Hodgson, Russell, Azimov, Rustam, Martínez Díaz, Rut, Santos Pereira, Rute, Naidoo, Ruvashni, Noor, Ruzaimie, Campbell, Ryan, Khalil, Ryta, Chigblo, S. 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Sharitha, Laura, Sharon, Shanker, Shashwat, Ababneh, Shatha, Gilbert, Shaun, Kenworthy, Shaunna, Ng, Shawn Hong Ming, Mackenzie, Shawn, Salindera, Shehnarz, Khattak, Shehrbano, Loke, Sheih Nee, Manzoor, Sheikh Viqar, Alwardi, Sheikha, Allam, Shereen, Tawfik, Sherifa, Francis, Shikha, Cai, Shirley, Dindyal, Shiva, Pandya, Shivangi, Chopra, Shreya, Ingley, Shreya, Kulkarni, Shrirang, Kosna, Shuba, Nayak, Shubhalaxmi, Ahuja, Shubham, Hariharan, Shubhang, Karuppusamy Krishnasamy, Shyam, Khare, Siddhant, Handa, Siddhartha, Amin Omar Alsiddig, Siddig, Alqurashi, Siddiga, Al-Tahayneh, Sief-Addeen, Sibiya, Silindokuhle, Perretta, Silvana, Ibarra Camargo, Silvia Alejandra, Montisci, Silvia, Mungo, Silvia, Puddu, Silvia, Severi, Silvia, Agudelo Mendoza, Silvia Valentina, Makkai-Popa, Silviu Tiberiu, Boyes, Simon, Monkhouse, Simon, Stock, simon, Alberti, Simona, Meneghini, Simona, Giudici, Simone, Guadagni, Simone, Birolo, Simone Lorenzo, Novello, Simone, Oliveira, Simone, Gumede, Simphiwe, Dhole, Simran, Budhwani, Simran Saleem, Ramjit, Sinead, Yumurtacilar, Sinem, Mahendra, Sirigi Naga, Abeykoon, Sithira, Moh Pauzi, Siti Farhan, Rajendra, Sittampalam, Sundararajan, Siva, Gananadha, Sivakumar, Kamarajah, Sivesh K, Marawu, Siyasanga, Basu, Sk, Hassan, Sleman, Reddy, Snigdha Mettu, Anaya Sanchez, Sofia, Gaspar Reis, Sofia, Gomez, Sofía, Gamba, Sofia Lucia, Pimentel Morais, Sofia, Ashry, Soha, Abdullateef, Sohaila, Bandyopadhyay, Soham, Samadi, Soheil, Pathan, Sohilkhan R., Lakew, Solomon, Basu, Somprakas, Ohri, Sonali, Alonso Marcos, Sonia, Amoza Pais, Sonia, Fortuna Martins, Sónia, Gill, Sonia, Matthiess, Sonia, Sabbatini, Sonia, Soto Schütte, Sonia, Engel, Sophie, Eam, Sothseyhakmonique, Botaitis, Sotirios, Lawani, Souliath, Jamil, Soumaya, Kondpan, Sourav, Oum, Sovannarith, Govender, Sovishnee, Christodoulou, Spyridon, Davakis, Spyridon, Vernadakis, Spyridon, Gkogkos, Spyros, Gobishangar, Sreekanthan, Suresh, Sreelakshmi, Vembar, Sridhar, M, Srikanth, Abdelrasoul Elnour Ismail, Srraa, Zourntou, Stamatina-Emmanouela, Nwabuoku, Stanley Emeka, Ideh, Stanley, Charitonos, Stavria, Liapis, Stavros Chrysovalantis, Faber, Stefan, Piccioni, Stefania Angela, Romano, Stefania, Silvestre, Stefania, Jarmusch, Stefanie, Soelling, Stefanie, Cardelli, Stefano, Chaifouroosh Mamagany, Stefano, Corso, Stefano, Basso, Stefano Maria Massimiliano, Megna, Stefano, Bitsianis, Stefanos, Tsatsos, Stefanos, Morales, Steffanía, Gerdes, Stephan, Göller, Stephanie, Hanna, Stephanie, Tabiri, Stephen, Agana, Stephen, Theivendran, Stephen Arthur, Kache, Stephen, Knight, Stephen R, Smith, Stephen, Stonelake, Stephen, Wrenn, Stephen, Gopaul, Steven, Vederaki, Styliani, Kapiris, Stylianos, Kykalos, Stylianos, Hlaing, Su Su, Chia, Su Yin Denise, Abu Khousa, Suad, M. Udwan, Suad, Raul, Subrat, Chase, Suchita, Nair, Sudharrshan, Joseph, Sudhir, Singh, Sudhir Kumar, Singh, Sudhir, Timmalah, Suhaylah, Alsuwiyah, Suhir, Thalgaspitiya, Sujeewa Priyantha Bandara, Sellahewa, Sujeewa, Neogi, Sujoy, Burger, Sule, Polat, Süleyman, Alkadi, Sulman, Asiri, Sultan, Otho, Sumaira, Mewa Kinoo, Suman, Ebrahim, Sumayyah, Tontus, Sumeyya, Midya, Sumit, Thuraisamy Sarma, Sundaramoorthy Iyer, Payyanur Thotan, Sundeep, Kumar Venkatappa, Sunil, Techapongsatorn, Suphakarn, Kaur, Supreet, Jp, Supritha, Tan, Suqi, Djote, Surafel Mulatu, Surendran, Suraj, Singh, Surendra, Chilaka, Suresh, Lee, Susan, Henriques, Susana, Giridaran, Suseendirarajah, Achugatla, Sushma, Kumar, Suvam, Brincat, Svetlana, Deshpande, Swati, Batista, Sylvia, Akharaekpanya, Tachporn, Moges, Tadesse Girma, Türkmen, Taha Berkay, Alhaj Hasan, Taima, Alshawabkeh, Taima', Majed, Taima', Lawal, Taiwo Akeem, Ibiyeye, Taiye Taibat, Rashid, Tajamul, Košir Božič, Tajda, Mohammed, Tajudeen, Khewater, Talal, Abelman, Talia, Al Barhi, Tamadher, Mogne, Tamiris, Salazar-Lorenzana, Tania Abril, Akter, Tania, Gómez Sanz, Tania, Motiwala, Tanmay, Valizadeh Elizeh, Tanya, Almahdi, Tanzeel, Albushary, Tanzel Alrahman, Abdulrahman, Taofeeq, Finlay, Tara, Chouari, Tarak, Awad, Tarek, Sabra, Tarek, M. Abubasheer, Tareq, Alhusban, Tariq, Yılmaz, Tarık Emre, Aloqaili, Tasneem, Aldirawi, Tayef, Karahasanoğlu, Tayfun, Gülşen, Taygun, Jemal, Tebarek, Nadeem, Tehmina, Singh, Tejinder Paul, Alinger, Temsula, Longkumer, Temsutoshi, Lo, Terence, Gimenez Maurel, Teresa, Uprak, Tevfik Kıvılcım, Petropoulou, Thalia, Rawther, Thampi, Techapongsatorn, Thawin, Manickam, Thendral, Padioti, Theodora, Kozonis, Theodoros, Sidiropoulos, Theodoros, Tsirlis, Theodoros, Theodosopoulos, Theodosios, Hessou, Thierry Kinnongni, Uiyapat, Thitapon, Agyen, Thomas, Harris, Thomas, Hugh, Thomas J, Jorgensen, Thomas W., Theivendrampillai, Thrshegan, Pham, Thuy Vy, Branco, Tiago, Nagwamutse, Tijjani Nasiru, Tony V, Tina, Devabalan Koil, Titus, Pilia, Tiziana, Abdulmola, Tmador Mahmed Ali, Oyeyemi, Tobiloba, Kebede, Tolera, Ibarra-Hurtado, Tomás Ramón, Reichelt, Tomas, Gach, Tomasz, Stefura, Tomasz, Wojewoda, Tomasz, Soric, Tomislav, Risteski, Toni, Tridip, Tridip Dutta Baruah, Yotsov, Tsanko, Doma Bhutia, Tshering, Girma, Tsion, Kwan, Tsun Yu, Ivanov, Tsvetomir, Iahmo, TT, Ashkar, Tuleen, Mabogoane, Tumi, Olobatoke, Tunde, Sholadoye, Tunde T., Mishra, Tushar Subhadarshan, Parker, Tyla, Ezomike, Uchechukwu, Dilibe, Uchenna, Kumbhar, Uday, Una, Uduak-Abasi, Grossi, Ugo, Ezidiegwu, Ugochukwu, Edith, Ugwuoke, Daspal, Ujjwal, Kalu, Ukoha Agwu, Dietz, Ulrich, Ronellenfitsch, Ulrich, Wirth, Ulrich, Abdullah, Umar, Rivolta, Umberto, Jayarajah, Umesh, Kanyan Kassim, Umu-Hera, Govindan, Unnikrishnan, Fernandes, Urânia, Akram, Usman, Mohammed Bello, Usman, Omara, Usra, Naidoo, Uvarasen, Mahendravarman, Vaishnaivy, Negoita, Valentina Madalina, Mariottini, Valentina, Murzi, Valentina, Zucchini, Valentina, Agbakwuru, Valentine, Armenta Tapia, Valeria Estefania, Gentilino, Valerio, Borgogni, Vanessa, Ng, Vanessa, Wolfschluckner, Vanessa, Silvestri, Vania, Žufić, Vanja, Gunasaegaram, Varman, Kamalathevan, Vasan, Pillay, Vasanthan, Neykov, Vasil, Kalles, Vasileios, Mousafeiris, Vasileios, Papadopoulos, Vasileios, Tsaousis, Vasileios, Tselepidis, Vasileios, Vougas, Vasileios, Georgilaki, Vasiliki, Nikolaou, Vasiliki, Themelidi, Vasiliki, Manchev, Vassil, Ioannou, Veatriki, Jha, Vedant Shekhar, Dragisic, Vedran, Sutharshan, Vengadasalam, Alonso, Veronica, Brocco, Veronica, Ongil Rodríguez, Verónica, Schirinzi, Veronica, Budyakova, Veronika, Naunova, Vesna, Panduro-Correa, Vicky, Ruiz López, Víctor Andrés, Bill, Victor, Dassah, Victor, Gonzabay, Víctor Eduardo, Etwire, Victor, Modekwe, Victor, Serna-Alarcon, Victor, De Donato, Victor Ugo, Duque Mallén, Victoria, Liu, Victoria, Sharma, Vidushi, Kumar, Vijaya, Muralidharan, Vijayaragavan, Kakotkin, Viktor, Enemuo, Vincent, Kudoh, Vincent, Osoka, Vincent, Siepaal, Vincent, Granata, Vincenza, Dinuzzi, Vincenza Paola, Lizzi, Vincenzo, Ricchiuti, Vincenzo, Mosca, Vinicio, Kanna D, Vinoth, Nair, Vipin Venugopal, Ledda, Virginia, Michael, Vishal, Singh, Vishavdeep, Govindasamy, Vishendran, Kollengode, Viswanathan V, Giordano, Vittoria, Morinelli, Vittoria, Lin, Vivian, Cuk, Vladica, Cijan, Vladimir, Çalik, Volkan, Bakshi, Vrushank, Ten, Vyacheslav, Ratheesh, Vysakh, Alsado, Wael, Mayo, Wafik, Yang, Wah, Rehman, Wajeeh Ur, Abbas, Walaa, Al-Khyatt, Waleed, Mabood, Waleed, Santucci, Walter, Yew, Wan Ting, Tahir, Warda, De Silva, Warusha Dhammika Dulantha, Wijenayake, Wasantha, Almadhoun, Waseem J.N., Alhroub, Wasef, Ebrahim, Wesam, Jabłoński, Wiktor, Krawczyk, Wiktor, Bhatti, William, Lai, William Kwan Ho, Petrushnko, Wilson, Afedo, Wisdom, Kasetsermwiriya, Wisit, Serednicki, Wojciech, Wysocki, Wojciech, Zerefa, Wondwossen Amtataw, Vagena, Xanthoula, Tarrado, Xavier, Papazarkadas, Xenofon, Po, Xiang Yuen, Ouadi, Yacine, Myla, Yacob, Haido, Yacoub, Hasan, Yafea, Karataş, Yağmur, Carpio Colmenares, Yahaira, Galvañ Félix, Yaiza, Balogun, Yakub Lekan, Maktabi, Yaman, Nerabani, Yaman, Fulgence, Yamuremye, De Silva, Yannick, Asar, Yara, Samer Morsy, Yara, Ghaleb, Yasameen Saif Saeed Mohammed, Vashishth, Yash, M S, Yashas, Manickchund, Yashoda, Sakaray, Yashwant, Kara, Yasin, Tosun, Yasin, Zwain, Yasir, Farag, Yasmeen, Jedidi, Yasmine, Seada, Yasmine, Aldebasi, Yasser, Ashour, Yasser, Badr, Yassin, Sarpong, Yaw, Alawneh, Yazan, Aung, Yee Lay, Orabi, Yehia, Lam, Yick Ho, Şen, Yigit Kaan, Koyluoglu, Yilmaz Onat, Huang, Yining, Mintz, Yoav, Perez, Yocarli, Chamara, Yohan, Melkamu, Yohannes, Maestre González, Yolanda, Dean, Yomna, Metaferia, Yonas Yilma, Malki, Yosra, Mohamed, Younis, A. Omar, Yousef, Alhammoud, Yousef, Allaoua, Yousef, Tanas, Yousef, El Okazy, Youssef, Kerolous, Youssef, Mohamed, Youssef, Al-Junaidi, Youssuf, Lakdawala, Yousuf, Lu, Yuann, Asano, Yukio, Altinel, Yuksel, Aktimur, Yunus Emre, Fishman, Yuri, Kudryavcev, Yurii, Tandoğan, Yusuf Iskender, Razafimandimby, Yves Michaël, Adofo-Asamoah, Yvonne, Şenol, Zafer, Odeh, Zahra, Benamrouche, Zahra Rayane, Alkhaier, Zahraa, Al-Sheikh Ali, Zaid, Zaher, Zain Aldin, Alnajjar, Zaina, Al-Balushi, Zainab, Alkhuzaie, Zainab, Khraim, Zakaria, Toutounji, Zakaria, Djama, Zakarya, Farraj, Zamil, Shah, Zamir Ahmad, Khan, Zara, Khan, Zarnigar, Abo Alarous, Zayn Alabden, Asaad, Zaynab, Demetrashvili, Zaza, Lorenc, Zbigniew, Brekalo, Zdrinko, Hannouneh, Zein Alabdin, Robertson, Zelda, Bady, Zeyad, Durna, Zeynep, Wong, Zhen Yu, Fozo, Zien Alabdin, Klib, Zienab, Chin, Ziling, Tamou, Zime Farid, Johnson, Zina, Shabello, Ziyad, Orzeszko, Zofia, Aljalabi, Zohal, Al-Azher El-Hamel, Zohour, Karampotaki, Zoi Rafaila, Valera Sanchez, Zoraida, Matkovic, Zoran, Azhar, Zubair, Qureshi, Zubaria, Correa López, Zulema Margarita, Balciscueta, Zutoia, Musilová, Zuzana, Katusic, Zvonimir, Osama, Zyad, and Dauksa, Zygimantas
Published: 2024
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188. Implementation of Non-Gaussian Motion Models Within Stone Soup.

Author: Zhen Yuen Chong, Henry Pritchett, Qing Li 0033, Runze Gan, Yaman Kindap, and Simon J. Godsill
Published: 2024
Full Text: View/download PDF

189. Audio-Visual Speech Representation Expert for Enhanced Talking Face Video Generation and Evaluation.

Author: Dogucan Yaman, Fevziye Irem Eyiokur, Leonard Bärmann, Seymanur Akti, Hazim Kemal Ekenel, and Alexander Waibel
Published: 2024
Full Text: View/download PDF

190. VLP: Vision Language Planning for Autonomous Driving.

Author: Chenbin Pan, Burhaneddin Yaman, Tommaso Nesti, Abhirup Mallik, Alessandro Gabriele Allievi, Senem Velipasalar, and Liu Ren
Published: 2024
Full Text: View/download PDF

191. CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow.

Author: Chenbin Pan, Burhaneddin Yaman, Senem Velipasalar, and Liu Ren
Published: 2024
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192. Enabling Restorative Hawaiian Futurism via a Tabletop Role-Playing Game and Digital Ha'i Mo'olelo.

Author: Rachel Baker-Ramos, Michael Parkin, Angelica Raza-Furtado, Alika Spahn Naihe, Jack Hobbs, Jeffrey Vierra, Aaron Ramirez, Chantel Rubin-Molina, Cheridean Kaaialii, Celeste Mason, Yaman Sangar, May Okihiro, and Josiah D. Hester
Published: 2024
Full Text: View/download PDF

193. Normative Requirements Operationalization with Large Language Models.

Author: Nick Feng, Lina Marsso, Sinem Getir Yaman, Isobel Standen, Yesugen Baatartogtokh, Reem Ayad, Victória Oldemburgo de Mello, Beverley A. Townsend, Hanne Bartels, Ana Cavalcanti 0001, Radu Calinescu, and Marsha Chechik
Published: 2024
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194. Classification Method of Plants with Support Vector Machine (SVM) Using Local Binary Gaussian Model (LBGP) for Smart Agriculture.

Author: Irfan Kilic and Orhan Yaman
Published: 2024
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195. Classification of Spyware from Network Packets with Decision Trees Using Recursive Feature Elimination (RFE).

Author: Irfan Kilic and Orhan Yaman
Published: 2024
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196. The LuViRA Dataset: Synchronized Vision, Radio, and Audio Sensors for Indoor Localization.

Author: Ilayda Yaman, Guoda Tian, Martin Larsson, Patrik Persson, Michiel Sandra, Alexander Dürr, Erik Tegler, Nikhil Challa, Henrik Garde, Fredrik Tufvesson, Kalle åström, Ove Edfors, Steffen Malkowsky, and Liang Liu 0002
Published: 2024
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197. The Effect of Training Schedules on Morphological Robustness and Generalization.

Author: Edoardo Barba, Anil Yaman, and Giovanni Iacca
Published: 2024
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198. An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms.

Author: Leonardo Lucio Custode, Fabio Caraffini, Anil Yaman, and Giovanni Iacca
Published: 2024
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199. Analyzing and Debugging Normative Requirements via Satisfiability Checking.

Author: Nick Feng, Lina Marsso, Sinem Getir Yaman, Yesugen Baatartogtokh, Reem Ayad, Victória Oldemburgo de Mello, Beverley A. Townsend, Isobel Standen, Ioannis Stefanakos, Calum Imrie, Genaína Nunes Rodrigues, Ana Cavalcanti 0001, Radu Calinescu, and Marsha Chechik
Published: 2024
Full Text: View/download PDF

200. ParsyBot: Chatbot for Baskent University Related FAQs.

Author: Zeynep Karkiner, Begum Yaman, Begum Zengin, Feride Nursena Cavli, and Mustafa Sert
Published: 2024
Full Text: View/download PDF

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