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1,973 results on '"Mahfoud, A."'

1. Histopathology image embedding based on foundation models features aggregation for patient treatment response prediction

Author

Guetarni, Bilel, Windal, Feryal, Benhabiles, Halim, Chaibi, Mahfoud, Dubois, Romain, Leteurtre, Emmanuelle, and Collard, Dominique

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Predicting the response of a patient to a cancer treatment is of high interest. Nonetheless, this task is still challenging from a medical point of view due to the complexity of the interaction between the patient organism and the considered treatment. Recent works on foundation models pre-trained with self-supervised learning on large-scale unlabeled histopathology datasets have opened a new direction towards the development of new methods for cancer diagnosis related tasks. In this article, we propose a novel methodology for predicting Diffuse Large B-Cell Lymphoma patients treatment response from Whole Slide Images. Our method exploits several foundation models as feature extractors to obtain a local representation of the image corresponding to a small region of the tissue, then, a global representation of the image is obtained by aggregating these local representations using attention-based Multiple Instance Learning. Our experimental study conducted on a dataset of 152 patients, shows the promising results of our methodology, notably by highlighting the advantage of using foundation models compared to conventional ImageNet pre-training. Moreover, the obtained results clearly demonstrates the potential of foundation models for characterizing histopathology images and generating more suited semantic representation for this task., Comment: Accepted at MICCAI 2024 workshop MOVI

Published
2024

2. Dielectric Fano Nanoantennas for Enabling Sub-Nanosecond Lifetimes in NV-based Single Photon Emitters

Author

An, Shu, Kalashnikov, Dmitry, Shi, Wenqiao, Mahfoud, Zackaria, Chew, Ah Bian, Liu, Yan, Wu, Jing, Zhu, Di, Gao, Weibo, Qiu, Cheng-Wei, Leong, Victor, and Dong, Zhaogang

Subjects
Physics - Optics, Physics - Applied Physics, Quantum Physics
Abstract

Solid-state quantum emitters are essential sources of single photons, and enhancing their emission rates is of paramount importance for applications in quantum communications, computing, and metrology. One approach is to couple quantum emitters with resonant photonic nanostructures, where the emission rate is enhanced due to the Purcell effect. Dielectric nanoantennas are promising as they provide strong emission enhancement compared to plasmonic ones, which suffer from high Ohmic loss. Here, we designed and fabricated a dielectric Fano resonator based on a pair of silicon (Si) ellipses and a disk, which supports the mode hybridization between quasi-bound-states-in-the-continuum (quasi-BIC) and Mie resonance. We demonstrated the performance of the developed resonant system by interfacing it with single photon emitters (SPEs) based on nitrogen-vacancy (NV-) centers in nanodiamonds (NDs). We observed that the interfaced emitters have a Purcell enhancement factor of ~10, with sub-ns emission lifetime and a polarization contrast of 9. Our results indicate a promising method for developing efficient and compact single-photon sources for integrated quantum photonics applications., Comment: 20 pages, 4 figures

Published
2024

3. Domain-Specific Shorthand for Generation Based on Context-Free Grammar

Author

Kanyuka, Andriy and Mahfoud, Elias

Subjects
Computer Science - Computation and Language
Abstract

The generation of structured data in formats such as JSON, YAML and XML is a critical task in Generative AI (GenAI) applications. These formats, while widely used, contain many redundant constructs that lead to inflated token usage. This inefficiency is particularly evident when employing large language models (LLMs) like GPT-4, where generating extensive structured data incurs increased latency and operational costs. We introduce a domain-specific shorthand (DSS) format, underpinned by a context-free grammar (CFG), and demonstrate its usage to reduce the number of tokens required for structured data generation. The method involves creating a shorthand notation that captures essential elements of the output schema with fewer tokens, ensuring it can be unambiguously converted to and from its verbose form. It employs a CFG to facilitate efficient shorthand generation by the LLM, and to create parsers to translate the shorthand back into standard structured formats. The application of our approach to data visualization with LLMs demonstrates a significant (3x to 5x) reduction in generated tokens, leading to significantly lower latency and cost. This paper outlines the development of the DSS and the accompanying CFG, and the implications of this approach for GenAI applications, presenting a scalable solution to the token inefficiency problem in structured data generation.

Published
2024

5. Interdisciplinary and Collaborative Training in Neuroscience: Insights from the Human Brain Project Education Programme

Author

Geminiani, Alice, Kathrein, Judith, Yegenoglu, Alper, Vogel, Franziska, Armendariz, Marcelo, Ben-Zion, Ziv, Bogdan, Petrut Antoniu, Covelo, Joana, Diaz Pier, Marissa, Grasenick, Karin, Karasenko, Vitali, Klijn, Wouter, Kokan, Tina, Lupascu, Carmen Alina, Lührs, Anna, Mahfoud, Tara, Özden, Taylan, Pedersen, Jens Egholm, Peres, Luca, Reiten, Ingrid, Simidjievski, Nikola, Ulnicane, Inga, van der Vlag, Michiel, Zehl, Lyuba, Saria, Alois, Diaz-Pier, Sandra, and Passecker, Johannes

Published
2024
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25. A Risk-Averse Framework for Non-Stationary Stochastic Multi-Armed Bandits

Author

Alami, Reda, Mahfoud, Mohammed, and Achab, Mastane

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

In a typical stochastic multi-armed bandit problem, the objective is often to maximize the expected sum of rewards over some time horizon $T$. While the choice of a strategy that accomplishes that is optimal with no additional information, it is no longer the case when provided additional environment-specific knowledge. In particular, in areas of high volatility like healthcare or finance, a naive reward maximization approach often does not accurately capture the complexity of the learning problem and results in unreliable solutions. To tackle problems of this nature, we propose a framework of adaptive risk-aware strategies that operate in non-stationary environments. Our framework incorporates various risk measures prevalent in the literature to map multiple families of multi-armed bandit algorithms into a risk-sensitive setting. In addition, we equip the resulting algorithms with the Restarted Bayesian Online Change-Point Detection (R-BOCPD) algorithm and impose a (tunable) forced exploration strategy to detect local (per-arm) switches. We provide finite-time theoretical guarantees and an asymptotic regret bound of order $\tilde O(\sqrt{K_T T})$ up to time horizon $T$ with $K_T$ the total number of change-points. In practice, our framework compares favorably to the state-of-the-art in both synthetic and real-world environments and manages to perform efficiently with respect to both risk-sensitivity and non-stationarity.

Published
2023

26. The validity and reliability of the Arabic version of the EQ-5D in atrial fibrillation patients in a conflict country: a study from Syria

Author

Ibrahim Antoun, Alkassem Alkhayer, Majed Aljabal, Alamer Alkhayer, Peter Simon, Yaman Mahfoud, Ahmed Kotb, Joseph Barker, Akash Mavilakandy, Riyaz Somani, G Andre Ng, and Mustafa Zakkar

Subjects
Quality of life, Syria, Atrial fibrillation, Conflict, EQ-5D, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Abstract Background The EQ-5D is one of the most commonly used tools to establish health-related quality of life (QoL). EQ-5D data in atrial fibrillation (AF) patients in the Middle East are lacking. Objectives This study aims to evaluate the reliability and validity of the Arabic version of the EQ-5D in AF inpatients in Syria. Methods The study involved patients admitted to the emergency department of Tishreen’s University Hospital in Latakia with AF as the primary diagnosis between the 1st of June 2021 and the 1st of June 2023. Arabic versions of the EQ-5D, EQ-VAS and SF36 questionnaires were administered to patients. Validation was done using convergent, discriminant, and known-groups validity, while reliability was conducted using EQ-5D retesting within 2–4 weeks. Results 432 participants were included in the study with a mean ± standard deviation of 63 ± 15. Males represented 242 (56%) of the participants. All hypotheses relating EQ-5D responses to external variables were satisfied. All three validation hypotheses demonstrated that the EQ-5D had the convergent, discriminant and known group validity to assess QoL in this cohort. The intraclass correlation coefficient (ICC) for test-retest reliability ranged between 0.74 and 0.88, while Cohen’s κ ranged between 0.72 and 0.86. Cronbach’s α value for internal consistency was 0.73. Conclusion The Arabic version of EQ-5D was valid and reliable in measuring QoL in AF inpatients in Syria. This validation opens the door for more widespread use of the EQ-5D in Arabic-speaking regions, facilitating better-informed healthcare decisions and improving patient care strategies in Syria and other Middle Eastern countries.

Published
2024
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27. Decoding the diagnostic and therapeutic potential of microbiota using pan-body pan-disease microbiomics

Author

Georges P. Schmartz, Jacqueline Rehner, Madline P. Gund, Verena Keller, Leidy-Alejandra G. Molano, Stefan Rupf, Matthias Hannig, Tim Berger, Elias Flockerzi, Berthold Seitz, Sara Fleser, Sabina Schmitt-Grohé, Sandra Kalefack, Michael Zemlin, Michael Kunz, Felix Götzinger, Caroline Gevaerd, Thomas Vogt, Jörg Reichrath, Lisa Diehl, Anne Hecksteden, Tim Meyer, Christian Herr, Alexey Gurevich, Daniel Krug, Julian Hegemann, Kenan Bozhueyuek, Tobias A. M. Gulder, Chengzhang Fu, Christine Beemelmanns, Jörn M. Schattenberg, Olga V. Kalinina, Anouck Becker, Marcus Unger, Nicole Ludwig, Martina Seibert, Marie-Louise Stein, Nikolas Loka Hanna, Marie-Christin Martin, Felix Mahfoud, Marcin Krawczyk, Sören L. Becker, Rolf Müller, Robert Bals, and Andreas Keller

Subjects
Science
Abstract

Abstract The human microbiome emerges as a promising reservoir for diagnostic markers and therapeutics. Since host-associated microbiomes at various body sites differ and diseases do not occur in isolation, a comprehensive analysis strategy highlighting the full potential of microbiomes should include diverse specimen types and various diseases. To ensure robust data quality and comparability across specimen types and diseases, we employ standardized protocols to generate sequencing data from 1931 prospectively collected specimens, including from saliva, plaque, skin, throat, eye, and stool, with an average sequencing depth of 5.3 gigabases. Collected from 515 patients, these samples yield an average of 3.7 metagenomes per patient. Our results suggest significant microbial variations across diseases and specimen types, including unexpected anatomical sites. We identify 583 unexplored species-level genome bins (SGBs) of which 189 are significantly disease-associated. Of note, the existence of microbial resistance genes in one specimen was indicative of the same resistance genes in other specimens of the same patient. Annotated and previously undescribed SGBs collectively harbor 28,315 potential biosynthetic gene clusters (BGCs), with 1050 significant correlations to diseases. Our combinatorial approach identifies distinct SGBs and BGCs, emphasizing the value of pan-body pan-disease microbiomics as a source for diagnostic and therapeutic strategies.

Published
2024
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28. Viscoplastic fluid flow in pipes: A rheological study using in-situ laser Doppler velocimetry

Author

Belaid Hadj Arab, Mohamed Mahfoud, Zineeddine Louna, Karim Bekkour, and de Souza Mendes Paulo R.

Subjects
viscoplastic fluid, carbopol solutions, herschel–bulkley, ldv, flow curve, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

This experimental study focuses on exploiting laser Doppler velocimetry (LDV), a non-intrusive technique, for rheological characterization based on analyzing flows of Carbopol solutions at two distinct concentrations and two different temperatures within a pipe. The velocity profiles obtained using LDV and the pressure drops associated with each flow rate were exploited to establish the behavioral law of aqueous Carbopol solutions. Two approaches were used: the first was an analytical velocity model to fit the experimental profile, and the second used the first derivative of the experimental velocity profile and the pressure drops to reconstruct the flow curve. In addition, a third reference characterization was carried out using a rotary rheometer equipped with a vane geometry. This study’s three rheological characterization methods showed excellent agreement concerning the Herschel–Bulkley model. Finally, all the laws resulting from these three methods were validated using an empirical law relating to Darcy’s coefficient of friction.

Published
2024
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29. The Theme of Identity in Contemporary Narrative Discourse; (Narrative excerpts from the novel 'Nights Pregnant with Moons' by: Mouammar Hajeij)

Author

Mahfoud MALAOUI

Subjects
Arts in general, NX1-820, Computational linguistics. Natural language processing, P98-98.5
Abstract

Abstract : Since the beginning of humanity, peoples around the world have strived to preserve their distinctiveness and uniqueness by forming an identity that elevates the status of individuals and communities socially, nationally, and culturally. This study addresses the concept of identity in contemporary narrative discourse, focusing on the novel " The Nights Pregnant with Moons" by Muammar Hajeij. It explores the cultural and social structures within the novel that reflect the deeply rooted Islamic dimension in the narrative character and the conflict between self and the other. The study concludes that identity forms a strong sense of belonging and pride, both on an individual and collective level, and that this sense of identity is reinforced by returning to the true religion and authentic cultural references. As highlighted in the study, literature serves as a true bastion of the nation's identity and a weapon in its confrontation with intellectual and cultural conflicts, ensuring the continuity of its existence in the face of challenges. Keywords: Identity, underlying pattern, symbolic discourse, Islamic dimension, self and the other.

Published
2024
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30. Engineering Perovskite Emissions via Optical Quasi-Bound-States-in-the-Continuum

Author

Csányi, Evelin, Liu, Yan, Rezaei, Soroosh Daqiqeh, Lee, Henry Yit Loong, Tjiptoharsono, Febiana, Mahfoud, Zackaria, Gorelik, Sergey, Zhao, Xiaofei, Lim, Li Jun, Zhu, Di, Wu, Jing, Goh, Kuan Eng Johnson, Gao, Weibo, Tan, Zhi-Kuang, Leggett, Graham, Qiu, Cheng-Wei, and Dong, Zhaogang

Subjects
Physics - Optics, Physics - Applied Physics
Abstract

Metal halide perovskite quantum dots (PQDs) have emerged as promising materials due to their exceptional photoluminescence (PL) properties. A wide range of applications could benefit from adjustable luminescence properties, while preserving the physical and chemical properties of the PQDs. Therefore, post-synthesis engineering has gained attention recently, involving the use of ion-exchange or external stimuli, such as extreme pressure, magnetic and electric fields. Nevertheless, these methods typically suffer from spectrum broadening, intensity quenching or yield multiple bands. Alternatively, photonic antennas can modify the radiative decay channel of perovskites via the Purcell effect, with the largest wavelength shift being 8 nm to date, at an expense of 5-fold intensity loss. Here, we present an optical nanoantenna array with polarization-controlled quasi-bound-states-in-the-continuum (q-BIC) resonances, which can engineer and shift the photoluminescence wavelength over a ~39 nm range and confers a 21-fold emission enhancement of FAPbI3 perovskite QDs. The spectrum is engineered in a non-invasive manner via lithographically defined antennas and the pump laser polarization at ambient conditions. Our research provides a path towards advanced optoelectronic devices, such as spectrally tailored quantum emitters and lasers., Comment: 39 pages, 4 figures in the main text and 10 figures in the supporting information

Published
2023

31. Materials and Methods

Author

Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, Delgado, João M. P. Q., Azevedo, António C., de Freitas, Vasco Peixoto, Series Editor, Costa, Aníbal, Series Editor, Delgado, João M. P. Q., Series Editor, Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, and Azevedo, António C.

Published
2024
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32. Literature Review

Author

Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, Delgado, João M. P. Q., Azevedo, António C., de Freitas, Vasco Peixoto, Series Editor, Costa, Aníbal, Series Editor, Delgado, João M. P. Q., Series Editor, Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, and Azevedo, António C.

Published
2024
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33. Results and Discussion

Author

Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, Delgado, João M. P. Q., Azevedo, António C., de Freitas, Vasco Peixoto, Series Editor, Costa, Aníbal, Series Editor, Delgado, João M. P. Q., Series Editor, Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, and Azevedo, António C.

Published
2024
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34. Introduction

Author

Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, Delgado, João M. P. Q., Azevedo, António C., de Freitas, Vasco Peixoto, Series Editor, Costa, Aníbal, Series Editor, Delgado, João M. P. Q., Series Editor, Silva, Fernando A. N., Roma, Rodrigo F., Bourbatache, Mohamed K., Tahlaiti, Mahfoud, and Azevedo, António C.

Published
2024
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37. Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes

Author

Alami, Reda, Mahfoud, Mohammed, and Moulines, Eric

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

We consider the problem of learning in a non-stationary reinforcement learning (RL) environment, where the setting can be fully described by a piecewise stationary discrete-time Markov decision process (MDP). We introduce a variant of the Restarted Bayesian Online Change-Point Detection algorithm (R-BOCPD) that operates on input streams originating from the more general multinomial distribution and provides near-optimal theoretical guarantees in terms of false-alarm rate and detection delay. Based on this, we propose an improved version of the UCRL2 algorithm for MDPs with state transition kernel sampled from a multinomial distribution, which we call R-BOCPD-UCRL2. We perform a finite-time performance analysis and show that R-BOCPD-UCRL2 enjoys a favorable regret bound of $O\left(D O \sqrt{A T K_T \log\left (\frac{T}{\delta} \right) + \frac{K_T \log \frac{K_T}{\delta}}{\min\limits_\ell \: \mathbf{KL}\left( {\mathbf{\theta}^{(\ell+1)}}\mid\mid{\mathbf{\theta}^{(\ell)}}\right)}}\right)$, where $D$ is the largest MDP diameter from the set of MDPs defining the piecewise stationary MDP setting, $O$ is the finite number of states (constant over all changes), $A$ is the finite number of actions (constant over all changes), $K_T$ is the number of change points up to horizon $T$, and $\mathbf{\theta}^{(\ell)}$ is the transition kernel during the interval $[c_\ell, c_{\ell+1})$, which we assume to be multinomially distributed over the set of states $\mathbb{O}$. Interestingly, the performance bound does not directly scale with the variation in MDP state transition distributions and rewards, ie. can also model abrupt changes. In practice, R-BOCPD-UCRL2 outperforms the state-of-the-art in a variety of scenarios in synthetic environments. We provide a detailed experimental setup along with a code repository (upon publication) that can be used to easily reproduce our experiments.

Published
2023

38. Predictors and health outcomes of cigarette and shisha smoking among men in Gaza: a cross-sectional study

Author

Ali Ismail, Layal Hamdar, Hiba Dirawi, Mohamad Kanso, Islam Salem, Hani Tamim, Gaza NCD Study Group, and Ziyad Mahfoud

Subjects
Smoking, Tobacco, Cigarette, Shisha, NCDs, Gaza, Medicine, Science
Abstract

Abstract Tobacco smoking, a significant public health concern globally, is associated with a rise in noncommunicable diseases (NCDs) and preventable deaths, with pronounced impacts in conflict zones like Gaza. A cross-sectional study, conducted in 2020, in Gaza focused on individuals over 40 years of age, aiming to identify predictors of tobacco use and its links to diseases like coronary artery disease (CAD), chronic lung disease (CLD), and stroke using regression analysis. The research, based on the Gaza NCD study data with 4576 participants and a 96.6% response rate, found an overall tobacco smoking prevalence of 19.4%, with higher rates among men. After adjusting for various factors, the study identified significant associations between cigarette smoking in men and adverse health outcomes, such as CAD and CLD, with adjusted odds ratios (OR) of 1.67, 95% CI (1.22–2.29) and 1.68, 95% CI (1.21–2.33) respectively. However, after adjusting for independent variables, shisha smoking in men showed no association with these health outcomes. The findings of this study could assist other researchers in designing interventions aimed at reducing smoking prevalence by utilizing the associated factors identified in our analysis, such as age, education level, physical activity, and body mass index among men in Gaza.

Published
2024
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44. Optimizing Orthogonalized Tensor Deflation via Random Tensor Theory

Author

Seddik, Mohamed El Amine, Mahfoud, Mohammed, and Debbah, Merouane

Subjects
Statistics - Machine Learning, Mathematics - Probability, Mathematics - Statistics Theory
Abstract

This paper tackles the problem of recovering a low-rank signal tensor with possibly correlated components from a random noisy tensor, or so-called spiked tensor model. When the underlying components are orthogonal, they can be recovered efficiently using tensor deflation which consists of successive rank-one approximations, while non-orthogonal components may alter the tensor deflation mechanism, thereby preventing efficient recovery. Relying on recently developed random tensor tools, this paper deals precisely with the non-orthogonal case by deriving an asymptotic analysis of a parameterized deflation procedure performed on an order-three and rank-two spiked tensor. Based on this analysis, an efficient tensor deflation algorithm is proposed by optimizing the parameter introduced in the deflation mechanism, which in turn is proven to be optimal by construction for the studied tensor model. The same ideas could be extended to more general low-rank tensor models, e.g., higher ranks and orders, leading to more efficient tensor methods with a broader impact on machine learning and beyond.

Published
2023

47. Positive Association Between Family and Teachers’ Tobacco Use on the Smoking Behaviors of Iraqi Adolescents Attending Schools – A Cross Sectional Study Using the Global Youth Tobacco Survey

Author

Fatima Al-Binali, Soha R. Dargham, and Ziyad R. Mahfoud

Subjects
Public aspects of medicine, RA1-1270
Abstract

Objective: Adolescent tobacco and E-cigarette use have been rising globally in the past decade. Iraq’s post-war conflict and economic crises posed psychosocial and mental health trauma, contributing to increased vulnerability to drug and substance use among adolescents. This study looks to assess the potential relationship between current tobacco and E-cigarette smoking and exposure to smoking at home and school among Iraqi adolescents attending schools. Methods: Data analysis for the 2019 Iraq Global Youth Tobacco Survey, a cross-sectional study completed by 2560 Iraqi adolescents aged 11 to 17 years old was conducted. The survey tool which includes demographic, tobacco use, knowledge and attitudes towards tobacco use questions is anonymous and self-administered using paper-based bubble sheets that are scannable. Current tobacco and E-cigarette use (defined as past 30-days) were the main outcomes. Univariate and multivariate logistic regression models were used to assess the relationship between the main outcomes and the following variables: participants’ demographics, exposure to smoking, attitude and knowledge scores. Results: Current tobacco and E-cigarette smoking prevalence among Iraqi adolescents attending school were 14.9% (95% CI: 13.5%-16.4%) and 9.7% (95% CI: 8.6%-11.0%), respectively. Exposure to smoking at home was high among fathers (39.1%), mothers (13.9%), siblings smoke (23.9%), other individuals smoke (56.1%). The percentages of students who witnessed people smoking within school premises was 45.7% and observed teachers smoking in schools was 57.6%. The current use of tobacco smoking among Iraqi adolescents was significantly and positively associated with exposure to smoking by the father (AOR = 1.39; 95% CI: 1.05-1.85), mother (AOR = 1.84; 95% CI: 1.30-2.60), sibling (AOR = 3.50; 95% CI: 2.62-4.67), teacher (AOR = 1.48; 95% CI: 1.10-1.98), and people in school (AOR = 1.99; 95% CI: 1.57-2.53). Similarly, the current use of E-cigarettes was significantly associated with father smoking (AOR = 2.02; 95% CI: 1.29-3.16), sibling smoking (AOR = 3.09; 95% CI: 2.04-4.67), and people smoking in school (AOR2.02; 95% CI: 1.39-2.95). Conclusion: Stricter policies need to be enforced to ensure safer school environments that do not expose adolescents to smoking habits of teachers or other students.

Published
2024
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48. Teaching troubleshooting skills to graduate students

Author

Gina Partipilo, Yang Gao, Alexis J Holwerda, Yassir Lekbach, Ismar E Miniel Mahfoud, Trevor R Simmons, Bailey M Tibbett, Rebecca E Wilen, Marcus S Benyamin, and Benjamin K Keitz

Subjects
point of view, experimental techniques, troubleshooting, problem solving, graduate school, training, Medicine, Science, Biology (General), QH301-705.5
Abstract

Troubleshooting is an important part of experimental research, but graduate students rarely receive formal training in this skill. In this article, we describe an initiative called Pipettes and Problem Solving that we developed to teach troubleshooting skills to graduate students at the University of Texas at Austin. An experienced researcher presents details of a hypothetical experiment that has produced unexpected results, and students have to propose new experiments that will help identify the source of the problem. We also provide slides and other resources that can be used to facilitate problem solving and teach troubleshooting skills at other institutions.

Published
2024
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49. 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. 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Daniel, Montwedi, Daniel, Muñoz, Daniel, Patterson, Daniel, Reim, Daniel, Agbley, Daniel Yao Dodzie, Patiño García, Daniela Cristina, Di Pietrantonio, Daniela, Pais, Daniela, Rosado, Daniela, Tavares, Daniela, Alberti, Daniele, Fusario, Daniele, Massaro, Daniele, Paglione, Daniele, Pironi, Daniele, Kurochka, Daniil, Centonze, Danilo Corrado, Hackner, Danilo, Herrera, Danilo, Amangaliyev, Daniyar, Silva-Cano, Danny Wladimir, Chaudhry, Daoud, Palmisano, Dario, Ribero, Dario, Vukosav, Dario, Misca, Darius, Lowen, Darren, Rattray, Darren, Walia, Darshanjit Singh, Maan, Darvesh, Muyenzi, Daryle, Verdi, Daunia, Bardsley, David, Reyes Rodríguez, David Estuardo, Fra Corral, David, Garcia López De Goicoechea, David, Gavit, David, Gómez, David, Idowu, David, Konkin, David, Labadah, David Kplorla Kekeli, Liu, David, Merlini, David, Mitchell, David, Moro-Valdezate, David, Osifo, David, Proud, David, Ridder, David, Gobatti, Davide, Muschitiello, Davide, Pertile, Davide, Zulian, Davide, Mengiste, Dawit, Mikami, Dean, Mohanty, Debajyoti, Chatterjee, Debarghya, Komolafe, Deborah Olaitan, Scotto Di Carlo, Deborah, Wright, Deborah, Rahme, Deema, Talreja, Deep Parkash, Jain, Deepak, Rajput, Deepak, Singh, Deepak, Anbu, Deepika, Ibrahim, Dena, Phom, Denchu, Hili, Denise, Osei, Dennis Broni, Daary, Dennis, Kyeremeh, Dennis, Shen, Dennis, Uymaz, Derya Salim, Cianflocca, Desiree, Ashitey, Desmond, Evripidou, Despo, Papageorgouli, Despoina, Kaushal, Devesh, Abeysirigunawardana, Dewmi, Dugar, Dharmendra, Mallik, Dhiraj, Ghosh, Dhruva, Houmran, Diaa, Abdulrahman, Diala, Pantoja Pachajoa, Diana Alejandra, Cardona Gomez, Diana Catalina, Fenner, Diana, Gonzalez, Diana Samantha, Siriwardena, Diana, Garcés Palacios, Diana Sofía, Stoian, Diana, Zuikyte, Diana, Sosa Méndez, Dianne Alitzá, Wickramarathna, Dickson, Mutter, Didier, Palma Portillo, Diego Andrés, Chavez Fernandez, Diego, Córdova García, Diego, Enjuto, Diego, Giulitti, Diego, Sasia, Diego, Visconti, Diego, Yiğit, Dilara, George, Dilip, Rabaia, Dima, Georgiev, Dimitar, Hadzhiev, Dimitar, Alexandrou, Dimitrios, Balalis, Dimitrios, Giakoustidis, Dimitrios, Manatakis, Dimitrios K., Korkolis, Dimitrios, Lytras, Dimitrios, Massaras, Dimitrios, Moris, Dimitrios, Politis, Dimitrios, Sampanis, Dimitrios, Schizas, Dimitrios, Tsiardas, Dimitrios, Vardakostas, Dimitrios, Kotsaris, Dimitris, Khattab, Dina Hesham, M. Awad, Dina, Alrokh, Dina Sami, Schippers, Dina, Waleed, Dina, Salinovic, Dinko, Gonçalves Múrias Gomes, Diogo Miguel, Silva, Diogo, Vaz Acosta, Diogo, Morton, Dion, Panagopoulos, Dionisios, Kelgiorgi, Dionysia, Dellaportas, Dionysios, Prevezanos, Dionysios, Joshi, Dipti, Ozal, Direm, Yigit, Direnc, Chimkaomasiri, Divine, Jabbar, Diya, Nepogodiev, Dmitri, Belekar, Dnyanesh, Abdalaziz, Doaa, Abunemer, Doaa, Attia, Doaa, Elkafrawy, Doaa, Dimitrov, Dobromir, Pignatelli, Domenica, Merlicco, Domenico, Soriero, Domenico, Zerbo, Domenico, Atouguia, Domingas, Fairbrass, Dominic, T. Enti, Donald, Venskutonis, Donatas, Rukavina, Dora, Caruso, Dorena, Herappe, Dorihela, Lee, Dorinda Norbetha, Ofosuhene, Doris, Hajela, Apoorva, Badwan, Basem, Kulkarni, Datta, Dhawan, Deep, Dhillon, Jeevanjit, Mehmood, Manzer, Mahmood, Namrah, Nikam, Narendra, Ramchandani, Radhakrishna, Thind, Ravinder Singh, Riazhussain, D Hafiz, Maqsood, Saliha, Alalawi, Yousef, Tyagi, Harshdeep, Kshirsagar, Shivani, Ahmed, Hisham, Juan Carlos, Luna Cydejko, Kone, Dramane, Omar, Duaa, Alves, Duarte Gil, Subasinghe, Duminda, Ommi, Durgesh, Joshiba, Durshney, Chakarov, Dzhevdet, Arkoh, Ebenezer Ameyaw, Frimpong-Manso, Ebenezer, Ada, Ece, Lincango, Eddy P., Lozada Hernandez, Edgard Efren, Hodžić, Edin, Di Marco, Edith, Baccalini, Edoardo Andrea, Baldini, Edoardo, González Marín, Eduardo, Gutierrez, Eduardo, Sepúlveda, Eduardo, Dainius, Edvinas, Zhang, Edward, Yenli, Edwin Mwintiereh Ta-Ang, Antoniou, Efstathios, Kapasakis, Efstathios, Baili, Efstratia, Poulios, Efthymios, Kubiliute, Egle, Osaze, Ehioghae, Afeikhena, Ehis, Elshennawy, Eiad, Athanasopoulou, Eirini, Synekidou, Eirini, Ekaladze, Eka, Tampaki, Ekaterini Christina, Adam, Elaf, Adel Hamdoun Aziz, Elaf, Yousuf, Elamin, Gialamas, Eleftherios, Spartalis, Eleftherios, Bedzhanyan, Elen, Toma, Elena Adelina, Daukšaitė, Elena, Desiato, Elena, Dvivedi, Elena, Hadzhieva, Elena, Martí Cuñat, Elena, Montalbán Martínez, Elena, Montanari, Elena, Signaroli, Elenasofia, Efremidou, Eleni, Gavriil, Eleni, Karakeke, Eleni, Mavrodimitraki, Eleni, Papamattheou, Eleni, Jose, Elenza, Cianci, Eleonora, Ciccioli, Eleonora, Daleva, Eleonora, Locci, Eleonora, Lori, Eleonora, Silanos, Eleonora, Ayala, Elí, Bankart, Eliana, Brolese, Eliane, Efstathiou, Elias, Salloum, Elias, Colak, Elif, Terzi, Elif Didem, Ametefe, Elikem, Cagigal Ortega, Elima Pilar, Donnarumma, Elio, Mina, Elisa, Reitano, Elisa, Wallner, Elisabeth, Moggia, Elisabetta, Betz, Elise, Kontis, Elissaios, Anestiadou, Elissavet, Gimson, Eliza, Lun, Elizabeth, Fraser, Elizabeth, Li, Elizabeth, Torres De Anda, Elizabeth Magaly, Murphy, Elizabeth Mary Ann, O'Connell, Elizabeth, Redondo, Elizabeth, Lun, Elizabeth Weng Yan, Francis, Ella, Haiden, Elmar, Hamed, Elmonzir, Alkhalifa, Elmustafa, Dexter, Eloise, Daketsey, Elorm, Setsoafia, Elorm, Mohamed, Elsagad, Mohammed, Elsamoual, Hegab, Elsayed, Ay, Elvin, Adinolfi, Elvira, Mbanzabugabo, Elvis, Chin, Elynn, Ahmed, Emad Ali, Younes, Eman, Basile, Emanuela, Gessa, Emanuela, Pontecorvi, Emanuele, Romairone, Emanuele, Hatangimana, Eméry, Ndizeye, Emile, Ciofic, Emilia, Dijan, Emilio, López-Negrete Cueto, Emilio, Baker, Emily, Reid, Emily, Schmidt, Emily, Alić, Emir, Bičakčić, Emir, Agbowada, Emma, Colton, Emma, Downing, Emma, Haege, Emma, O'Neill, Emma, Roussos, Emmanouel, Nachelleh, Emmanuel Aadereyir, Adebunmi, Emmanuel, Obiesie, Emmanuel Ahuizechukwu, Akakpo, Emmanuel Bismark, Konlan, Emmanuel Dammigu Francis, Nwangwu, Emmanuel Ifeanyi, Kafui Ayodeji, Emmanuel, Ofori, Emmanuel Owusu, Spanoudakis, Emmanuel, Abate, Emmanuele, Balik, Emre, Bozdağ, Emre, Bozkurt, Emre, Karabulut, Emre Cagri, Ozoran, Emre, Tunçcan, Emre, Tuzuner, Emre, Halilović, Emsad, Alabed, Enaam, Zidan, Enas, Hodžić, Enes, Aybar, Engin, Yildirim, Engin Okan, Wong, Enoch, Yhoshu, Enono, Bisogno, Enrica, Andolfi, Enrico, Ferri, Enrico, Potenza, Enrico, Spalice, Enrico, Volpin, Enrico, González, Enrique, Downes, Eoin, Gallo, Erdachew, Kamer, Erdinc, Naidoo, Eressa, Erginöz, Ergin, Bara, Eric, Irungu, Eric, García-Villegas, Eric Yusif, Mazzotta, Erica, Monati, Erica, Chan, Erick, Gómez Mejía, Erika, Dylja, Eris, Somuncu, Erkan, Yavuz, Erkan, Begunić, Ernes, Margelis, Ernest, Osei, Ernest Owusu, Saitoglou, Ertzan, Agastra, Ervis, Mazumdar, Eshan, Soyer Güldoğan, Esra, Abu Siam, Esra'A, Abdelbaset, Esraa, Abdu, Esraa, Adel Mahmod Sultan, Esraa, Nubi Mohamed, Esraa Gamal, Abuobaida Banaga Hag El Tayeb, Essam Eldien, Ali, Essraa, Page-Taylor, Estelle, Marra, Ester, Garcia Santos, Esther Pilar, Elsheikh, Ethar, Unal, Ethem, Tan, Eugene, De Leo, Eugenio, Borges, Eva, Gáspár, Éva, Ruiz-Daum, Eva, Apostolopoulos, Evaggelos, Samara, Evangelia, Barkolias, Evangelos, Fradelos, Evangelos, Hopping, Eve, Romo Ascencio, Evelia Veronica, Sosa Ferreira, Ever David, Shestakov, Evgenii, Tyurina, Evgenya, Hristova, Evguenia, Efthymiou, Evripidis, Tokidis, Evripidis, Harrison, Ewen, Dontoh, Ewurama Akroma, Mansour, Eyad, Yeshialem, Eyosiyas, Dabbagh, Ezeddin, Amer, Ezzeldin, Manasci, Fabiana, Gomes, Fabio, Medas, Fabio, d'Acapito, Fabrizio, Vassallo, Fabrizio, Haddad, Fadi, Elhabishi, Fadwa, Akhtar, Fahad, Tauheed, Fahad, Al Abbood, Fahd, Gareb, Fahed, Ghazali, Fairuz, Alnazawi, Faisal, Ondago, Faith, Rasoaherinomenjanahary, Fanjandrainy, Wiese, Fanny, González Ponce, Fanny Yesenia, Georgiades, Fanourios, Ali, Farah, Galley, Fareeda, Huda, Farhanul, Amir, Farhat Naaz, Ashraf, Fariha, Alfarsi, Faris, Ayasra, Faris, Ali, Farman, Mahmoud, Faten, Aliskander, Fater, Tahir Lwdie, Fathea, Buyuker, Fatih, Aguilar Del Castillo, Fátima, Mohammed Daoud, Fatima Ahmed, Alowjaly, Fatima, Oni, Fatima, Rauf, Fatima, Elkhafeefi, Fatimah, Hourri, Fatine, Monib, Fatma A., Alshreef, Fatma, Benghalbon, Fatma, Ntirenganya, Faustin, Ashraf, Fauziyah, Chahrour, Fayez, Ahmad, Fazal, Parray, Fazlul Qadir, Philips, Febi, Campus, Federica, Di Marco, Federica, Ferraina, Federica, Frongia, Federica, Maffeis, Federica, Natali, Federica, Pederiva, Federica, Scolari, Federica, Tofani, Federica, Marin, Federico Alberto Niccolò, Biolchini, Federico, Cappellacci, Federico, Corronca, Federico, Mazzola, Federico, Suldrup, Federico, Nyarko, Felicia, Casas J, Felipe, Zapata, Felipe, Aigner, Felix, Alakaloko, Felix, Amoako, Felix, Camacho, Felix, Hammett, Felix, Kuubetersob B. 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, Velluti, Francesco, Mulita, Francesk, Bello, Francis, Caiquo, Francis, Dossou, Francis, Eshun, Francis Junior, Opoku Twene, Francis, Tierenye, Francis, Quayson, Francis William, Romo Rosales, Francisco David, Ibañez Ortiz, Francisco, León Frutos, Francisco Javier, Redondo Calvo, Francisco Javier, Silva Rivera, Francisco Javier, Barbosa Camacho, Francisco José, Bujalance Cabrera, Francisco Manuel, Ruescas, Francisco, Irakiza, Franck Fanon, Corvatta, Franco, Pascual, Franco Raúl, Roviello, Franco, Roodt, Francois, Gyamfi, Frank Enoch, Olaniru, Frank, Owusu, Frank, Bader, Franz G., Anzinger, Franz-Xaver, Agbodo, Fred David Anku, Ris, Frederic, Agbemafoh, Frederick Mawuli, Afonso, Frederico, Nazareth, Frederico, Berrevoet, Frederik, Hounde, Fréjus, Demiral, Furkan, Hassooni, Furqan Ridha Hassooni, Kafa, Gabi, Cárdenas Rivera, Gabriel, Ntwari, Gabriel, Szydlo Shein, Gabriel, Ambriz González, Gabriela, Nita, Gabriela Elisa, Bellio, Gabriele, Moitzi, Gabriele, Urdang, Gabriella, Marom, Gad, Gallo, Gaetano, Luglio, Gaetano, Poillucci, Gaetano, Singh, Gagandeep, Saletta, Gaia, Abouelnagah, Galal, Yarovenko, Galina, Kazobinka, Gallina, Ahmed, Gamal Mutwakil Gamal, Rahman, Ganiyu Adebisi, Smith, Garett, Pillai, Gargi, Saxena, Garima, Gbessi, Gaspard, Nkunguzi, Gaston, Jalal, Gaurav, Chillarge, Gauri, Singh, Gautam, Mevognon, Gedeon, Getachew, Gedion, George, Gejoe, De La Peña González, Gema, Martínez Izquierdo, Gema, Grande, Gennaro, Birikorang, Geoffrey, Weber, Georg F., Singer, Georg, Ansong, George, Bashour, George, Brown, George Darko, Hneino, George, Kavalieratos, George, Kenchadze, George, Nagy, George, Pappas Gogos, George, Skroubis, George, Waiyaki, George, Cox, Georgia, Zeringa, Georgia, De Wee, Georgin, Hart, Georgina, Bekakos, Georgios, Fragulidis, Georgios, Kapogiannatos, Georgios, Karakaidos, Georgios, Kokkinos, Georgios, Kostoulas, Georgios, Koukoulis, Georgios, Peros, Georgios, Rados, Georgios, Tsoulfas, Georgios, Verras, Georgios-Ioannis, Berger, Geraint, Adoro, Gerard Ayuka, Chamoso Mialdea, Gerardo, Palmieri, Gerardo, Procaccini, Gerardo, Steenkamp, Gerhard, Viscido, Germán Rodrigo, Dajti, Gerti, Alemayehu, Getachew, Seyfu, Gezachew, Birqeeq, Ghada, Alsheikh, Ghadeer, Alrayyes, Ghaith, El Hunjul, Ghalib Nashaat, Zaza, Ghayath, Matroud, Ghazlah, Alhadwah, Ghena, Maltinti, Gherardo, Awais, Ghina, Shamsi, Ghina, Calini, Giacomo, Carganico, Giacomo, Zanus, Giacomo, Canu, Gian Luigi, Mendiola, Gian, Ibero Casadiego, Giana Pamela, Cocorullo, Gianfranco, Baronio, Gianluca, Pellino, Gianluca, Zanni, Gianluca, Poto, Gianmario Edoardo, Gravante, Gianpiero, Aduroja, Gideon, Almogy, Gidon, Bond-Smith, Giles, Natchagande, Gilles, Bechara, Gio, Brachini, Gioia, Riccioli, Giordana, Ercolani, Giorgio, Farris, Giorgio, Giraudo, Giorgio, Mammolo, Giovanna, Pavone, Giovanna, Sgarzini, Giovanna, Aprea, Giovanni, Fonsi, Giovanni Battista, Boroni, Giovanni, De Angeli, Giovanni, De Palma, Giovanni Domenico, Emiliani, Giovanni, Grava, Giovanni, Guercio, Giovanni, De Carlo, Giulia, Del Corpo, Giulia, Duranti, Giulia, Galatioto, Giulia, Grassi, Giulia, Graziano, Giulia, Marini, Giulia Maria Francesca, Munzi, Giulia, Tarantino, Giulia, Borda-Luque, Giuliano, Pellicano', Giuseppe Antonino, Canonico, Giuseppe, Carollo, Giuseppe, Ietto, Giuseppe, Palomba, Giuseppe, Pascarella, Giuseppe, Salamone, Giuseppe, Sica, Giuseppe, Sorrentino, Giuseppe, Orlando, Giuseppina, Pignata, Giusto, Pisarevi, Givi, Akcakoca, Gizem, Owusu, Godfred, Yohanna Abrak, Godwin, Kurtoglu, Gokalp Kagan, Kurtoglugk, Gokalp Kagan, Alıcı, Gökhan, Kurtoglu, Goktug Mert, Delgado Hernandez, Gonzalo, Augustin, Goran, Bhat, Gowhar Aziz, Sundaram Venkatesan, Gowtham, Chang, Grace, Eke, Grace, Lee, Grace, Massarra, Grace, Travaglini, Grazia, Scialandrone, Grazisa, Stavrou, Gregor A., Di Franco, Gregorio, Charalambous, Gregory, Christodoulidis, Gregory, Kouraklis, Gregory, Goodwin, Gregory Richard, Devidze, Grigol, Fialho, Guilherme, Santos, Guilherme, Cabezudo, Guillermo, García-Santos, Guillermo, Pou, Guillermo, Romero Reyna, Guillermo, Yanowsky-Reyes, Guillermo, Ozyuksel, Gul, Karadeniz Cakmak, Guldeniz, Kucuk, Gultekin Ozan, Bulbuloglu, Guney Cem, Sarp, Guray, Kaur, Gurleen, Nibogora, Guy Darcy, Hamdan, Gymar, Ogundipe, Habeeb, Yunes, Habib, Ayesh, Hadeel, Al Atassi, Hadi, Jalilehvand, Hadis, Masalma, Hafez, Jafarkhan, Hafis, Shahid, Hafiz Huzaifa, Younus, Hafsa, Al-Derume, Hail, Shames, Haitam, Mimouni, Haithem Ahmed, Aldare, Hajar, Odah Bashi, Hajar Omar, Abusnina, Hajer, Altounsi, Hajir, Qayum, Hajra, Baysal, Hakan, Bolukbasi, Hakan, Yigitbas, Hakan, Alkhatib, Hala, Afzal, Haleema, Mftah, Halima, Oyinlola, Halimah, Tümer, Haluk, Dolo, Hamadoun, Braham, Hamdi, Ozsahin, Hamdi, Abu-Arish, Hamdoon, Al-Aamri, Hamed, Fadlalmola, Hammad Ali, Abu Obead, Hamza, Al-Fahel, Hamza, Al-Zoubi, Hamza, Asaad, Hamza, Ejaz, Hamza, Jaber, Hamza, Bhatti, Hamza Waqar, Mohammadi Sardoo, Hamzeh, Farhat, Hana, Idheiraj, Hanadi, Zwaraa, Hanady, Al Sohabi, Hanan, Basharat, Hanan, Said, Hanan, Al-Abdallat, Haneen, Foad, Haneen, Daaboul, Hanen, Al Qadhi, Hani, Elhallaq, Hani, Alhusaini, Hanin, Lidbetter, Hannah, Reilly, Hannah, Moya- Ambriz, Hannia Betzabeth, Lederhuber, Hans, Fehrer, Hans-Jörg, Xiao, Haotian, Iswariah, Harish, Kaur, Harmeena, Cheema, Harnoor Kaur, Foda, Haroun, Chauhan, Harpreet, Kaur, Harpreet, Sagar, Harry, Unwin, Harry, Kaur, Harsharan, Panga, Harshavardhan, Gupta, Harshit, Prabhakar, Harshit Kumar, Anand, Harshitha, Pahwa, Harvinder Singh, Abbadi, Hasan, Amoudi, Hasan, Zaini, Hasan Hadi Zaini, Škiljo, Hasan, Miyasika, Hasangi, Altabbaa, Hashem, Haj Freej, Hasn, Abdelazim, Hassan, Habiba, Hassan, Kamal, Hassan, Sabir, Hassan, Zaigham, Hassan, Pehlivan, Hatice, Telci, Hatice, Abuobaida, Hayat, Tetley, Heather, Taher, Heba, Aguado López, Héctor, Askarpour, Hedyeh, Sherif Farouk Ahmed Hassan, Heidi, Devesa, Helena, Arbogast, Helmut, Nuñez Del Barrio, Henar, Abiyere, Henry, Delacave, Henry, Rice, Henry E., Pleass, Henry, Bradly, Hera, 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Rugambwa, Jean Paul, Jordaan, Jean- Jacques, Razafindrahita, Jeannie Ba, Do, Jee Eun, Senavirathna, Jeewantha, Kalyanapu, Jeffrey A, Chan, Jeffrey, Ofori, Jeffrey, Otote, Jeffrey, Akiely, Jehad, Cassiano Neves, Jelena, Gillingham, Jemima, Herrera Batres, Jenifer Olga María, Ezeh, Jennifer, Okei, Jennifer, Vu, Jennifer, Guevara, Jenny, Siu, Jenny, Rolinger, Jens, Skaff, Jeolle, Uys, Jernelle, Makama, Jerry Godfrey, Barklimore, Jessica, Dei-Asamoa, Jessica, Jahjah, Jessica, Jones, Jessica, Ng, Jessica, Ricardo, Jéssica, Schembri Higgans, Jessica, You, Jessica, Annan, Jessie, Aguilar, Jesus Antonio, Pizarro Lozano, Jesús, Lim, Jia Hui, Zhu, Jiang, Wang, Jianxue, Abbasy, Jibran, Ugwu, Jideofor, Rathod, Jignesh, Albalushi, Jihan, Najajra, Jinan, Fu, Jing Hui, Tefay, Joan Sia Tan, Domingues, Joana Cristina, Simoes, Joana FF, Figueiredo, Joana, Fontaínhas, Joana, Frazão, Joana, Marques Antunes, Joana, Simoes, Joana, Marx, Joanna Naemi, Dias-Ferreira, João, Fernandes, João, Mendes, João, Pinho, João, Ribeiro, João, Vaz, João, Dominguez, Joaquina, Abutu John, Job, Chen, Joe Jun Qiao, Enaholo, Joel, Alaji, Joelle, Miller, Johanna, Binder, Johannes, Daleku, John, Katogiritis, John, Khoury, John, Anyorigiya, John Noah, Reilly, John, Abebrese, John Tabiri, Ahale, Johnny Lordson, Tabora-Zepeda, Johnny, Barrutia Leonardo, Jon, Demma, Jonathan Abraham, Hong, Jonathan, Chejfec-Ciociano, Jonathan Matias, Oppong, Jonathan, Quansah, Jonathan, Sutcliffe, Jonathan, Taiwo, Jones, Nyamekye - Baidoo, Joojo, Prat-Ortells, Jordi, Dongmo, Jordy, Kleeff, Jorg, Jimenez Flores, Jorge Alberto, Pellecer Cano, Jorge Bernardo, Chóliz, Jorge, Giubi Bobeda, Jorge Eduardo, Escartin, Jorge, Febré, Jorge, Gass, Jörn-Markus, Calvache, Jose A, Guzman Barba, Jose Aldo, Gutiérrez Gómez, José Alonso, Calvache, Jose Andres, Acevedo Parrales, José Danilo, Orozco Navarro, José Esteban, Viñas, José Federico, Gomez, José, Goncalves-Nobre, Jose Guilherme, Valenzuela, José Ignacio, Garcia Galocha, Jose Luis, 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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, 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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, 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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, 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