Author: "Saleh, Ali" - Searchworks@Jio Institute Digital Library Search Results

1,902 results on '"Saleh, Ali"'

1. QoE-Aware and Secure UAV-Aided Rate-Splitting Multiple Access Based Communications

Author: Adam, Abuzar B. M., Wan, Xiaoyu, and Muthanna, Mohammed Saleh Ali
Subjects: Computer Science - Networking and Internet Architecture
Abstract: In this work, we address the issue of quality of experience (QoE) in unmanned aerial vehicle (UAV) aided multiuser rate-splitting multiple access (RSMA) networks under secrecy constraints. The problem is formulated as maximization of sum mean opinion scores (MOSs) of the users. The problem is decomposed into two subproblems, beamforming and rate allocation and UAV trajectory subproblem. For, beamforming and rate allocation subproblem, we use the epigraph method, property of polynomials, and the norm-bounded error of channels, we linearize the objective function. Then, applying second-order conic (SOC) and first Taylor expansion, we convexify the remaining nonconvex constraints. For the highly nonconvex UAV trajectory, we unroll the constraints and we apply first Taylor expansion on the unrolled constraints. The simulation results demonstrate the efficiency of the proposed framework., Comment: 6 pages, 4 figures
Published: 2024

2. A Smart IoT-Cloud Framework with Adaptive Deep Learning for Real-Time Epileptic Seizure Detection

Author: Hussein, Ahmad MohdAziz, Alomari, Saleh Ali, Almomani, Mohammad H., Zitar, Raed Abu, Saleem, Kashif, Smerat, Aseel, Nusier, Shawd, and Abualigah, Laith
Published: 2024
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3. Evaluation of the Reverse Deep Drawing Process to Produce Square Cup of Brass Without Blank-Holder

Author: Saleh, Ali Hassan, Abdulridha, Hussein Muwafaq, Al-Kalali, Rawaa Hamid Mohammed, and Ismail, Muammar Ibrahim
Published: 2024
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4. Real-Time and Security-Aware Precoding in RIS-Empowered Multi-User Wireless Networks

Author: Adam, Abuzar B. M., Ouamri, Mohamed Amine, Muthanna, Mohammed Saleh Ali, Li, Xingwang, Elhassan, Mohammed A. M., and Muthanna, Ammar
Subjects: Computer Science - Information Theory, Electrical Engineering and Systems Science - Signal Processing
Abstract: In this letter, we propose a deep-unfolding-based framework (DUNet) to maximize the secrecy rate in reconfigurable intelligent surface (RIS) empowered multi-user wireless networks. To tailor DUNet, first we relax the problem, decouple it into beamforming and phase shift subproblems, and propose an alternative optimization (AO) based solution for the relaxed problem. Second, we apply Karush-Kuhn-Tucker (KKT) conditions to obtain a closed-form solutions for the beamforming and the phase shift. Using deep-unfolding mechanism, we transform the closed-form solutions into a deep learning model (i.e., DUNet) that achieves a comparable performance to that of AO in terms of accuracy and about 25.6 times faster.
Published: 2023

5. Experimental and numerical study of shear behavior of concrete–soft rock interface: with approach of concrete penetration in rock cavities

Author: Sarfarazi, Vahab, Ahmadian Saleh, Ali, Fu, Jinwei, Haeri, Hadi, Tahmasebi Moez, Mina, Moayer, Ali, and Golsanami, Naser
Published: 2024
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6. Students’ performance in clinical class II composite restorations: a case study using analytic rubrics

Author: Arwa Daghrery, Ghadeer Saleh Alwadai, Nada Ahmad Alamoudi, Saleh Ali Alqahtani, Faisal Hasan Alshehri, Mohammed Hussain Al Wadei, Naif Nabel Abogazalah, Gabriel Kalil Rocha Pereira, and Mohammed M Al Moaleem
Subjects: Class II composite restoration, Clinical, Dental education, Rubrics, Special aspects of education, LC8-6691, Medicine
Abstract: Abstract Background The analytical rubric serves as a permanent reference for guidelines on clinical performance for undergraduate dental students. This study aims to assess the rubric system used to evaluate clinical class II composite restorations performed by undergraduate dental students and to explore the impact of gender on overall student performance across two academic years. Additionally, we investigated the relationship between cumulative grade point averages (CGPAs) and students’ clinical performance. Methods An analytical rubric for the assessment of clinical class II composite restoration in the academic years of 2022/2023 and 2023/2024 was used by two evaluators. These two evaluators were trained to use the rubric before doing the evaluations. The scores were based on a 4-point scale for the evaluation of five major parameters for pre-operative procedures (10 points), cavity preparation (20 points), restoration procedures (20 points), and time management (4 points). At the same time, chairside oral exam parameter was 15 points based on a 5-point scale. Descriptive statistics were calculated for the different analytical rubric parameters, and the independent t-test was used to compare the scores between the student groups and the evaluators. Other tests, such as the Kappa test and Pearson’s correlation coefficient, were used to measure the association among CGPA, evaluators, and gender participants. Results The overall score out of 69 slightly increased for females/males (61.28/59.42) and (61.18/59.49) in the 2022/2023 and 2023/2024 academic years, respectively, but the differences were not statistically significant. In the 2022/2023 academic year, female students scored significantly higher than male students in pre-operative procedures, as evaluated by both evaluators (p = 0.001), and in time management, as assessed by both evaluators (p = 0.031). The Kappa test demonstrated a moderate to substantial level of agreement between the two evaluators in both academic years. Strong and significant correlations were noted between students’ CGPA and some tested parameters (p = 0.000). Conclusion The overall performance was very good and high among both genders, but it was marginally higher among females than among males. This study found some differences in performance between male and female students and variability in the evaluations by the two raters ranging from moderate to substantial agreement and similar performances for students with different CGPA.
Published: 2024
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7. Inspiring nurses’ sustainability mindset: Exploring the Mediating Role of Organizational Culture on the relationship between Pro-social Leader behaviors and nurses’ sustainability consciousness

Author: Amal Diab Ghanem Atalla, Wafaa Hassan Mostafa, and Mohamed Saad Saleh Ali
Subjects: Organizational culture, Pro-social leader behaviors, Nurses, Sustainability consciousness, Mediator, Nursing, RT1-120
Abstract: Abstract Background Since nurses are at the frontline of healthcare delivery, their actions and understanding of the environment have a big impact on how long healthcare systems can last. It is essential to comprehend the elements that impact nurses’ sustainability consciousness to encourage ecologically conscious actions in the healthcare industry. Aim This study aimed to explore the relationship between pro-social leader behaviors and nurses’ sustainability consciousness and testify to the mediating role of organizational culture in this relationship. Design A cross-sectional descriptive correlational design by STROBE criteria was used. Methods and tools An approach to a judgmental non-probability sampling technique was employed to obtain data from 350 nurses in an Egyptian hospital. Three measurement surveys were employed: Organizational Culture Survey, Prosociality Scale, and, Sustainability Consciousness Questionnaire (SCQ-S). Relationships were shown using structural equation modeling and descriptive and inferential statistics. Results 53.4% of nurses have high perceptions of organizational culture, and the majority of nurses (85.7%) have high perceptions of prosocial leader behaviors. Furthermore, 60.9% of nurses have high perceptions of sustainability consciousness. Additionally, Prosocial leader behaviors positively correlated with organizational culture (r = 0.129) and nurses’ sustainability consciousness (r = 0.274). The indirect effect of prosocial leader behaviors on nurses’ sustainability consciousness through organizational culture is calculated by multiplying the coefficients of both direct effects (0.129 * 0.159 = 0.811). This means that for each unit increase in prosocial leader behaviors, we would expect a 0.811 unit increase in nurses’ sustainability consciousness through the mediating effect of organizational culture. The model appears to match the data well based on the model fit parameters (CFI = 1.000, IFI = 1.000, RMSEA = 0.114). Conclusions The study highlights the impact of pro-social leader behaviors on nurses’ sustainability consciousness through the organizational culture as a mediating factor. Nursing Implications: Findings from this research can promote environmental stewardship and sustainable practices in the healthcare sector by illuminating the elements that can encourage and support a sustainability-oriented mindset among nurses. To promote a more sustainable future for the nursing profession, the findings can guide activities in nursing education, corporate culture transformation, and leadership development.
Published: 2024
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8. The influence of organizational agility on nurses` career planning: nurses` grit as a mediating factor

Author: Amal Diab Ghanem Atalla, Mohamed Saad Saleh Ali, Ayman Mohamed El-Ashry, and Wafaa Hassan Mostafa
Subjects: Organizational agility, Nurses, Career planning, Grit, Mediating factor, Nursing, RT1-120
Abstract: Abstract Background Organizational agility is the cornerstone of the complex dynamics for the success of healthcare organizations and the sustenance of nurses’ career planning and professional development. Aim Assess the organizational agility and the extent of nurses’ career planning. It also sought to investigate the association between the two and the intermediating function that nurses` grit plays in this association. Design A cross-sectional descriptive design following STROBE guidelines was carried out. Methods and tools Data were collected from 300 nurses who made up the entire population sample that we used (a judgmental non-probability sampling technique) working across all in-patient care units at Itay El-Baroud General Hospital, in El Behaira governorate, using structured questionnaires as follows: the organizational agility questionnaire, the career planning scale, and the grit scale. The sociodemographic characteristics of the studied nurses were also collected. Statistical analyses were used to analyze the data, including ANOVA, Pearson correlation, and SEM, to determine whether career development may act as a mediator between organizational agility and the nurses’ career planning. Results Rendering the findings of this study, more than half of nurses have a high perception regarding organizational agility and career planning. In contrast, the majority of them have a moderate perception regarding grit. In addition, there is a statistically high significant relationship between organizational agility and career planning. Also, there is a statistically high significant relationship between organizational agility and grit. There is a statistically high significant relationship between career planning and grit. Conclusion The statistically substantial correlations among grit, career planning, and organizational agility demonstrate how interrelated they are. This implies that encouraging organizational flexibility and effective career planning techniques may have a good impact on nurses’ resilience, which would ultimately result in a workforce of nurses who are more resilient and engaged. Additional investigation into the precise mechanisms behind these associations may yield important information for improving nurse wellbeing and retention. Nursing implications According to this study, putting organizational agility and career planning first can have a good impact on nurses’ grit, which will make them more resilient and engaged workers. To encourage flexibility and growth among nurses, healthcare institutions should make training investments, provide clear career tracks, and support work-life balance. More investigation into the precise mechanisms underlying these connections may yield insightful information that improves nurse well-being and retention. The importance of organizational agility in creating a supportive work environment for nurses’ career growth should be acknowledged by healthcare companies. This can lead to increased job satisfaction and lower turnover.
Published: 2024
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9. Board composition and corporate social responsibility: uncovering the effects of co-opted directors

Author: El Saleh, Ali I. and Jurdi, Doureige J.
Published: 2024
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10. Clustering of hepatitis C infection among family members in Aden, Yemen

Author: Gubran, Ali N.M., Al-Barq, Ali Mohsen Mohammed, Hashem, Mohammed Abdulbaset Mohammed, Saleh, Noura Ramzy Mohammed, Saleh, Abdulsalam Abdullah Mohammed, Mohammed, Shaima Rashad Saleh Ali, Bn Zead, Wala Salem Saleh Salem, Muswat, Fatima Luai Ali Saeed, Bahumaish, Arwa Khaled Ali Mohammed, and Al-Saadi, Yousif Fahmi Qasim
Published: 2024
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11. Students’ performance in clinical class II composite restorations: a case study using analytic rubrics

Author: Daghrery, Arwa, Alwadai, Ghadeer Saleh, Alamoudi, Nada Ahmad, Alqahtani, Saleh Ali, Alshehri, Faisal Hasan, Al Wadei, Mohammed Hussain, Abogazalah, Naif Nabel, Pereira, Gabriel Kalil Rocha, and Al Moaleem, Mohammed M
Published: 2024
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12. MGFEEN: a multi-granularity feature encoding ensemble network for remote sensing image classification

Author: Jean Bosco, Musabe, Jean Pierre, Rutarindwa, Muthanna, Mohammed Saleh Ali, Jean Pierre, Kwizera, Muthanna, Ammar, and Abd El-Latif, Ahmed A.
Published: 2024
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13. Recent Developments and Different Perspectives on Social and Emotional Competency Classifications: A Comparative Study

Author: Ali Said Sulayiam Al Matari, Saliha Juma Fadhil AlSaadi, and Wasin Saleh Ali Albalushi
Subjects: social, emotional, developments, perspectives, competencies, Education (General), L7-991
Abstract: Abstract Social and emotional competencies play a major role in promoting a climate of positive relationships, responsibility, and a sense of family security; supporting positive behavior; achieving academic growth; contributing to emotional self-regulation; reducing anxiety about social interaction in individuals; reducing psychological stress; promoting optimism; and supporting mental health in individuals; however, there is no consensus on the number of core competencies, and how to identify and activate them. This difference in approach challenges future research, as well as the scientific utility of creating an integrative taxonomy, and focused review evaluates different approaches to visualizing and assessing social and emotional competencies. Based on common concepts, the researchers seek to provide different classifications of social and emotional learning competencies, through which they identify the basic domains and manifestations of social and emotional competencies that link frameworks focused on social and emotional learning ( C A S E L ) and personality traits ( s u c h a s t h e B i g F i v e ) . By presenting these different developments in the classifications of social and emotional learning competencies, the researcher sees better organizing many of the terms and definitions used and directing the perception and activation of social and emotional competencies and their various aspects.
Published: 2024
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14. RCLNet: an effective anomaly-based intrusion detection for securing the IoMT system

Author: Jamshed Ali Shaikh, Chengliang Wang, Wajeeh Us Sima Muhammad, Muhammad Arshad, Muhammad Owais, Rana Othman Alnashwan, Samia Allaoua Chelloug, and Mohammed Saleh Ali Muthanna
Subjects: IoMT, CNN, LSTM, focal loss, WUSTL-EHMS-2020, Medicine, Public aspects of medicine, RA1-1270, Electronic computers. Computer science, QA75.5-76.95
Abstract: The Internet of Medical Things (IoMT) has revolutionized healthcare with remote patient monitoring and real-time diagnosis, but securing patient data remains a critical challenge due to sophisticated cyber threats and the sensitivity of medical information. Traditional machine learning methods struggle to capture the complex patterns in IoMT data, and conventional intrusion detection systems often fail to identify unknown attacks, leading to high false positive rates and compromised patient data security. To address these issues, we propose RCLNet, an effective Anomaly-based Intrusion Detection System (A-IDS) for IoMT. RCLNet employs a multi-faceted approach, including Random Forest (RF) for feature selection, the integration of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models to enhance pattern recognition, and a Self-Adaptive Attention Layer Mechanism (SAALM) designed specifically for the unique challenges of IoMT. Additionally, RCLNet utilizes focal loss (FL) to manage imbalanced data distributions, a common challenge in IoMT datasets. Evaluation using the WUSTL-EHMS-2020 healthcare dataset demonstrates that RCLNet outperforms recent state-of-the-art methods, achieving a remarkable accuracy of 99.78%, highlighting its potential to significantly improve the security and confidentiality of patient data in IoMT healthcare systems.
Published: 2024
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15. Influence of Access Points’ Height and High Signal Relation in WLAN Fingerprinting-Based Indoor Positioning Systems’ Accuracy

Author: Nicholaus, Mrindoko R., Ruambo, Francis A., Masanga, Elijah E., Muthanna, Mohammed Saleh Ali, Lashchev, Andrei, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Vishnevskiy, Vladimir M., editor, Samouylov, Konstantin E., editor, and Kozyrev, Dmitry V., editor
Published: 2024
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16. Multilevel Edge Computing System for Autonomous Vehicles

Author: Muthanna, Mohammed Saleh Ali, Elkin, Dmitry, Likhtin, Semyon, Al-Sveiti Malik, A. M., Chlamtac, Imrich, Series Editor, Abd El-Latif, Ahmed A., editor, Tawalbeh, Lo’ai, editor, Maleh, Yassine, editor, and Gupta, Brij B., editor
Published: 2024
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17. Organization of Smart City Services Based on Microservice Architecture

Author: Muthanna, Mohammed Saleh Ali, Elkin, Dmitry, Likhtin, Semyon, Muthanna, Ammar, Chlamtac, Imrich, Series Editor, Abd El-Latif, Ahmed A., editor, Tawalbeh, Lo’ai, editor, Maleh, Yassine, editor, and Gupta, Brij B., editor
Published: 2024
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18. Machine Learning–Based Identity and Access Management for Cloud Security

Author: Jamil, Harun, Ali, Abid, Ammi, Meryem, Kirichek, Ruslan, Muthanna, Mohammed Saleh Ali, Jamil, Faisal, Chlamtac, Imrich, Series Editor, Abd El-Latif, Ahmed A., editor, Tawalbeh, Lo’ai, editor, Maleh, Yassine, editor, and Gupta, Brij B., editor
Published: 2024
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19. Latent Hydraulic Effect of Ground Granulated Blast Furnace Slag on the Strength Development of Stabilized Peat

Author: Wong, Leong Sing, Alhaddad, Hasan Omar Ali, Bakri, Raed Saleh Ali Ba, Haider, Hattan Ahmed Ahmed, Oweida, Ahmed Farid Mahmoud, Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, Gawad, Iman O., Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, Çiner, Attila, editor, Ergüler, Zeynal Abiddin, editor, Bezzeghoud, Mourad, editor, Ustuner, Mustafa, editor, Eshagh, Mehdi, editor, El-Askary, Hesham, editor, Biswas, Arkoprovo, editor, Gasperini, Luca, editor, Hinzen, Klaus-Günter, editor, Karakus, Murat, editor, Comina, Cesare, editor, Karrech, Ali, editor, Polonia, Alina, editor, and Chaminé, Helder I., editor
Published: 2024
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20. Quality Infrastructure: Metrology, Accreditation, and Standards

Author: Kumar, Vinay, primary and Al-Bashrawi, Saleh Ali, additional
Published: 2024
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21. Salmonella (Salmonellosis and Typhoid Fever) Attack

Author: O’Neill, Ansley, primary, Alesa, Saleh Ali, additional, and Proano, Lawrence, additional
Published: 2024
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22. Contributors

Author: Adams, Axel, primary, Affun-Adegbulu, Clara, additional, Al-Rasheed, Rakan S., additional, Alaska, Yasser A., additional, Aldawas, Abdulaziz D., additional, Alesa, Saleh Ali, additional, Alexander, George A., additional, Alhadhira, Abdullah Ahmed, additional, Alhajjaj, Fahad Saleha, additional, Alhazmi, Hazem H., additional, Alhussaini, Zainab Abdullah, additional, Aljerian, Nawfal, additional, Aljohani, Majed, additional, AlKhaldi, Khaldoon H., additional, Alkhattabi, Eyad, additional, Allen, Bryant, additional, Almand, Austin, additional, Alnoaimi, Moza M., additional, Alotaibi, Mohammad, additional, Alpert, Evan Avraham, additional, Alrusayni, Yasir A., additional, Alshammari, Mai, additional, Alsulimani, Loui K., additional, Amanullah, Siraj, additional, Anderson, Arian, additional, Arastehmanesh, David, additional, Ardalan, Ali, additional, Argote-Araméndiz, Killiam A., additional, Artenstein, Andrew W., additional, Bailey, Olivia E., additional, Baker, Russell, additional, Balsari, Satchit, additional, Banner, Gregory T., additional, M, Fermin Barrueto, additional, Bartels, Susan A., additional, Baugh, Joshua J., additional, Berg, Frederic, additional, Bhola, Vijai, additional, Binder, William, additional, Bortolin, Michelangelo, additional, Bounes, Vincent, additional, Bouton, Michael, additional, Brown, Natasha, additional, Jr, Frederick M. Burkle,, additional, Burnett, Lynn Barkley, additional, Burns, Michele M., additional, Sr, Nicholas V. Cagliuso,, additional, Cahill, John, additional, Callaway, David W., additional, Caneva, Duane C., additional, Cattamanchi, Srihari, additional, Caycedo, Alejandra, additional, Cetaruk, Edward W., additional, Chacko, Sneha, additional, Chang, James C., additional, Chiang, Crystal, additional, Chiu, David T., additional, Ciottone, Gregory R., additional, Ciottone, Jonathan Peter, additional, Ciottone, Melissa A., additional, Ciottone, Robert A., additional, Ciottone, Robert G., additional, Ciottone, Vigen G., additional, Clark, Alexander, additional, Clark, Jonathan, additional, Conley, Sean P., additional, Cono, Joanne, additional, Cooper, Arthur, additional, Cormier, Scott B., additional, Court, Michael F., additional, Cunningham, Cord W., additional, Czarnecki, Fabrice, additional, Davis, Supriya, additional, Davis, Timothy E., additional, DeMers, Gerard, additional, Dilling, Sharon, additional, Djalali, Ahmadreza, additional, Donahoe, Timothy, additional, Donahue, Joseph, additional, Dresser, Caleb, additional, Dylik, Jason, additional, Easter, Benjamin, additional, Eastman, Alexander, additional, Ebbeling, Laura, additional, Emetarom, Chigozie, additional, Eyal, Nir, additional, Eyre, Andrew J., additional, Freeman, David J., additional, Friedman, Franklin D., additional, Fritz, Christie, additional, Fung, Frederick, additional, Gallahue, Fiona E., additional, Garbern, Stephanie Chow, additional, Gebhart, Mark E., additional, Gluckman, William A., additional, Goolsby, Craig, additional, Gougelet, Robert M., additional, Granholm, Fredrik, additional, Greenough, P. Gregg, additional, Grimes, Jennifer O., additional, Grosse, Steve, additional, Grossman, Shamai A., additional, Jr, John T. Groves, additional, Guidotti, Tee L., additional, Guo, George, additional, Haessler, Sarah, additional, Hall, Matthew M., additional, Hardin, John W., additional, Harrell, Mason, additional, Hart, MD, Alexander, additional, Harvey, Melissa, additional, Hertelendy, PhD, Attila J., additional, Hiremath, Nishanth S., additional, Hitchens, Jordan, additional, Holstege, Christopher P., additional, Horne, Simon T., additional, Horng, Steven, additional, Hosin, Amer, additional, House, Hans R., additional, Ingrassia, Pier Luigi, additional, Issa, Fadi S., additional, Jacoby, Irving “Jake”, additional, Jaiswal, Rajnish, additional, Jay, Gregory, additional, Jenkins, J. Lee, additional, Joseph, Josh W., additional, Kappler, Shane, additional, Keim, Mark E., additional, Kelman, Julie, additional, Ketterer, Andrew R., additional, Khan, Anas A., additional, Kharel, Ramu, additional, Kharod, Chetan U., additional, Kirsch, Thomas D., additional, Knopov, Anita, additional, Kravitz, Max, additional, Lee, J. Austin, additional, Lemery, Jay, additional, Leventhal, Evan L., additional, Loughlin, Jesse, additional, Ludy, Stephanie, additional, Maguire, Brian J., additional, Mahon, Selwyn E., additional, Maniscalco, Paul M., additional, Manners, Philip, additional, Marcus, Leonard Jay, additional, Margus, Colton, additional, Masri, Taha M., additional, Matthews, Jeff, additional, McKay, Sean D., additional, McKinney, Zeke J., additional, McLellan, Robert K., additional, McNulty, Eric J., additional, Mehkri, Faroukh, additional, Mehta, Mandana, additional, Mendelsohn, Rebecca A., additional, Merin, Ofer, additional, Milsten, Andrew, additional, Molé, Dale M., additional, Molloy, Michael Sean, additional, Morelli, Ilaria, additional, Mothershead, Jerry L., additional, Mulhern, John, additional, Mullendore, Nicole F., additional, Musisca, Nicholas J., additional, Naganathan, Sonya, additional, Nathanson, Larry A., additional, Nelson, Erica L., additional, Nelson, Lewis S., additional, Newbury, Bradford A., additional, Newbury, Kimberly, additional, O’Neill, Ansley, additional, Obernier, Robert, additional, Olagnero, Jacopo M., additional, Oostrom-Shah, Leonie, additional, Ordun, Catherine Y., additional, Parazynski, Scott, additional, Park, Andrew J., additional, Partridge, Robert, additional, S, Jeffrey, additional, Phillips, James P., additional, Pinter, Emily, additional, IV, David P. Polatty, additional, Popieluszko, Patrick, additional, Porcaro, William, additional, Proano, Lawrence, additional, Pruitt, Peter B., additional, Qureshi, Moiz, additional, Ragazzoni, Luca, additional, Rashid, Murtaza, additional, Rega, Paul Patrick, additional, Reilly, Michael J., additional, Restuccia, Marc C., additional, Rifino, James J., additional, Robben, Paul M., additional, Rosenblatt, Joy L., additional, Ryan, Kevin M., additional, Rybasack-Smith, Heather, additional, Salway, Richard James, additional, Samo, Daniel, additional, Sanchez, Leon D., additional, Sanford, Shawn M., additional, Sarin, Ritu R., additional, Sarma, Deesha, additional, Schacht, Jesse, additional, Schwind, Valarie, additional, Shapiro, Geoffrey L., additional, Sheehan, Joshua, additional, Shreve, Brian, additional, Simonyan, Grigor, additional, Smith, Devin M., additional, MD, E. Reed Smith,, additional, MA, Jack E. Smith,, additional, Smith, Montray, additional, Smulowitz, Peter B., additional, Snyder, Angela M., additional, Solano, Joshua J., additional, Stenson, Bryan A., additional, Stewart, Charles, additional, Stewart, M. Kathleen, additional, Sullivan, Patrick, additional, Supple, Jared S., additional, Tin, Derrick, additional, Valente, Jonathan Harris, additional, Vear, Kathryn M., additional, Vidyalakshmi, P.R., additional, Vilas, Faith, additional, Vilke, Gary M., additional, Villano, Janna H., additional, Voskanyan, Amalia, additional, Watson, C. James, additional, Weber, Nancy, additional, Weiner, Scott G., additional, Weinstein, Brielle, additional, Weinstein, Eric S., additional, Werner, Jordan R., additional, MD, Roy Karl Werner,, additional, Whitledge, James D., additional, Wiener, Sage W., additional, Wiesner, Lauren, additional, Williams, Kenneth A., additional, Wing, Robyn, additional, Wolfe, Richard E., additional, Wong, Wendy Hin-Wing, additional, Woolard, Robert, additional, Wuthisuthimethawee, Prasit, additional, and Youssef, Nadine A., additional
Published: 2024
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23. تأثير السعر على نية شراء الحجاج والمعتمرين الأجانب لمنتجات الأزياء والمنسوجات الثقافية السعودية

Author: Al-Hanouf Ali Muhammad Al-Shehri and Dr. Taghreed Saleh Ali Aba Al-Khail
Subjects: السعر، الحجاج، المعتمرين، منتجات، الأزياء، المنسوجات، الثقافية، نية الشراء, Social Sciences
Abstract: تم إجراء هذا البحث بهدف معرفة تأثير عامل السعر على نية شراء الحجاج والمعتمرين الأجانب لمنتجات الأزياء والمنسوجات الثقافية السعودية في سوق السياحة الدينية بمنطقة مكة المكرمة ،وتكونت عينة البحث من ٣٩٥حاج ومعتمر أجنبي ، من متحدثي اللغة العربية والإنجليزية ،كما استخدم البحث أداة الاستبانة لمعرفة تأثير عامل السعر على النية الشرائية لمنتجات الأزياء والمنسوجات الثقافية السعودية ،والمنهج الوصفي لقياس ذلك ،وكانت أبرز نتائج البحث وجود علاقة ارتباطية موجبة دالة إحصائيا بين سعر منتجات الأزياء والمنسوجات الثقافية السعودية، في سوق السياحة الدينية بمنطقة مكة المكرمة ونية شراء الحجاج والمعتمرين الأجانب لها.
Published: 2024
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24. Advanced integration of 2DCNN-GRU model for accurate identification of shockable life-threatening cardiac arrhythmias: a deep learning approach

Author: Abduljabbar S. Ba Mahel, Shenghong Cao, Kaixuan Zhang, Samia Allaoua Chelloug, Rana Alnashwan, and Mohammed Saleh Ali Muthanna
Subjects: dangerous arrhythmias, recognition, deep learning networks, data synthesis, scalogram, Physiology, QP1-981
Abstract: Cardiovascular diseases remain one of the main threats to human health, significantly affecting the quality and life expectancy. Effective and prompt recognition of these diseases is crucial. This research aims to develop an effective novel hybrid method for automatically detecting dangerous arrhythmias based on cardiac patients’ short electrocardiogram (ECG) fragments. This study suggests using a continuous wavelet transform (CWT) to convert ECG signals into images (scalograms) and examining the task of categorizing short 2-s segments of ECG signals into four groups of dangerous arrhythmias that are shockable, including ventricular flutter (C1), ventricular fibrillation (C2), ventricular tachycardia torsade de pointes (C3), and high-rate ventricular tachycardia (C4). We propose developing a novel hybrid neural network with a deep learning architecture to classify dangerous arrhythmias. This work utilizes actual electrocardiogram (ECG) data obtained from the PhysioNet database, alongside artificially generated ECG data produced by the Synthetic Minority Over-sampling Technique (SMOTE) approach, to address the issue of imbalanced class distribution for obtaining an accuracy-trained model. Experimental results demonstrate that the proposed approach achieves high accuracy, sensitivity, specificity, precision, and an F1-score of 97.75%, 97.75%, 99.25%, 97.75%, and 97.75%, respectively, in classifying all the four shockable classes of arrhythmias and are superior to traditional methods. Our work possesses significant clinical value in real-life scenarios since it has the potential to significantly enhance the diagnosis and treatment of life-threatening arrhythmias in individuals with cardiac disease. Furthermore, our model also has demonstrated adaptability and generality for two other datasets.
Published: 2024
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25. Evaluating future building energy efficiency and environmental sustainability with PCM integration in building envelope

Author: Kulumkanov, Nursat, Memon, Shazim Ali, and Khawaja, Saleh Ali
Published: 2024
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26. Next-Gen Connectivity: Exploring UAV Swarm Applications in Cell-Free Massive MIMO for IIoT

Author: Reem Alkanhel, Ghada Atteia, Mohamed Amine Ouamri, Mohammed Saleh Ali Muthanna, Daljeet Singh, Ahmed Aziz, and Ammar Muthanna
Subjects: IIoT, MIMO, power consumption, QoS, resource allocation, UAV’s network, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: The emergence of Industrial Internet of Things (IIoT) networks has sparked a demand for reliable and efficient communication systems. One promising strategy to overcome interference and coverage issues in IIoT setups is leveraging massive multiple-input multiple-output (MIMO) technology in a cell-free configuration. However, implementing large antenna arrays for such systems can be impractical and expensive, especially in remote or dynamic environments. Unmanned aerial vehicles (UAVs) have emerged as a versatile solution, including for communication relays. This study investigates the integration of UAV swarms into cell-free massive MIMO systems for IIoT networks. The proposed approach involves deploying a swarm of UAVs equipped with multiple antennas as aerial base stations to serve ground-based IIoT devices. It examines the benefits of employing UAV swarms, such as expanded coverage, better interference management, and increased flexibility. Additionally, it addresses challenges like UAV mobility, resource allocation, and power consumption. To address these challenges, an algorithm for resource allocation is proposed. This algorithm considers factors like UAV mobility, quality-of-service requirements for IIoT devices, and interference among UAVs. It aims to optimize transmit power and antenna selection for each UAV, ensuring QoS satisfaction and enhancing overall system capacity. Simulation results demonstrate the effectiveness of the algorithm, indicating improvements in system capacity, coverage, and interference management. Moreover, the findings highlight the trade-offs between system performance and power consumption within the UAV swarm. In essence, this study contributes to understanding the potential of utilizing UAV swarms in cell-free massive MIMO systems for IIoT networks. The proposed resource allocation algorithm offers insights for planning and enhancing such nodes, paving the way for further research and development in this promising field.
Published: 2024
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27. Reinforcement Learning for EV Fleet Smart Charging with On-Site Renewable Energy Sources

Author: Handong Li, Xuewu Dai, Stephen Goldrick, Richard Kotter, Nauman Aslam, and Saleh Ali
Subjects: reinforcement learning, renewable energy, EV fleet, ORES, Technology
Abstract: In 2020, the transportation sector was the second largest source of carbon emissions in the UK and in Newcastle upon Tyne, responsible for about 33% of total emissions. To support the UK’s target of reaching net zero emissions by 2050, electric vehicles (EVs) are pivotal in advancing carbon-neutral road transportation. Optimal EV charging requires a better understanding of the unpredictable output from on-site renewable energy sources (ORES). This paper proposes an integrated EV fleet charging schedule with a proximal policy optimization method based on a framework for deep reinforcement learning. For the design of the reinforcement learning environment, mathematical models of wind and solar power generation are created. In addition, the multivariate Gaussian distributions derived from historical weather and EV fleet charging data are utilized to simulate weather and charging demand uncertainty in order to create large datasets for training the model. The optimization problem is expressed as a Markov decision process (MDP) with operational constraints. For training artificial neural networks (ANNs) through successive transition simulations, a proximal policy optimization (PPO) approach is devised. The optimization approach is deployed and evaluated on a real-world scenario comprised of council EV fleet charging data from Leicester, UK. The results show that due to the design of the rewards function and system limitations, the charging action is biased towards the time of day when renewable energy output is maximum (midday). The charging decision by reinforcement learning improves the utilization of renewable energy by 2–4% compared to the random charging policy and the priority charging policy. This study contributes to the reduction in battery charging and discharging, electricity sold to the grid to create benefits and the reduction in carbon emissions.
Published: 2024
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28. A computer-based simulation methodology of the predetermined maintenance scheme of an irradiation facility

Author: Ismail, Mohammad Hisham, Chiachío, Manuel, Chiachío, Juan, Arranz, Fernando, and Saleh, Ali
Published: 2024
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29. An asset management modelling framework for wind turbine blades considering monitoring system reliability

Author: Wu, Wen, Prescott, Darren, Remenyte-Prescott, Rasa, Saleh, Ali, and Ruano, Manuel Chiachio
Published: 2024
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30. Dual wavelength signal generation with four wave mixing based on directly modulated laser

Author: Majeed, Majidah H., Ahmed, Riyadh Khlf, Alnasar, Suha I., Mahmood, Omar Abdulkareem, Muthanna, Mohammed Saleh Ali, and Muthanna, Ammar
Published: 2024
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31. The global burden of cancer attributable to risk factors, 2010–19: a systematic analysis for the Global Burden of Disease Study 2019

Author: Collaborators, GBD 2019 Cancer Risk Factors, Tran, Khanh Bao, Lang, Justin J, Compton, Kelly, Xu, Rixing, Acheson, Alistair R, Henrikson, Hannah Jacqueline, Kocarnik, Jonathan M, Penberthy, Louise, Aali, Amirali, Abbas, Qamar, Abbasi, Behzad, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abbastabar, Hedayat, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdelwahab, Ahmed Abdelwahab, Abdoli, Gholamreza, Abdulkadir, Hanan Abdulkadir, Abedi, Aidin, Abegaz, Kedir Hussein, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Absalan, Abdorrahim, Abtew, Yonas Derso, Ali, Hiwa Abubaker, Abu-Gharbieh, Eman, Achappa, Basavaprabhu, Acuna, Juan Manuel, Addison, Daniel, Addo, Isaac Yeboah, Adegboye, Oyelola A, Adesina, Miracle Ayomikun, Adnan, Mohammad, Adnani, Qorinah Estiningtyas Sakilah, Advani, Shailesh M, Afrin, Sumia, Afzal, Muhammad Sohail, Aggarwal, Manik, Ahinkorah, Bright Opoku, Ahmad, Araz Ramazan, Ahmad, Rizwan, Ahmad, Sajjad, Ahmad, Sohail, Ahmadi, Sepideh, Ahmed, Haroon, Ahmed, Luai A, Ahmed, Muktar Beshir, Rashid, Tarik Ahmed, Aiman, Wajeeha, Ajami, Marjan, Akalu, Gizachew Taddesse, Akbarzadeh-Khiavi, Mostafa, Aklilu, Addis, Akonde, Maxwell, Akunna, Chisom Joyqueenet, Hamad, Hanadi Al, Alahdab, Fares, Alanezi, Fahad Mashhour, Alanzi, Turki M, Alessy, Saleh Ali, Algammal, Abdelazeem M, Al-Hanawi, Mohammed Khaled, Alhassan, Robert Kaba, Ali, Beriwan Abdulqadir, Ali, Liaqat, Ali, Syed Shujait, Alimohamadi, Yousef, Alipour, Vahid, Aljunid, Syed Mohamed, Alkhayyat, Motasem, Al-Maweri, Sadeq Ali Ali, Almustanyir, Sami, Alonso, Nivaldo, Alqalyoobi, Shehabaldin, Al-Raddadi, Rajaa M, Al-Rifai, Rami H Hani, Al-Sabah, Salman Khalifah, Al-Tammemi, Ala'a B, Altawalah, Haya, Alvis-Guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Dehkordi, Javad Javad Aminian, Amirzade-Iranaq, Mohammad Hosein, Amu, Hubert, Amusa, Ganiyu Adeniyi, Ancuceanu, Robert, Anderson, Jason A, Animut, Yaregal Animut, Anoushiravani, Amir, Anoushirvani, Ali Arash, Ansari-Moghaddam, Alireza, Ansha, Mustafa Geleto, Antony, Benny, Antwi, Maxwell Hubert, Anwar, Sumadi Lukman, and Anwer, Razique
Subjects: Prevention, Cancer, Aetiology, 2.2 Factors relating to the physical environment, Good Health and Well Being, Female, Global Burden of Disease, Global Health, Humans, Male, Neoplasms, Quality-Adjusted Life Years, Risk Assessment, Risk Factors, Smoking, GBD 2019 Cancer Risk Factors Collaborators, Medical and Health Sciences, General & Internal Medicine
Abstract: BackgroundUnderstanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally.MethodsThe GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented.FindingsGlobally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01-4·94) deaths and 105 million (95·0-116) DALYs for both sexes combined, representing 44·4% (41·3-48·4) of all cancer deaths and 42·0% (39·1-45·6) of all DALYs. There were 2·88 million (2·60-3·18) risk-attributable cancer deaths in males (50·6% [47·8-54·1] of all male cancer deaths) and 1·58 million (1·36-1·84) risk-attributable cancer deaths in females (36·3% [32·5-41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6-28·4) and DALYs by 16·8% (8·8-25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9-42·8] and 33·3% [25·8-42·0]).InterpretationThe leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden.FundingBill & Melinda Gates Foundation.
Published: 2022

32. Scientific Research Hypotheses Understanding of the Pre-Service Science Teachers at Faculty of Education, Amran University, Yemen

Author: Al-Hadabi, Abddulsalam and Al-soudi, Mabrook Saleh Ali
Abstract: Preparing pre-service science teachers (PSSTs) with the scientific research skills (SRSs) is an ultimate aim of PSSTs' programs. This study aimed to explore PSSTs' understanding level of SRHs (SRHUL). To this end, an action research (AR) was adopted using a pre-post-test design. In doing so, a multiple choice test which consists of 15 items was developed and conducted on a random sample comprising 120 subjects. Results of the study revealed that participants showed insufficient performance on the test of understanding scientific research hypotheses (SRHUT) for both pre and post-test. Besides, results of t-test showed a significant difference between mean scores of pre-test and post-test. The difference was in favor of post-test. Also, results of one-way ANOVA revealed a non-significant difference between or within mean scores of compared groups. Based on the results of the study, some recommendations were made.
Published: 2020

33. How School Climate Predicts Teachers' Organizational Silence

Author: Alqarni, Saleh Ali Y.
Abstract: This study aims to explore the relationships between school climate constructs and teachers' organizational silence (OS) and to analyze how school climate predicts teachers' OS. The study population comprised all teachers (2,237) working in private primary schools in Jeddah, Saudi Arabia. The sample consisted of 329 responses, which represented 14.7% of the original population. Structural equation modeling for path analysis between the main constructs (teacher behavior, principal behavior) and teachers' organizational silence revealed the influence of principal behavior on teachers' silence was significant. However, the influence of teachers' behavior on teachers' silence was found to be non-significant. The relationships between teachers' OS and four school climate constructs (supportive principal behavior, directive principal behavior, collegial teacher behavior, intimate teacher behavior) were negative, while the relationships between teachers' organizational silence and two school climate scales (restrictive principal behavior, disengaged teacher behavior) were positive. It is recommended that top educational management officials develop relevant policy procedures, such as legislating necessary regulations to protect whistle-blowers in the school environment. Given the increased popularity of the Organizational Climate Description Questionnaire for Elementary Schools (OCDQ-RE) in measuring school typology, we encourage the use of this questionnaire to predict other teachers' behaviors in the school environment.
Published: 2020

34. Development and Validation of the Ethical Climate Questionnaire in a Saudi Educational Context

Author: Alqarni, Saleh Ali Y., Alsulami, Abdulrahman Ham, Alqarni, Ali Hasan, Alfadeel, Mohammad Akron, and Khan, Khushnoor
Abstract: The present study focuses on studying the psychometric properties of Ethical Climate Questionnaire (ECQ) in Saudi educational milieu. It is a cross-sectional study and the data was collected from 309 educational supervisors from six educational offices of General Department of Education in Jeddah. Confirmatory Factor Analysis (CFA) was carried out to study the psychometric properties of the EC scale. Kuder Richardson's Cronbach's coefficient '[alpha]' was used to assess the reliability of the nine dimensions of the EC scale. Findings of the study revealed that nine dimensions of the EC scale had a good model fit. Hence, it is suggested that EC scale is valid and reliable for use within the educational context in Saudi Arabia. This study also compares the findings of the current study with previous findings. Results of the present study will provide much-needed impetus for future research in EC particularly, within the educational organizations throughout Saudi Arabia and generally in other Arab countries of the region.
Published: 2020

35. Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics

Author: Zamani, Abu Sarwar, Hashim, Aisha Hassan Abdalla, Shatat, Abdallah Saleh Ali, Akhtar, Md. Mobin, Rizwanullah, Mohammed, and Mohamed, Sara Saadeldeen Ibrahim
Published: 2024
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36. 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, Alfiya, Alberico, Alfonso, Amendola, Alfonso, Sánchez-Terán, Alfonso Iván, Lapergola, Alfonso, Baiden Amissah, Alfred, Königsrainer, Alfred, Twumasi, Alfred, Alhebshi, Alhasan, Abbas, Ali, Abdul Rahman, Ali, Abidali, Ali, Abu Tair, Ali, Ahmad, Ali, Al Mukhtar, Ali, Sharq, Ali Al, Alloush, Ali, Amaigl, Ali, Kheirkhah Vakilabad, Ali Asghar, Bassma, Ali, Hacioglu, Ali Doruk, Elzanaty, Ali, Fani, Ali, Farsi, Ali, Ghummied, Ali, Hajali, Ali, Al Sharqi, Ali Hamed, Hammed, Ali, Hewari, Ali, Isler, Ali, Marouf, Ali, Uysal, Ali Mert, Murtada, Ali, Syed, Ali Naqi, Ozkomec, Ali, Sapmaz, Ali, Wassouf, Ali, Aldurssi, Alia, Polatbekov, Alibek, Caltagirone, Alice, Gori, Alice, Lim, Alicia, Bhatt, Alisha, Mohammed, Aljarrah, Maxwell, Allison, Kiyabayev, Almaz, Eltayeb, Almoutaz, Khamees, Almu'atasim, Abdalla, Alnazir, Pikarsky, Alon, Trigos Díaz, Alonso, A Elhars, Alshymaa, Alhaj Zain, Altayeb, Eltahir, Altayeb, Robin Valle De Lersundi, Alvaro, Sanad, Aly, Abdalhadi, Alya, Sparke, Alyssa, 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Ana Marta, Minaya-Bravo, Ana, Lourenço, Ana Rita, Mateus Loureiro, Ana Rita, Sánchez Gollarte, Ana, Tvaladze, Ana, Veira, Ana, Perja, Ana-Maria, Dusabimana, Anaclet, Herewini, Anahera, Fatima, Anam, Zafar, Anam, Bangar, Anant, Kutma, Ananta, Mehta, Ananya, Alqerem, Anas, Jaber, Anas, Mourtzouni, Anastasia, Theochari, Anastasia, Zarafidou, Anastasia, Smyrnis, Anastasios, Tsechpenakis, Anastasios, Zakaria, Andee Dzulkarnaen, Cardoso Almeida, Andre, Pita, André, Torbey, André, Abreu, Andrea, Barberis, Andrea, Bartalini Cinughi De Pazzi, Andrea, Belli, Andrea, Sironi, Andrea Carlo, Damigella, Andrea, Manetti, Andrea, Mingoli, Andrea, Natili, Andrea, Police, Andrea, Razzore, Andrea, Scacchi, Andrea, Vazquez Fernandez, Andrea, Luzzi, Andrea-Pierre, Brosin, Andreas, Efstathiou, Andreas, Kirschniak, Andreas, Panagakis, Andreas, Pilavas, Andreas, Scheiwiller, Andreas, Skarpas, Andreas, Chitul, Andrei, Trif, Andrei, Ferreira, Andreia, Silva, Andreia, Subocius, Andrejus, Cembellin, Andres, García 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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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Ioannis, Kozadinos, Ioannis, Margaris, Ioannis, Maroulis, Ioannis, Papaconstantinou, Ioannis, Siannis, Ioannis, Sougkas, Ioannis, Spyridakis, Ioannis, Tierris, Ioannis, Tsakiridis, Ioannis, Imihteev, Ion, Negoi, Ionut, Chatzis, Iosif, Shahbaz, Iqra, Didier, Irabishohoje, Pipia, Irakli, Parwaiz, Iram, Durán Sánchez, Iran Irani, Norman, Irena, Bakaweri, Irenaeus Nutumie, Santos, Irene, Mylona, Irene Chrysovalanto, De Haro Jorge, Irene, Cervera, Iria, Dajti, Irida, Datji, Irida, Matache, Irina Mihaela, Russo, Iris Shari, Aremu, Is'haq Ishola, Amankwaa, Isaac, Caitens, Isaac, Esparza Estrada, Isaac, Mubezi, Isaac, Gascon Ferrer, Isabel, Serrano, Isabel, Dong, Isabella, Mondi, Isabella, Serfontein, Isabella, Rakshit, Ishani, Kyei, Ishmael, Murshed, Ishraq, Cabrera, Ishtar, Abo Elhagag, Islam, Alsoubie, Ismael, Lawani, Ismail, Bilgin, Ismail Ahmet, Cholah, Ismail, Hamzaoglu, Ismail, Lawani, Ismaïl, Maharem, Israa, Shehadeh, Israa, Hagbevor, Israel, Bahikoro, Issa Wendpouiré, Laopeamthong, Issaree, Mikulic, Iva, Bacic, Ivan, Rakvin, Ivan, Separovic, Ivan, Vidić, Ivan, Conversano, Ivana, Mrazkova, Ivana, Yotsov, Ivelin, Ilieva, Ivelina, Ćoza, Ivo, Ali, Iyad, Aljada, Iyad, Hussein, Iyad, Tesfahun, Iyasu, Sadiq, Izzah, Martinez Martin Del Campo, J Francisco, Mackenzie, Jack, Maida, Jack Vittorio, Kaippally, Jacob, Montero García, Jacobo, Andreuccetti, Jacopo, Martellucci, Jacopo, Secchi, Jacopo, Van Niekerk, Jacques, Saunders, Jada, Duffield, Jaime A., Tavares-Ortega, Jaime Alberto, Orozco-Perez, Jaime, Mihanovic, Jakov, Woleský, Jakub, Bryan, James, Bundred, James, Cui, James, Glasbey, James, Casella Mariolo, James Rossario, Suliman, Jamil, Mohammad Mohammad, Jamiu, Bolanowski, Jan, Goedeke, Jan, Grosek, Jan, Moravik, Jan, Ringers, Jan, Roman, Jan, Chew, Janae, Maritz, Jancke, Martin, Janet, Velkoski, Jaqueline, Wong, Jason, García-Quijada, Javier, Tk, Jayakumar, Siby, Jayas, Mcnab-Hand, Jaymee, Gusa, JB, Gusa, Jean Bosco, Allen, Jean Claude, Mbonicura, Jean Claude, 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, Rodicio Miravalles, Jose Luis, Faylona, Jose Macario, Alvarez Hernandez, Jose Manuel, De Francisco Rios, Jose Mario, Martin Fernandez, Jose, Michel, José, Carlos, José Miguel, Mondino, Jose, Vieira De Sousa, José Pedro, Asturias Luna, José Rodrigo, Hernández, Jose Rodrigo, García, José Sebastian, Galea, Joseph, Hwang, Joseph, Leong, Joseph, Yorke, Joseph, Psaila, Josephine, Walshaw, Josephine, Ampadu, Joshua, Linker, Joshua, Ng-Kamstra, Joshua, Olorunfunmi, Joshua, Mavrek, Josip, Miskovic, Josip, Petric, Josipa, Avakoudjo, Josue, Al Karmi, Joud, Fahed, Joud, Suleiman Hadidi, Joudd, Alkharish, Joul, Juloski, Jovan, Vaitekūnas, Jovydas, Wang, Joyce, Flores Prado, Juan Armando, Beltrán De Heredia, Juan, Garcia Vera, Juan Carlos, Molina Marin, Juan David, Gonzalez Aboytes, Juan Eduardo, Ulloa Robles, Juan Jose, Blas Laina, Juan Luis, Carranza Rosales, Juan Manuel, Morales, Juan, Naranjo Fernández, Juan Ramón, Al Daradkah, Jude, Aseme, Jude, Ede, Jude, Kahn, Judith, Lindert, Judith, Deeb, 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, 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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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37. IoMT-based smart healthcare monitoring system using adaptive wavelet entropy deep feature fusion and improved RNN

Author: Akhtar, MD. Mobin, Shatat, Raid Saleh Ali, Shatat, Abdallah Saleh Ali, Hameed, Shabi Alam, and Ibrahim Alnajdawi, Sakher (M.A)
Published: 2023
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38. MapReduce with Deep Learning Framework for Student Health Monitoring System using IoT Technology for Big Data

Author: Akhtar, Md. Mobin, Shatat, Abdallah Saleh Ali, Al-Hashimi, Mukhtar, Zamani, Abu Sarwar, Rizwanullah, Mohammed, Mohamed, Sara Saadeldeen Ibrahim, and Ayub, Rashid
Published: 2023
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39. Antimicrobial and antioxidant potential of the silver nanoparticles synthesized using aqueous extracts of coconut meat (Cocos nucifera L)

Author: Rizwana, Humaira, Aljowaie, Reem M., Al Otibi, Fatimah, Alwahibi, Mona S., Alharbi, Saleh Ali, Al asmari, Saeed Ali, Aldosari, Noura S., and Aldehaish, Horiah A.
Published: 2023
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40. DNA-PK hyperactivation occurs in deletion 11q chronic lymphocytic leukemia and is both a biomarker and therapeutic target for drug-resistant disease

Author: Kost, Sara E. F., Saleh, Ali, Yuan, Shek H., Kuzio, Bozena, Gibson, Spencer B., Yang, Lin, Banerji, Versha, Johnston, James B., and Katyal, Sachin
Published: 2023
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41. Rate of obesity within a mixed-breed group of horses in Ireland and their owners’ perceptions of body condition and useability of an equine body condition scoring scale

Author: Golding, Emma, Al Ansari, Ahmed Saleh Ali, Sutton, Gila A., Walshe, Nicola, and Duggan, Vivienne
Published: 2023
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42. The effects of instrument lubricants on the physical and mechanical properties of resin-based composites

Author: Alqahtani, Saleh Ali M.
Abstract: Uncured resin-based composites (RBCs) tend to stick to the placement instrument instead of cavity walls, potentially increasing void formation and margin discrepancy. Instrument lubricants (ILs) are used to overcome this problem, but they may affect the properties of RBC restorations. One hundred registered UK dentists were surveyed using a bespoke questionnaire to investigate their perspective on IL use and understand why and how they used them. Additionally, different laboratory investigations were conducted, based on the survey data, to test the effects of ILs on the physical and mechanical properties of RBCs. Two RBCs were treated with three classes of ILs -solvents, bonding agents and wetting resins -to investigate the effects different ILs have on the physical and mechanical properties of RBCs. Several areas were tested: degree of conversion, water uptake, Martens hardness, diametral tensile strength, microtensile bonding strength (μTBS), and the appearance of changes at the increment interface. The survey revealed that about 50% of the dentists used lubricants (32% response rate), of which bonding agents (67%) and wetting resins (33%) were most common. These were applied with microbrushes (47%) and by wiping the placement instruments (40%). The solvents, bonding agents and wetting resins created significant reductions in diametral tensile strength and Martens hardness, and increased water uptake compared to control groups fabricated without lubricants. The μTBS significantly reduced following treatment with solvents and bonding agents, but there was no reduction from the wetting resins. The respondents used lubricants to aid manipulation during placement. However, these materials have an impact upon physical and mechanical properties with solvents and bonding agents having the greater effect. Therefore, the use of ILs to manipulate the RBC should be limited or avoided.
Published: 2022

43. Theoretical analysis of some thin-film flows over complex surfaces

Author: Alshaikhi, Abdulwahed Saleh Ali, Grinfeld, Michael, and Wilson, Stephen K.
Abstract: In this thesis, three different aspects of thin-film flow over complex surfaces are investigated. First, locally-unidirectional rivulet flow on a slippery surface is considered. We study rivulets with prescribed flux and either fixed semi-width or fixed contact angle. In both cases we determined the effect of varying the slip length on the rivulet. We found that in the limit of strong slip, for a rivulet of a perfectly wetting fluid and a rivulet with constant = width, the velocity becomes large and plug-like, and the rivulet becomes shallow, while for a rivulet with positive constant contact angle, the velocity becomes large and plug-like, and the rivulet becomes narrow and shallow. Second, rivulet flow over and through a permeable membrane is considered. We study rivulets with prescribed flux and either fixed semi-width or fixed contact angle. We found that whereas there is a physically realisable pendant rivulet solution only if the semi-width does not exceed a critical value, there are physically realisable sessile and vertical rivulet solutions for all values of the semi-width; moreover, a sessile rivulet with fixed semi-width has a finite maximum possible length which is attained in the limit of a wide rivulet. Lastly, patterns formed in a two-dimensional thin film with a Derjaguin-type disjoining pressure on a planar substrate with periodic wettability stripes is considered. Using Liapunov-Schmidt reduction, we study the local bifurcation structure of the problem for spatially homogeneous disjoining pressure and how the structure depends on the average film thickness. Using methods of local bifurcation theory and the continuation software package AUTO, we perform a continuation analysis of the steady state solutions and establish the existence of both nucleation and metastable regimes. The dependence of the steady state solutions on the wettability contrast are investigated for two forms of spatially non-homogeneous disjoining pressure.
Published: 2022
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44. Effects on the compressive strength of cement-stabilized rammed earth blocks with varied content of buffelgrass-based fibers in wet-dry conditions

Author: Federico Pederson, Reuel Florendo, Saleh Ali Khawaja, Kirk Dimond, and Hee-Jeong Kim
Subjects: rammed earth, cement stabilized rammed earth, plant fibers, buffelgrass, fiber reinforced, Engineering (General). Civil engineering (General), TA1-2040, City planning, HT165.5-169.9
Abstract: Stabilized rammed earth blocks have been an alternative building material around the world due to their cost efficiency, low embodied energy, and environmental footprints. However, the lower compressive strength and resistance to wearing limits their use in comparison to higher-cost alternatives. The integration of fibers in rammed earth blocks has been a promising technique for enhancing their properties. In this research, the viability of buffelgrass as a reinforcing fiber in stabilized earth blocks was determined. The buffelgrass was incorporated into the mix up to 5% by weight for samples with the increment of 1% for each mix and the durability was determined under wet and dry conditions. In addition, the influence of the buffelgrass on the compressive strength was observed and the optimum content was determined. The morphological characteristics were observed using SEM imaging of the rammed earth and fiber interaction at a fracture surface. The results showed the inclusion of buffelgrass helps the wear resistance of the earth blocks when exposed to wet-dry conditions as well as slightly improving the compressive strength of the material after dry and wet curing.
Published: 2024
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45. العوامل الانذارية لدى مرضى رضوض الراس الشديدة

Author: Yasser Al-Hamoud, Muhammad Saleh Ali, and Mofid Mahfouz
Subjects: Medicine
Abstract: النتائج: أجريت الدراسة على 200 مريض، 40 منهم إناث(20%) و 160 ذكور (80%) . توفي منهم 123 مريض (61.5%) ، متوسط الأعمار 23 ± 42 سنة و متوسط مقياس غلاسكو 2± 6 . عند دراسة المتغيرات المؤثرة على تخريج أو وفاة المرضى لم نجد تأثير للعمر وجنس المريض، المرضى ذو مقياس غلاسكو أعلى والمرضى ذو ضغط أوكسجيني أعلى غالباً سيبقون على قيد الحياة. لوحظ أن عدم تفاعل الحدقات والإصابة بارتفاع التوتر الشرياني له دور في التأثير على حدوث الوفاة بعد التعرض لرض بالرأس. تمت دراسة عوامل الإنذار عند المرضى الذين تم تخريجهم ولوحظ أن الإنذار الجيد يترافق مع عمر أقل و تفاعل الحدقات و مقياس غلاسكو أعلى و حالة نزف فوق جافية وضغط أوكسجيني طبيعي. الإنذار الجيد لا يترافق مع انمحاء الصهاريج ويكون الإنذار أسوأ في حالة موجودات الطبقي المحوسب للرأس مرضية عدا نزف فوق الجافية يكون الإنذار أفضل. لا يختلف الإنذار باختلاف الضغط الشرياني أو الجنس أو وجود جراحات سابقة.
Published: 2024

46. Deep transfer learning with gravitational search algorithm for enhanced plant disease classification

Author: Mehdhar S.A.M. Al-Gaashani, Nagwan Abdel Samee, Reem Alkanhel, Ghada Atteia, Hanaa A. Abdallah, Asadulla Ashurov, and Mohammed Saleh Ali Muthanna
Subjects: Deep learning, Plant disease, Gravitational search algorithm, Convolutional neural network, Transfer learning, Science (General), Q1-390, Social sciences (General), H1-99
Abstract: Plant diseases annually cause damage and loss of much of the crop, if not its complete destruction, and this constitutes a significant challenge for farm owners, governments, and consumers alike. Therefore, identifying and classifying diseases at an early stage is very important in order to sustain local and global food security. In this research, we designed a new method to identify plant diseases by combining transfer learning and Gravitational Search Algorithm (GSA). Two state-of-the-art pretrained models have been adopted for extracting features in this study, which are MobileNetV2 and ResNe50V2. Multilayer feature extraction is applied in this study to ensure representations of plant leaves from different levels of abstraction for precise classification. These features are then concatenated and passed to GSA for optimizing them. Finally, optimized features are passed to Multinomial Logistic Regression (MLR) for final classification. This integration is essential for categorizing 18 different types of infected and healthy leaf samples. The performance of our approach is strengthened by a comparative analysis that incorporates features optimized by the Genetic Algorithm (GA). Additionally, the MLR algorithm is contrasted with K-Nearest Neighbors (KNN). The empirical findings indicate that our model, which has been refined using GSA, achieves very high levels of precision. Specifically, the average precision for MLR is 99.2%, while for KNN it is 98.6%. The resulting results significantly exceed those achieved with GA-optimized features, thereby highlighting the superiority of our suggested strategy. One important result of our study is that we were able to decrease the number of features by more than 50%. This reduction greatly reduces the processing requirements without sacrificing the quality of the diagnosis. This work presents a robust and efficient approach to the early detection of plant diseases. The work demonstrates the utilization of sophisticated computational methods in agriculture, enabling the development of novel data-driven strategies for plant health management, therefore enhancing worldwide food security.
Published: 2024
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47. Simplified models for unsteady three-dimensional flows in slowly varying microchannels

Author: Issa, Leila, Medlej, Sajed, Saleh, Ali, and Lakkis, Issam
Subjects: Physics - Fluid Dynamics
Abstract: We present a reduced order model for three dimensional unsteady pressure-driven flows in micro-channels of variable cross-section. This fast and accurate model is valid for long channels, but allows for large variations in the channel's cross-section along the axis. It is based on an asymptotic expansion of the governing equations in the aspect ratio of the channel. A finite Fourier transform in the plane normal to the flow direction is used to solve for the leading order axial velocity. The corresponding pressure and transverse velocity are obtained via a hybrid analytic-numerical scheme based on recursion. The channel geometry is such that one of the transverse velocity components is negligible, and the other component, in the plane of variation of channel height, is obtained from combination of the corresponding momentum equation and the continuity equations, assuming a low degree polynomial Ansatz of the pressure forcing. A key feature of the model is that it puts no restriction on the time dependence of the pressure forcing, in terms of shape and frequency, as long as the advective component of the inertia term is small. This is a major departure from many previous expositions which assume harmonic forcing. The model reveals to be accurate for a wide range of parameters and is two orders of magnitude faster than conventional three dimensional CFD simulations.
Published: 2021

48. Combination Therapy with Enalapril and Paricalcitol Ameliorates Streptozotocin Diabetes-Induced Testicular Dysfunction in Rats via Mitigation of Inflammation, Apoptosis, and Oxidative Stress

Author: Magdy Y. Elsaeed, Osama Mahmoud Mehanna, Ezz-Eldin E. Abd-Allah, Mohamed Gaber Hassan, Walid Mostafa Said Ahmed, Abd El Ghany A. Moustafa, Gaber E. Eldesoky, Amal M. Hammad, Usama Bahgat Elgazzar, Mohamed R. Elnady, Fatma M. Abd-Allah, Walaa M. Shipl, Amr Mohamed Younes, Mostafa Rizk Magar, Ahmed E. Amer, Mohamed Ali Mahmoud Abbas, Khaled Saleh Ali Elhamaky, and Mohammed Hussien Mohammed Hassan
Subjects: diabetes, enalapril, oxidative stress, paricalcitol, testicular dysfunction, Physiology, QP1-981
Abstract: Background: As the impacts of diabetes-induced reproductive damage are now evident in young people, we are now in urgent need to devise new ways to protect and enhance the reproductive health of diabetic people. The present study aimed to evaluate the protective effects of enalapril (an ACE inhibitor) and paricalcitol (a vitamin D analog), individually or in combination, on streptozotocin (STZ)-diabetes-induced testicular dysfunction in rats and to identify the possible mechanisms for this protection. Material and methods: This study was carried out on 50 male Sprague-Dawley rats; 10 normal rats were allocated as a non-diabetic control group. A total of 40 rats developed diabetes after receiving a single dose of STZ; then, the diabetic rats were divided into four groups of equivalent numbers assigned as diabetic control, enalapril-treated, paricalcitol-treated, and combined enalapril-and-paricalcitol-treated groups. The effects of mono and combined therapy with paricalcitol and enalapril on testicular functions, sperm activity, glycemic state oxidative stress, and inflammatory parameters, as well as histopathological examinations, were assessed in comparison with the normal and diabetic control rats. Results: As a result of diabetes induction, epididymal sperm count, sperm motility, serum levels of testosterone, follicle-stimulating hormone (FSH) as well as luteinizing hormone (LH), and the antioxidant enzyme activities, were significantly decreased, while abnormal sperm (%), insulin resistance, nitric oxide (NO), malondialdehyde (MDA), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were significantly increased, along with severe distortion of the testicular structure. Interestingly, treatment with paricalcitol and enalapril, either alone or in combination, significantly improved the sperm parameters, increased antioxidant enzyme activities in addition to serum levels of testosterone, FSH, and LH, reduced insulin resistance, IL-6, and TNF-α levels, and finally ameliorated the diabetes-induced testicular oxidative stress and histopathological damage, with somewhat superior effect for paricalcitol monotherapy and combined therapy with both drugs compared to monotherapy with enalapril alone. Conclusions: Monotherapy with paricalcitol and its combination therapy with enalapril has a somewhat superior effect in improving diabetes-induced testicular dysfunction (most probably as a result of their hypoglycemic, antioxidant, anti-inflammatory, and anti-apoptotic properties) compared with monotherapy with enalapril alone in male rats, recommending a synergistic impact of both drugs.
Published: 2023
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49. Antimicrobial and antioxidant potential of the silver nanoparticles synthesized using aqueous extracts of coconut meat (Cocos nucifera L)

Author: Humaira Rizwana, Reem M. Aljowaie, Fatimah Al Otibi, Mona S. Alwahibi, Saleh Ali Alharbi, Saeed Ali Al asmari, Noura S. Aldosari, and Horiah A. Aldehaish
Subjects: Medicine, Science
Abstract: Abstract Human pathogenic fungi and bacteria pose a huge threat to human life, accounting for high rates of mortality every year. Unfortunately, the past few years have seen an upsurge in multidrug resistance pathogens. Consequently, finding an effective alternative antimicrobial agent is of utmost importance. Hence, this study aimed to phytofabricate silver nanoparticles (AgNPs) using aqueous extracts of the solid endosperm of Cocos nucifera L, also known as coconut meat (Cm). Green synthesis is a facile, cost-effective and eco-friendly methods which has several benefits over other physical and chemical methods. The synthesized nanoparticles were characterized by UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and dynamic light scattering (DLS). The Cm-AgNPs showed a UV–Vis peak at 435 nm and were crystalline and quasi-spherical, with an average size of 15 nm. The FTIR spectrum displayed functional groups of phenols, alkaloids, sugars, amines, and carbonyl compounds, which are vital in the reduction and capping of NPs. The antibacterial and anticandidal efficacy of the Cm-AgNPs was assessed by the agar-well diffusion method and expressed as a zone of inhibition (ZOI). Amongst all the test isolates, Staphylococcus epidermidis, Candida auris, and methicillin-resistant Staphylococcus epidermidis were more susceptible to the NPs with a ZOI of 26.33 ± 0.57 mm, 19.33 ± 0.57 mm, and 18 ± 0.76 mm. The MIC and MFC values for Candida spp. were higher than the bacterial test isolates. Scanning electron microscopic studies of all the test isolates at their MIC concentrations showed drastically altered cell morphology, indicating that the NPs could successfully cross the cell barrier and damage the cell integrity, causing cell death. This study reports the efficacy of Cm-AgNPs against several Candida and bacterial strains, which had not been reported in earlier studies. Furthermore, the synthesized AgNPs exhibited significant antioxidant activity. Thus, the findings of this study strongly imply that the Cm-AgNPs can serve as promising candidates for therapeutic applications, especially against multidrug-resistant isolates of Candida and bacteria. However, further investigation is needed to understand the mode of action and biosafety.
Published: 2023
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50. Experimental assessment of the effect of black dye and water depth on the performance of PV/solar distiller

Author: Ahmed, Omer K., Algburi, Sameer, Jasim, Maryam A., Taha, Taha A., Saleh, Ali M., and Yassin, Khalil F.
Published: 2024
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