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50 results on '"Ahmad, Nasir"'

1. Ornstein-Uhlenbeck Adaptation as a Mechanism for Learning in Brains and Machines

Author

Fernandez, Jesus Garcia, Ahmad, Nasir, and van Gerven, Marcel

Subjects
Computer Science - Machine Learning
Abstract

Learning is a fundamental property of intelligent systems, observed across biological organisms and engineered systems. While modern intelligent systems typically rely on gradient descent for learning, the need for exact gradients and complex information flow makes its implementation in biological and neuromorphic systems challenging. This has motivated the exploration of alternative learning mechanisms that can operate locally and do not rely on exact gradients. In this work, we introduce a novel approach that leverages noise in the parameters of the system and global reinforcement signals. Using an Ornstein-Uhlenbeck process with adaptive dynamics, our method balances exploration and exploitation during learning, driven by deviations from error predictions, akin to reward prediction error. Operating in continuous time, Orstein-Uhlenbeck adaptation (OUA) is proposed as a general mechanism for learning dynamic, time-evolving environments. We validate our approach across diverse tasks, including supervised learning and reinforcement learning in feedforward and recurrent systems. Additionally, we demonstrate that it can perform meta-learning, adjusting hyper-parameters autonomously. Our results indicate that OUA provides a viable alternative to traditional gradient-based methods, with potential applications in neuromorphic computing. It also hints at a possible mechanism for noise-driven learning in the brain, where stochastic neurotransmitter release may guide synaptic adjustments.

Published
2024

2. Correlations Are Ruining Your Gradient Descent

Author

Ahmad, Nasir

Subjects
Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Herein the topics of (natural) gradient descent, data decorrelation, and approximate methods for backpropagation are brought into a common discussion. Natural gradient descent illuminates how gradient vectors, pointing at directions of steepest descent, can be improved by considering the local curvature of loss landscapes. We extend this perspective and show that to fully solve the problem illuminated by natural gradients in neural networks, one must recognise that correlations in the data at any linear transformation, including node responses at every layer of a neural network, cause a non-orthonormal relationship between the model's parameters. To solve this requires a method for decorrelating inputs at each individual layer of a neural network. We describe a range of methods which have been proposed for decorrelation and whitening of node output, and expand on these to provide a novel method specifically useful for distributed computing and computational neuroscience. Implementing decorrelation within multi-layer neural networks, we can show that not only is training via backpropagation sped up significantly but also existing approximations of backpropagation, which have failed catastrophically in the past, benefit significantly in their accuracy and convergence speed. This has the potential to provide a route forward for approximate gradient descent methods which have previously been discarded, training approaches for analogue and neuromorphic hardware, and potentially insights as to the efficacy and utility of decorrelation processes in the brain., Comment: 15 pages, 4 figures

Published
2024

3. Subspace Node Pruning

Author

Offergeld, Joshua, van Gerven, Marcel, and Ahmad, Nasir

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing
Abstract

Efficiency of neural network inference is undeniably important in a time where commercial use of AI models increases daily. Node pruning is the art of removing computational units such as neurons, filters, attention heads, or even entire layers to significantly reduce inference time while retaining network performance. In this work, we propose the projection of unit activations to an orthogonal subspace in which there is no redundant activity and within which we may prune nodes while simultaneously recovering the impact of lost units via linear least squares. We identify that, for effective node pruning, this subspace must be constructed using a triangular transformation matrix, a transformation which is equivalent to and unnormalized Gram-Schmidt orthogonalization. We furthermore show that the order in which units are orthogonalized can be optimised to maximally reduce node activations in our subspace and thereby form a more optimal ranking of nodes. Finally, we leverage these orthogonal subspaces to automatically determine layer-wise pruning ratios based upon the relative scale of node activations in our subspace, equivalent to cumulative variance. Our proposed method reaches state of the art when pruning ImageNet trained VGG-16 and rivals more complex state of the art methods when pruning ResNet-50 networks across a range of pruning ratios., Comment: 16 pages, 6 figures, 5 tables

Published
2024

4. Efficient Deep Learning with Decorrelated Backpropagation

Author

Dalm, Sander, Offergeld, Joshua, Ahmad, Nasir, and van Gerven, Marcel

Subjects
Computer Science - Machine Learning
Abstract

The backpropagation algorithm remains the dominant and most successful method for training deep neural networks (DNNs). At the same time, training DNNs at scale comes at a significant computational cost and therefore a high carbon footprint. Converging evidence suggests that input decorrelation may speed up deep learning. However, to date, this has not yet translated into substantial improvements in training efficiency in large-scale DNNs. This is mainly caused by the challenge of enforcing fast and stable network-wide decorrelation. Here, we show for the first time that much more efficient training of very deep neural networks using decorrelated backpropagation is feasible. To achieve this goal we made use of a novel algorithm which induces network-wide input decorrelation using minimal computational overhead. By combining this algorithm with careful optimizations, we obtain a more than two-fold speed-up and higher test accuracy compared to backpropagation when training a 18-layer deep residual network. This demonstrates that decorrelation provides exciting prospects for efficient deep learning at scale.

Published
2024

5. A Named Entity Recognition and Topic Modeling-based Solution for Locating and Better Assessment of Natural Disasters in Social Media

Author

Mehmood, Ayaz, Zamir, Muhammad Tayyab, Ayub, Muhammad Asif, Ahmad, Nasir, and Ahmad, Kashif

Subjects
Computer Science - Computation and Language
Abstract

Over the last decade, similar to other application domains, social media content has been proven very effective in disaster informatics. However, due to the unstructured nature of the data, several challenges are associated with disaster analysis in social media content. To fully explore the potential of social media content in disaster informatics, access to relevant content and the correct geo-location information is very critical. In this paper, we propose a three-step solution to tackling these challenges. Firstly, the proposed solution aims to classify social media posts into relevant and irrelevant posts followed by the automatic extraction of location information from the posts' text through Named Entity Recognition (NER) analysis. Finally, to quickly analyze the topics covered in large volumes of social media posts, we perform topic modeling resulting in a list of top keywords, that highlight the issues discussed in the tweet. For the Relevant Classification of Twitter Posts (RCTP), we proposed a merit-based fusion framework combining the capabilities of four different models namely BERT, RoBERTa, Distil BERT, and ALBERT obtaining the highest F1-score of 0.933 on a benchmark dataset. For the Location Extraction from Twitter Text (LETT), we evaluated four models namely BERT, RoBERTa, Distil BERTA, and Electra in an NER framework obtaining the highest F1-score of 0.960. For topic modeling, we used the BERTopic library to discover the hidden topic patterns in the relevant tweets. The experimental results of all the components of the proposed end-to-end solution are very encouraging and hint at the potential of social media content and NLP in disaster management., Comment: 15 pages; 4 tables; 4 figures

Published
2024

6. Social Media and Artificial Intelligence for Sustainable Cities and Societies: A Water Quality Analysis Use-case

Author

Auyb, Muhammad Asif, Zamir, Muhammad Tayyab, Khan, Imran, Naseem, Hannia, Ahmad, Nasir, and Ahmad, Kashif

Subjects
Computer Science - Social and Information Networks, Computer Science - Computation and Language
Abstract

This paper focuses on a very important societal challenge of water quality analysis. Being one of the key factors in the economic and social development of society, the provision of water and ensuring its quality has always remained one of the top priorities of public authorities. To ensure the quality of water, different methods for monitoring and assessing the water networks, such as offline and online surveys, are used. However, these surveys have several limitations, such as the limited number of participants and low frequency due to the labor involved in conducting such surveys. In this paper, we propose a Natural Language Processing (NLP) framework to automatically collect and analyze water-related posts from social media for data-driven decisions. The proposed framework is composed of two components, namely (i) text classification, and (ii) topic modeling. For text classification, we propose a merit-fusion-based framework incorporating several Large Language Models (LLMs) where different weight selection and optimization methods are employed to assign weights to the LLMs. In topic modeling, we employed the BERTopic library to discover the hidden topic patterns in the water-related tweets. We also analyzed relevant tweets originating from different regions and countries to explore global, regional, and country-specific issues and water-related concerns. We also collected and manually annotated a large-scale dataset, which is expected to facilitate future research on the topic., Comment: 11 pages, 6 figures, and 3 tables

Published
2024

8. Stylometry Analysis of Multi-authored Documents for Authorship and Author Style Change Detection

Author

Zamir, Muhammad Tayyab, Ayub, Muhammad Asif, Gul, Asma, Ahmad, Nasir, and Ahmad, Kashif

Subjects
Computer Science - Computation and Language
Abstract

In recent years, the increasing use of Artificial Intelligence based text generation tools has posed new challenges in document provenance, authentication, and authorship detection. However, advancements in stylometry have provided opportunities for automatic authorship and author change detection in multi-authored documents using style analysis techniques. Style analysis can serve as a primary step toward document provenance and authentication through authorship detection. This paper investigates three key tasks of style analysis: (i) classification of single and multi-authored documents, (ii) single change detection, which involves identifying the point where the author switches, and (iii) multiple author-switching detection in multi-authored documents. We formulate all three tasks as classification problems and propose a merit-based fusion framework that integrates several state-of-the-art natural language processing (NLP) algorithms and weight optimization techniques. We also explore the potential of special characters, which are typically removed during pre-processing in NLP applications, on the performance of the proposed methods for these tasks by conducting extensive experiments on both cleaned and raw datasets. Experimental results demonstrate significant improvements over existing solutions for all three tasks on a benchmark dataset., Comment: Tables 7, pages 4

Published
2024

9. Efficacy of arginine kinase as a promising RNAi target in Aphis gossypii genome as revealed through aphid bioassay on field-grown transgenic cotton plants

Author

Iqra Yousaf, Bushra Tabassum, Basit Jabbar, Muhammad Arslan Amjad, Uzma Qaisar, Anwar Khan, Rida Khalid, Olawale Samuel Adeyinka, and Idrees Ahmad Nasir

Subjects
arginine kinase, cotton aphid, rnai target, transgenic cotton, Plant culture, SB1-1110
Abstract

The cotton aphid Aphis gossypii is a major agricultural pest of cotton that causes substantial damage to the crop not only by sucking sap but also through virus transmission. Globally adopted traditional and contemporary approaches to control aphid infestation have certain limitations and are hazardous to human health. RNA interference (RNAi) technology has unfolded its potential as an effective crop protection strategy against various pests. In this study, we adopted plant-mediated RNAi strategy to enhance aphid resistance in cotton by targeting arginine kinase (AK), which is a crucial enzyme responsible for energy homeostasis in insects. We selected a 312bp dsRNA fragment containing eight siRNAs and showing optimum GC content, Hb index, and stable secondary structure based on computational prediction studies. The binary construct expressing dsRNA was used to transform local cotton variety MNH886 and four transgenic lines were obtained in the T1 generation. Out of the four T1 transgenic cotton lines, dsA-7 exhibited the highest aphid mortality (73.3%), whereas, dsA-1, dsA-3 and dsA-6 revealed 60%, 61%, and 66.6% aphid mortality, respectively, in comparison to 13.3% mortality in the mock control cotton line. Moreover, significant knockdown in mRNA expression of AK was observed in aphids fed dsA-7 which was 79%. In comparison, 54%, 47%, and 45% downregulation was recorded in aphids which fed on dsA-6, dsA-3, and dsA-1 transgenic cotton lines, respectively. These results revealed that plant-mediated downregulation of aphid RNA induced significant RNA interference in A. gossypii which resulted in considerable aphid mortality and led to plant protection against aphids.

Published
2024
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10. Upgrading Bio-Oil through Esterification-HDO Process: Optimization of Temperature and Mass Ratio of Fe-Co Mixed Metal Oxide Catalyst Supported by Mordenite

Author

Pulungan, Ahmad Nasir, primary, Nurfajriani, Nurfajriani, additional, Kembaren, Agus, additional, Sihombing, Junifa Layla, additional, Hasibuan, Muhammad Irvan, additional, Rahayu, Rahayu, additional, Salomo, Saud, additional, Hidayah, Nurul, additional, and Br Ginting, Feby Erna, additional

Published
2024
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15. Biosynthesis of copper nanoparticles using Alstonia scholaris leaves and its antimicrobial studies

Author

Ahmad Nasir Labaran, Zakariyya Uba Zango, Giriraj Tailor, Ahmed Alsadig, Fahad Usman, Muhammad Tukur Mukhtar, Alhassan Muhammad Garba, Raed Alhathlool, Khalid Hassan Ibnaouf, and Osamah A. Aldaghri

Subjects
Alstonia scholaris, Antimicrobial, Copper nanoparticles, Characterization, Extract, Medicine, Science
Abstract

Abstract The utilization of plants for the production of metallic nanoparticles is gaining significant attention in research. In this study, we conducted phytochemical screening of Alstonia scholaris (A. scholaris) leaves extracts using various solvents, including chloroform, ethyl acetate, n-hexane, methanol, and water. Our findings revealed higher proportions of flavonoids and alkaloids in both solvents compared to other phytochemical species. In the methanol, extract proteins, anthraquinone and reducing sugar were not detected. On the other hand, the aqueous extract demonstrated the presence of amino acids, reducing sugar, phenolic compounds, anthraquinone, and saponins. Notably, ethyl acetate and chloroform extracts displayed the highest levels of bioactive compounds among all solvents. Intrigued by these results, we proceeded to investigate the antibacterial properties of the leaf extracts against two major bacterial strains, Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). All extracts exhibited significant zones of inhibition against both bacterial isolates, with S. aureus showing higher susceptibility compared to E. coli. Notably, the methanol extract displayed the most potent I hibitory effect against all organisms. Inspired by the bioactivity of the methanol extract, we employed it as a plant-based material for the green synthesis of copper nanoparticles (Cu-NPs). The synthesized Cu-NPs were characterized using Fourier infrared spectroscopy (FT-IR), UV–visible spectroscopic analysis, and scanning electron microscopy (SEM). The observed color changes confirmed the successful formation of Cu-NPs, while the FTIR analysis matched previously reported peaks, further verifying the synthesis. The SEM micrographs indicated the irregular shapes of the surface particles. From the result obtained by energy dispersive X-ray spectroscopic analysis, Cu has the highest relative abundance of 67.41 wt%. Confirming the purity of the Cu-NPs colloid. These findings contribute to the growing field of eco-friendly nanotechnology and emphasize the significance of plant-mediated approaches in nanomaterial synthesis and biomedical applications.

Published
2024
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21. Synthesis, characterization, in silico and in vitro studies of novel glycoconjugates as potential antibacterial, antifungal, and antileishmanial agents

Author

Khan Sher Wali, Nayab Saira, Umar Muhammad Naveed, Khan Momin, Iqbal Anila, Ahmad Nasir, Rashid Haroon ur, Shah Muhammad Ishaq Ali, Gulfam Naila, Zahoor Muhammad, Ullah Riaz, and Ali Essam A.

Subjects
glycoconjugates, glycopyranosyl-α-trichloroacetimidates, glycosylation, antimicrobial, antileishmanial, molecular docking, Chemistry, QD1-999
Abstract

In the present work, several new glycoconjugates (8a–e) were generated from glycopyranosyl-α-trichloroacetimidates (sugar-OTCA) as glycosyl donors and dimethyl-l-tartrate as an aglycone acceptor in good to excellent yields. In the synthetic protocol, various monosaccharides were transformed into pentaacetylated derivatives and then into glycopyranosyl-α-trichloroacetimidates. Afterward, the sugar-OTCA was reacted with dimethyl-l-tartrate using Schmidt’s trichloroacetimidate protocol to give the desired products. The newly synthesized glycoconjugates were characterized by FT-IR, 1H, and 13C-NMR spectroscopic analytical methods. All the target compounds (8a–e) were tested in vitro against various strains of bacteria and fungi at different concentrations. The results revealed that the target compounds had encouraging antibacterial and antifungal potential. The antileishmanial activity of the target compounds against Leishmania tropica promastigotes was also investigated. The in vitro results were further supported by the in silico docking study that indicated minimum values of the docking scores and binding energies for the resulting complexes obtained by the favorable interactions between the target compounds (8a–e) and the selected strains of bacteria and fungi. The docking results proposed promising antibacterial and antifungal activities of the target compounds (8a–e) against the selected bacterial and fungal species.

Published
2024
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22. 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, Maqsood-Shah, Amaal, Ali, Amal, Ouachhou, Amal, Ahmad, Aman, Kezze, Amana, Dawson, Amanda Caroline, Ali, Amani, Mohsen, Amani, Brar, Amanpreet, Dembele, Amara, Tansawet, Amarit, Obbeng, Ambe, Chiappini, Ambra, Davis, Amelia, Awidan, Amera, Tibude, Ameya, Shah, Ami, Hilder, Amie, Huremovic, Amila, Alamin, Amin, Egdeer, Amin, Gharib, Amin, Choudhary, Amin Mazhar, Amin, Amina, Ibrahim Hassan, Amina, Rashid, Amina, Patel, Aminah, Sebai, Amine, Asla, Amir, Ghanbari, Amir, Shweiki, Amir, Tursunovic, Amir, Aboshosha, Amira Abdelbadea Abdelhamed, Elbalal, Amira, Abdelhalim, Amira Ramadan, Gupta, Amit, Sinha, Amit, Al-Fandi, Amjad, Awwad, Amjad, Belaid, Amjad, Khatib, Amjad, Al-Zubeidy, Ammar, Niazi, Ammar, Zamareh, Ammar, Salam, Ammara, Ayodele, Amoda, Al Hammoud, Amr, Khouli, Amro, Crowe, Amy, Surkitt, Amy Louise, Alshiteewi, Amyirah, Alvarez Cuiñas, Ana, Cabral, Ana, Dupont, Ana, Faustino, Ana, Carreira-Marques, Ana Lúcia, Preto Barreira, Ana Lúcia, Minaya Bravo, Ana Maria, Pinheiro Pereira, 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De Leo, Eugenio, Borges, Eva, Gáspár, Éva, Ruiz-Daum, Eva, Apostolopoulos, Evaggelos, Samara, Evangelia, Barkolias, Evangelos, Fradelos, Evangelos, Hopping, Eve, Romo Ascencio, Evelia Veronica, Sosa Ferreira, Ever David, Shestakov, Evgenii, Tyurina, Evgenya, Hristova, Evguenia, Efthymiou, Evripidis, Tokidis, Evripidis, Harrison, Ewen, Dontoh, Ewurama Akroma, Mansour, Eyad, Yeshialem, Eyosiyas, Dabbagh, Ezeddin, Amer, Ezzeldin, Manasci, Fabiana, Gomes, Fabio, Medas, Fabio, d'Acapito, Fabrizio, Vassallo, Fabrizio, Haddad, Fadi, Elhabishi, Fadwa, Akhtar, Fahad, Tauheed, Fahad, Al Abbood, Fahd, Gareb, Fahed, Ghazali, Fairuz, Alnazawi, Faisal, Ondago, Faith, Rasoaherinomenjanahary, Fanjandrainy, Wiese, Fanny, González Ponce, Fanny Yesenia, Georgiades, Fanourios, Ali, Farah, Galley, Fareeda, Huda, Farhanul, Amir, Farhat Naaz, Ashraf, Fariha, Alfarsi, Faris, Ayasra, Faris, Ali, Farman, Mahmoud, Faten, Aliskander, Fater, Tahir Lwdie, Fathea, Buyuker, Fatih, Aguilar Del Castillo, Fátima, Mohammed Daoud, Fatima Ahmed, Alowjaly, Fatima, Oni, Fatima, Rauf, Fatima, Elkhafeefi, Fatimah, Hourri, Fatine, Monib, Fatma A., Alshreef, Fatma, Benghalbon, Fatma, Ntirenganya, Faustin, Ashraf, Fauziyah, Chahrour, Fayez, Ahmad, Fazal, Parray, Fazlul Qadir, Philips, Febi, Campus, Federica, Di Marco, Federica, Ferraina, Federica, Frongia, Federica, Maffeis, Federica, Natali, Federica, Pederiva, Federica, Scolari, Federica, Tofani, Federica, Marin, Federico Alberto Niccolò, Biolchini, Federico, Cappellacci, Federico, Corronca, Federico, Mazzola, Federico, Suldrup, Federico, Nyarko, Felicia, Casas J, Felipe, Zapata, Felipe, Aigner, Felix, Alakaloko, Felix, Amoako, Felix, Camacho, Felix, Hammett, Felix, Kuubetersob B. N, Felix, Alahmad, Feras, Alnimri, Feras, Haddad, Feras, Gool, Ferhana, Castro, Fernanda, Diaz, Fernanda, Lucero, Fernanda, Vovola, Fernanda, Mahnic, Fernando, Mercado Sanchez, Fernando, Prieto La Noire, Fernando, Soggiu, Fiammetta, Tsige, Fikreab, Brzeszczyński, Filip, Rudisch, Filip, Valente Costa Pinto, Filipa, Ramalho De Almeida, Filipe, Banchini, Filippo, Palomino Escalante, Fiorella, Fadzlullah, Fitri, Terefe, Fitsum, Sulo, Fjorenta, Ciccarone, Flavia, Tirelli, Flavio, Krämer, Florian, Grama, Florin, Spanos, Foivos, Solimene, Folco, Akinwande, Foluso, Osman, Forzia, Stefou, Foteini, Kyramargios, Fotios, Stavratis, Fotios, Alassani, Fousseni, Ascari, Francesca, Cammelli, Francesca, D'Agostino, Francesca, Tropeano, Francesca Paola, Peters, Francesca, Ré, Francesca, Brucchi, Francesco, Casti, Francesco, Coratti, Francesco, Ferrara, Francesco, Floris, Francesco, Izzo, Francesco, Maffei, Francesco, Palmieri, Francesco, Pata, Francesco, Porcelli, Francesco, Selvaggi, Francesco, Velluti, Francesco, Mulita, Francesk, Bello, Francis, Caiquo, Francis, Dossou, Francis, Eshun, Francis Junior, Opoku Twene, Francis, Tierenye, Francis, Quayson, Francis William, Romo Rosales, Francisco David, Ibañez Ortiz, Francisco, León Frutos, Francisco Javier, Redondo Calvo, Francisco Javier, Silva Rivera, Francisco Javier, Barbosa Camacho, Francisco José, Bujalance Cabrera, Francisco Manuel, Ruescas, Francisco, Irakiza, Franck Fanon, Corvatta, Franco, Pascual, Franco Raúl, Roviello, Franco, Roodt, Francois, Gyamfi, Frank Enoch, Olaniru, Frank, Owusu, Frank, Bader, Franz G., Anzinger, Franz-Xaver, Agbodo, Fred David Anku, Ris, Frederic, Agbemafoh, Frederick Mawuli, Afonso, Frederico, Nazareth, Frederico, Berrevoet, Frederik, Hounde, Fréjus, Demiral, Furkan, Hassooni, Furqan Ridha Hassooni, Kafa, Gabi, Cárdenas Rivera, Gabriel, Ntwari, Gabriel, Szydlo Shein, Gabriel, Ambriz González, Gabriela, Nita, Gabriela Elisa, Bellio, Gabriele, Moitzi, Gabriele, Urdang, Gabriella, Marom, Gad, Gallo, Gaetano, Luglio, Gaetano, Poillucci, Gaetano, Singh, Gagandeep, Saletta, Gaia, Abouelnagah, Galal, Yarovenko, Galina, Kazobinka, Gallina, Ahmed, Gamal Mutwakil Gamal, Rahman, Ganiyu Adebisi, Smith, Garett, Pillai, Gargi, Saxena, Garima, Gbessi, Gaspard, Nkunguzi, Gaston, Jalal, Gaurav, Chillarge, Gauri, Singh, Gautam, Mevognon, Gedeon, Getachew, Gedion, George, Gejoe, De La Peña González, Gema, Martínez Izquierdo, Gema, Grande, Gennaro, Birikorang, Geoffrey, Weber, Georg F., Singer, Georg, Ansong, George, Bashour, George, Brown, George Darko, Hneino, George, Kavalieratos, George, Kenchadze, George, Nagy, George, Pappas Gogos, George, Skroubis, George, Waiyaki, George, Cox, Georgia, Zeringa, Georgia, De Wee, Georgin, Hart, Georgina, Bekakos, Georgios, Fragulidis, Georgios, Kapogiannatos, Georgios, Karakaidos, Georgios, Kokkinos, Georgios, Kostoulas, Georgios, Koukoulis, Georgios, Peros, Georgios, Rados, Georgios, Tsoulfas, Georgios, Verras, Georgios-Ioannis, Berger, Geraint, Adoro, Gerard Ayuka, Chamoso Mialdea, Gerardo, Palmieri, Gerardo, Procaccini, Gerardo, Steenkamp, Gerhard, Viscido, Germán Rodrigo, Dajti, Gerti, Alemayehu, Getachew, Seyfu, Gezachew, Birqeeq, Ghada, Alsheikh, Ghadeer, Alrayyes, Ghaith, El Hunjul, Ghalib Nashaat, Zaza, Ghayath, Matroud, Ghazlah, Alhadwah, Ghena, Maltinti, Gherardo, Awais, Ghina, Shamsi, Ghina, Calini, Giacomo, Carganico, Giacomo, Zanus, Giacomo, Canu, Gian Luigi, Mendiola, Gian, Ibero Casadiego, Giana Pamela, Cocorullo, Gianfranco, Baronio, Gianluca, Pellino, Gianluca, Zanni, Gianluca, Poto, Gianmario Edoardo, Gravante, Gianpiero, Aduroja, Gideon, Almogy, Gidon, Bond-Smith, Giles, Natchagande, Gilles, Bechara, Gio, Brachini, Gioia, Riccioli, Giordana, Ercolani, Giorgio, Farris, Giorgio, Giraudo, Giorgio, Mammolo, Giovanna, Pavone, Giovanna, Sgarzini, Giovanna, Aprea, Giovanni, Fonsi, Giovanni Battista, Boroni, Giovanni, De Angeli, Giovanni, De Palma, Giovanni Domenico, Emiliani, Giovanni, Grava, Giovanni, Guercio, Giovanni, De Carlo, Giulia, Del Corpo, Giulia, Duranti, Giulia, Galatioto, Giulia, Grassi, Giulia, Graziano, Giulia, Marini, Giulia Maria Francesca, Munzi, Giulia, Tarantino, Giulia, Borda-Luque, Giuliano, Pellicano', Giuseppe Antonino, Canonico, Giuseppe, Carollo, Giuseppe, Ietto, Giuseppe, Palomba, Giuseppe, Pascarella, Giuseppe, Salamone, Giuseppe, Sica, Giuseppe, Sorrentino, Giuseppe, Orlando, Giuseppina, Pignata, Giusto, Pisarevi, Givi, Akcakoca, Gizem, Owusu, Godfred, Yohanna Abrak, Godwin, Kurtoglu, Gokalp Kagan, Kurtoglugk, Gokalp Kagan, Alıcı, Gökhan, Kurtoglu, Goktug Mert, Delgado Hernandez, Gonzalo, Augustin, Goran, Bhat, Gowhar Aziz, Sundaram Venkatesan, Gowtham, Chang, Grace, Eke, Grace, Lee, Grace, Massarra, Grace, Travaglini, Grazia, Scialandrone, Grazisa, Stavrou, Gregor A., Di Franco, Gregorio, Charalambous, Gregory, Christodoulidis, Gregory, Kouraklis, Gregory, Goodwin, Gregory Richard, Devidze, Grigol, Fialho, Guilherme, Santos, Guilherme, Cabezudo, Guillermo, García-Santos, Guillermo, Pou, Guillermo, Romero Reyna, Guillermo, Yanowsky-Reyes, Guillermo, Ozyuksel, Gul, Karadeniz Cakmak, Guldeniz, Kucuk, Gultekin Ozan, Bulbuloglu, Guney Cem, Sarp, Guray, Kaur, Gurleen, Nibogora, Guy Darcy, Hamdan, Gymar, Ogundipe, Habeeb, Yunes, Habib, Ayesh, Hadeel, Al Atassi, Hadi, Jalilehvand, Hadis, Masalma, Hafez, Jafarkhan, Hafis, Shahid, Hafiz Huzaifa, Younus, Hafsa, Al-Derume, Hail, Shames, Haitam, Mimouni, Haithem Ahmed, Aldare, Hajar, Odah Bashi, Hajar Omar, Abusnina, Hajer, Altounsi, Hajir, Qayum, Hajra, Baysal, Hakan, Bolukbasi, Hakan, Yigitbas, Hakan, Alkhatib, Hala, Afzal, Haleema, Mftah, Halima, Oyinlola, Halimah, Tümer, Haluk, Dolo, Hamadoun, Braham, Hamdi, Ozsahin, Hamdi, Abu-Arish, Hamdoon, Al-Aamri, Hamed, Fadlalmola, Hammad Ali, Abu Obead, Hamza, Al-Fahel, Hamza, Al-Zoubi, Hamza, Asaad, Hamza, Ejaz, Hamza, Jaber, Hamza, Bhatti, Hamza Waqar, Mohammadi Sardoo, Hamzeh, Farhat, Hana, Idheiraj, Hanadi, Zwaraa, Hanady, Al Sohabi, Hanan, Basharat, 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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, Nikolaos, Memos, Nikolaos, Michalopoulos, Nikolaos, Mathioudakis, Nikolaos Nestor, Roukounakis, Nikolaos, Stamos, Nikolaos, Tasis, Nikolaos, Tsakiridis, Nikolaos, Vlachakos, Nikolaos, Zampitis, Nikolaos, Kouzakos, Nikolas, Börner, Nikolaus, Dimitriou, Nikoletta, Dafnios, Nikos, Banerjee, Niladri, Klammer, Nils, Maharjan, Nima, Rabai, Nimah, Oscar, Nimpaye, Harrison, Nina, Kheyrbek, Nina, Kansakar, Nirajan, Bhat, Nisar, Krishnappa, Nischal, Pahuja, Nisha, Paul Ambrose, Nitin, Renovat, Niyongabo, Musawa, Nizar, Nwanne, Njideka, Steve, Nkurunziza, Chidumije, Nnaemeka, Nwafulume, Nnaemeka, Celestine, Nnamani, Duru, Nnamdi, López Bernal, Noelia Esthela, Laquatra, Noemi, Pasqua, Noemi, Awwad, Noor Al-Deen, Ali, Nora, Hielscher, Nora, Trabulsi, Nora, Hüser, Norbert, Muñoz Montes, Norberto, Eshak, Norma-Sol, Rajab, Nosaiba, Lahnaoui, Nouhaila, Ouachou, Nouhaila, Ali, Nour, Dadoush, Nour, Fazili, Noureen, Theophile, Ntahompagaze, Ntanzi, Ntuthuko, Bibila, Nubia Samuel, Alwaer, Nuhay, Naabo, Nuhu, Jiagge, Nuna, Freitas Oliveira, Nuno Miguel, Pratas, Nuno, Morricone, Nunzia, Franco, Nunzio Francesco, Binti Yusri, Nur Aima, Ramli, Nur Natasya, Abd Ghani, Nur Suriyana, Umar, Nura, Aly, Nuran Khaled, Lakhanov, Nurgali, Al-Hroub, Nurhan, Kiziltoprak, Nurhilal, Chavarrias, Nuria, Maulenov, Nurlan, Akinbami, Nurudeen, Abdulraheem, Nurudeen Toyin, Karunaratne, Nuwanthika, Jeannette, Nyiransabiyera, Altobaishat, Obieda, Egwuonwu, Ochonma Amobi, Enciu, Octavian, Cohen-Arazi, Oded, Pheiffer, Odette, Okoye, Odili Aloysius, Omoike, Ofure, čančar, Ognjen, Ekwunife, Okechukwu Hyginus, Emuze, Okundayo, Eljizoly, Ola Abdallah, Al Hamdani, Ola, Emadeldeen, Ola, Morgan, Ola, Olajumoke, Oladapo, Popoola, Olakunle, Ajiboye, Olalekan, Olasehinde, Olalekan, Jolayemi, Olamide, Babatunde, Olanrewaju, Balogun, Olanrewaju, Olajide, Olawumi, Lisin, Oleg, Bellou, Olga, Jurić, Oliver, Ladlow, Oliver, Whitehurst, Oliver, Camilleri, Olivia, Montaño Angeles, Olivia, Pryer, Olivia, Ray, Olivia, Gabom, Olivier, Ndizeye, Olivier, Ojewuyi, Olufemi, Oluyemi, Olukayode, Elebute, Olumide, Ogunsua, Oluseyi, Fasiku, Olushola Kayode, Fasoro, Olusola, Fatudimu, Oluwafemi, Osunlusi, Oluwafemi, Owolanke, Oluwagbenga, Oso, Oluwarotimi, Alaba, Oluwaseun, Ojo, Oluwaseun, Oluseye, Oluwaseun, Oyinloye, Oluwaseun, Al Alyani, Omaima, Okrah, Omane, Agha, Omar, Al-Fahel, Omar, Almomani, Omar, Alruwaili, Omar, Ibarra, Omar, Ibrahim, Omar, Khalil, Omar, Kouli, Omar, Lima Azurdia, Omar, Mansour, Omar, Mohamed Mokbel, Omar, Omar, Omar, Bedak, Omer, Ozkan, Omer Faruk, Yalkın, Omer, Mohamed, Omnia, Ayandipo, Omobolaji, Faboya, Omolara, Williams, Omolara Modupe, Irowa, Omorodion, Attawodi, Onuche, Salako, Opeyemi, Ioannidis, Orestis, Agcaoglu, Orhan, Martin Sole, Oriol, Webster, Orla, Abouhiekal, Osama, Al Shaqran, Osama, Bahsas-Zaky, Osama, Nubi, Osama Gamal, Hany, Osama, Matar, Osama, Mahafdah, Osama R., Sarhan, Osama, Osagie, Osasumwen, Soublett Rivas, Óscar Alexander, Gülcicek, Osman Bilgin, Cuenca Torres, Osmar Manuel, Carpineto Samorani, Osvaldo, Arsalan, Othman, Coyoy-Gaitán, Otto, Nouhail, Oumaima, Boujidi, Oumama, Dicko, Ousmane A A, Ahmad, Owais, Christianah, Oyegbola, Küpçüoğlu, Özge, Zanbak Mutlu, Özgecan Pırıl, Chadha, P, Prabhu, P Santosh, Carmignani, Pablo, Arteaga Asensio, Pablo Cesar, Del Val Ruiz, Pablo, Royo Dachary, Pablo, Sancho Pardo, Pablo, Vásquez, Pablo, Sukhvibul, Pakkapol, Assouto, Pamphile, Evangelou, Panagiota, Dorovinis, Panagiotis, Kapsampelis, Panagiotis, Kokoropoulos, Panagiotis, Kostoglou, Panagiotis, Manikis, Panagiotis, Sakarellos, Panagiotis, Lykoudis, Panagis, Kumar, Pankaj, Patel, Panna, Paraskeva, Panoraia, Vassiliu, Panteleimon, Antonakis, Pantelis, De Nardi, Paola, Marongiu, Paola, Kamenova, Paolina, Venturelli, Paolina, Belotti, Paolo, Ubiali, Paolo, Grivas, Paraskevas, Stamopoulos, Paraskevas, Chatzikomnitsa, Paraskevi, Trakosari, Paraskevi, Tekam Wadje, Parfait Stéphane, Manjunath, Parikshith, Gupta, Pariza, Dhamija, Parth, Haque, Parvez, Haque, Parvez David, Haque, Parwez Waseemul, Nze Obiang, Pascal Christian, Probst, Pascal, Chiacchio, Pasquale, Cianci, Pasquale, Favoriti, Pasqualino, Koggoh, Patience, Bernardo, Patrícia, Omwansa, Patricia, Serrano Méndez, Patricia, Owens, Patrick, Tang, Patrick, Walker, Patrick, Chimezie Andrew, Paul, Trinity, Paul, Wilson, Paul, George, Paul Yohan, Artigot, Paula, Devlin, Paula, Vladova, Paulina, Cabrera Rivera, Paulo Andrés, Arunachalam, Pavai, Glushkov, Pavel, Levíček, Pavel, Lal, Pawanindra, Panahi, Pedram, David Santos, Pedro, Laranjo, Pedro, Palazon Bellver, Pedro, Rego Ponte, Pedro, Salas Núñez, Pedro, Sornoza, Pedro, Chloropoulou, Pelagia, Correia, Penélope, Limani, Perparim, Agbonrofo, Peter, Boateng, Peter Agyekum, Elemile, Peter, Francúz, Peter, Riedl, Peter, Tschann, Peter, Yuide, Peter, Hudáč, Petr, Ostruszka, Petr, Zimmermann, Petra, Nambala, Petrus, Shimbulu, Petrus, Thomas, Phebey A, Kumassah, Philemon, Alexander, Philip, Mensah, Philip, Taah-Amoako, Philip, Horvath, Philipp, Garcia-Dubus, Philippe, Holt, Phillip, Lapolla, Pierfrancesco, Cicerchia, Pierfranco Maria, Palumbo, Piergaspare, Anoldo, Pietro, Calò, Pietro Giorgio, Grondona, Pietro, Masseria, Pietro, Riva, Pietro, Milewski, Piotr Jan, Kowalewski, Piotr, Kasetsermwiriya, Pohpdham, Patel, Poojan, Leungon, Poramet, Kaur, Prabhjot, Arya, Prafull Kumar, Shivashankar, Pranav, Kothari, Prashant, Dummala, Prashanth, Shukla, Prateek, John, Pravin, Adebayo, Precious, Andrejevic, Predrag, Thambi, Prem, Anandan, Premkumar, Idjerhe, Prince, Boateng, Prince Kwame, Ntem, Prince, Waghchoure, Prince, Yeboah Owusu, Prince, Moodley, Priyanka, Suresh, Priyanka, Kanavidis, Prodromos, Odigie, Vincent, Christodoulou, Prokopis, Nashidengo, Pueya Rashid, Patel, Puja, Dolatzay, Qayom Khan, Mashlah, Qusai, Sabbah, Qutaiba, Sethi, R, Robitsek, R. Jonathan, Jubran, Ra'Ed, Raheem Attallah Al-obaidy, Raad, Michael, Rabha, Abela, Rachel, Colbran, Rachel, Geow, Rachel, Titcombe, Rachel, Soglonou, Rachelle, Ait Ben Addi, Rachid, Jayakrishnan, Radhakrishnan, Acharya, Radhika, Salim, Radhwan, Guzmán Lambert, Radisnay, Donchev, Radoslav, Drasovean, Radu, Andreou, Rafael, Perez-Soto, Rafael Humberto, Santana Ortiz, Rafael, Villalobos Mori, Rafael, Sokratous, Rafailia, Smolinski Kurek, Rafal Ludwik, Solecki, Rafal, Basile, Raffaele, Abd Elkareem, Raghad, Yousef Yassin, Raghad, Faisal, Raghdah, Abd Alkareem, Rahaf, Hegy, Rahma, Jaba'Teh, Rahmah, Sharma, Rahul Deo, Gupta, Rahul, Saxena, Rahul, Sinha, Rahul, Varshney, Rahul, Ripoll I Palmés, Raimon, Lunevicius, Raimundas, Raghunath, Rajat, Redkar, Rajeev, Sharma, Rajeev, Philip Sridhar, Rajeevan, Krishna Raj, Rajesh, Nathani, Rajesh, Kottayasamy Seenivasagam, Rajkumar, Ahmed, Rakesh, Handa, Rakesh, Vakil, Rakesh, Armah, Ralph, Attaf, Ram, Elazary, Ram, Alkhatib, Rama, Alzu'Bi, Rama, Raddad, Rama, Kaur, Ramanjot, Kaur, Ramanpreet, Nataraja, Ramesh, Hussam Yacoub Hattar, Ramez, Ben Hmida, Rami, Chaudhary, Ramkaran, Ramirez Calas, Ramon Andres, Soliva Domínguez, Ramón, Ghaleb, Ramzi, Batir, Rana, Haddad, Rana, Sugair, Rana, Suleiman, Rand, Perera, Ranga, Altayargh, Rania, Joumaa, Ranim, Ellawala, Ranjith, Elaifia, Rany, Eloka, Raphael, Hernandez Rodriguez, Raquel Angelica, Diaz, Raquel, Lalanda, Raquel, Rodríguez-Uria, Raquel, Olatunji, Rasheed, Wani, Rauf, Díaz Pedrero, Raúl, Ubiñas, Raul, Lertnamvongwan, Raunika, Hiary, Rawan, Almahadin, Rawan Khalid Za'al, Radwan, Rawan, Issa, Rawand, Dar, Rayees Ahmad, Nyirenda, Raymond, Eghonghon, Raymond Atah, Oppong, Raymond, Govindaraju, Rayshini, Kalouk, Razan, Abad, Rebeca, Akankoatuesi Apatewen, Rebecca, Bradley, Rebecca, Enejo, Rebecca Eboshogwe, Hauwa Sani, Rebecca, Jurdon, Rebecca, Sönmez, Recep Erçin, Belouz, Reda, Abhinaya, Reddy, Abu Salah, Reem, Alatawi, Reem, Alqahtani, Reem, Sayad, Reem, Adel Diab, Rehab, Függer, Reinhold, Madi, Reman, Pajtak, Renata, Barradas, Renato, Díaz-Ruiz, Renato, Patrone, Renato, Palacios Huatuco, René M., Casma Bustamante, Renzo, Ranadive, Reuben Rajappa, Askari, Reza, Sulce, Rezart, Liang, Rhea, Tummon, Rhea, Roberts, Rhianna, Mcclen, Rhys, Duvenage, Riaan, Kattini, Ribal, Alvarado Hurtado, Ricardo, Tenfen Carneiro, Ricardo Augusto, Castro Lara, Ricardo Jesús, Silva Borges, Ricardo, Souto, Ricardo, Vaz Pereira, Ricardo, Barone, Riccardo, Fratarcangeli, Riccardo, Guercio, Riccardo, Magarini, Riccardo, Malatesti, Riccardo, Tripathi, Richa, Crawford, Richard, Kpangkpari, Richard, Marlin, Richard, McGee, Richard, Nesco, Richard, Spence, Richard, Akpaka, Richfield, Alinde, Rigobert, Khalid, Rija, Sato, Rikiya, Kitamura, Riley, Baldan, Rino, Agyei Boakye, Rita, Branquinho, Rita, Hleyhel, Rita, Miranda Pera, Rita, Pinheiro Duque, Rita, Ribeiro Dias, Rita, Bhatia, Riya, Rabah, Rnad, Damseh, Ro'Ya, Alzughayyar, Roa, Daradkeh, Roa'A, Bassam, Roaa, Refaie, Roaa, Bethune, Rob, Elshennawy, Roba, Cachia, Robert, Franz, Robert, Grützmann, Robert, Kibuuka, Robert, Laskowski, Robert, Mazurkiewicz, Robert, Munyaneza, Robert, Parker, Robert, Sagoe, Robert, Sucher, Robert, Granata, Roberta, Ruccella, Roberta, Tutino, Roberta, Badra, Roberto, Mares País, Roberto, Sampietro, Roberto, Scola, Roberto, Mackay, Robyn, Tumolo, Rocco, Figueroa, Rodrigo, Doamba, Rodrigue, Habib, Rohan, Gujjuri, Rohan R, Anjum T Siddeek, Rohik, Mittal, Rohin, Kumar, Rohit, Goudou, Roland, Rüdrich, Roland, Senin, Roman, Moukarzel, Romika, Ferlini, Romina Lorena, Ribeiro, Rómulo, Schmidt-Branden, Romy, Zerna Encalada, Ronald, Ferreira Acosta, Rosa, Lopatriello, Rosanna, Perez, Rosario, Hall, Rosie, Alloni, Rossana, Arena, Rossella, Gioco, Rossella, Polo, Roxy, Shen, Ru, Doherty, Ruairi, Rivas, Ruben, Oppong-Amoah, Ruby, Ooi, Rucira, Radojković, Rudolf, Herrera, Rudy, Bernardino, Rui, Ediru, Rukevwe, Al Shehhi, Ruqaiya, Masri, Ruqaya, Hodgson, Russell, Azimov, Rustam, Martínez Díaz, Rut, Santos Pereira, Rute, Naidoo, Ruvashni, Noor, Ruzaimie, Campbell, Ryan, Khalil, Ryta, Chigblo, S. Pascal, Abuzahra, Saad, Halabi, Saad, Maqbool, Saad, Alsmadi, Saba, Chaudhary, Sabah, Chowdhury, Sabbir Ahmed, Jayatilleke, Sachitha, Hayat, Saddaqat, Megdiche, Sadok, Abed, Saed, Abdeewi, Saedah, Toprak, Safa, Salim, Safauldeen, Yussif, Safia, P, Sagar, Trejo Ramos, Sagrario Leticia, Shittu, Saheed, Mahdi, Saher, Alijla, said, Al-Doghme, Saja, Bataineh, Saja, Mathew, Sajjan, Alshagrawi, Salah, Ibrahim Tour Harakan, Salah, Ibrahim, Salaheldin, Al Momani, Salam, Workineh, Saleamlak Tigabie, Said, Saleeha, Turkmani, Saleem, Ba-Shammakh, Saleh Ali Mohammed, Alshab, Saleh, Hammad, Saleh, Salama, Salem, Alneihuom, Salih, Karahan, Salih Nafiz, Dawo, Sallu, Ng, Sally, Nofal, Sally, Ahmed, Salma, Amahmid, Salma, Elnoamany, Salma, Fakhouri, Salma, Selim, Salma, Abrayik, Salmi, Di Saverio, Salomone, Kassad, Saloua, Carrabetta, Salvatore, Costa, Salvatore, Gargiulo, Salvatore, Schirone, Salvatore, Sorrenti, Salvatore, Beavis, Sam, Lawday, Sam, Alananzeh, Samah, Arafa, Samah, Bani Amer, Samah, Mamduh, Samah, Omar, Samah, Altaf, Saman, Dos Santos Rocha Ferreira, Samantha, Quoy, Samantha, Emile, Sameh, Abu Salem, Samer, Al Athath, Samer, Yigman, Samet, Eldirdiri, Sami, Imam, Sami, Jomaa, Sami, Errami, Samia, Kessab, Samia, Muhammad, Saminu, Delibegovic, Samir, Kanaan, Samir, Aliozor, Sampson, Olori, Samson, Sani, Samuel Ali, Anim, Samuel, Bennett, Samuel, Debrah, Samuel, Ghattas, Samuel, Brenu, Samuel Gyasi, Robinson, Samuel James Alexander, Arthur, Samuel Joseph, Mcclintock, Samuel, Mensah, Samuel, Ogunlade, Samuel, Tingle, Samuel, Jabeen, Sana, Borrego Canovaca, Sandra, De La Cruz Ahufinger, Sandra, Tsoti, Sandra Maria, Paterna -Lopez, Sandra, Sanz, Sandra, Tsatsu, Sandra, Hügli, Sandro, Yunusa, Sani Abdullahi, Aji, Sani Ali, Katragadda, Sanjay, Edem, Sanketh, Irrinki, Santhosh, Shivashankar Chikkanayakanahalli, Santhosh, Bertone, Santiago, Karmarkar, Santosh, Abbas, Sara, Alashhab, Sara, Alsaeiti, Sara, Andrade, Sara, Egreara, Sara, Elfallah, Sara, Galati, Sara, García López, Sara, Giovampietro, Sara, Ismail, Sara, Kamari, Sara, Lauricella, Sara, Marzorati, Sara, Mohammed, Sara, Moschella, Sara, Mostafa Yassin, Sara, Patrocínio, Sara, Massa, Sara Tiziana, Vertaldi, Sara, Abdelmohsen, Sarah, Al Sharie, Sarah, Barbosa Castelo Branco, Sarah, Bowman, Sarah, Condron, Sarah, Elfurdag, Sarah, Ellouzy, Sarah, Fennelly, Sarah, Mansour, Sarah, Molfino, Sarah, Qwyder, Sarah, Rennie, Sarah, Robinson, Sarah, Segnitome, Sarah, Staight, Sarah, Yassin, Sarah, Alsibai, Sareyah, Khan, Sarfaraz, Khurana, Sarita, Rafiq, Sarmad, Malhi, Sarvpreet Singh, Dognia, Satchmo, D A, Sathiafrey, Babu, Satia, Subbiah Nagaraj, Satish, Meena, Satya Prakash, Vasquez, Saul, Bradulskis, Saulius, Mikalauskas, Saulius, Laura, Saura García, Verhage, Savannah Skye, Simeonidis, Savvas, Sarwary, Sayed Haschmatullah, Naidu, Sayuri, Schimpke, Scott, Davis, Sean, Stevens, Sean, Sierra, Sebastian, Dos Santos, Sebastiano, Strachan, Sebastien, Bektas, Sebnem, Atupra, Sedinam Adjoa Asiedua, Kreid, Sedra, Bugren, Seeraj, Saudí-Moro, Sef, Ashini, Sehar, Aboseif, Seif, Abdul Rahman, Seif-Aldin, Karim, Seiver, Öztürk, Selen, Akuffo, Selma, Awad, Selmy, Srishankar, Selvaratnam, Tobome, Sèmèvo Romaric, Malek, Sepand, Quartarone, Serafino, Grimaldi, Serena, Guarriello, Serena, Kalenga, Serge, Katorkin, Sergei, Trujillo Ponce, Sergio Adrian, Villeda, Sergio Alejandro, Intini, Sergio Giuseppe, Vázquez-Sánchez, Sergio Jiram, Salido, Sergio, Valeri, Sergio, Yilmaz, Serhan, Meriç, Serhat, Bensalem, Serien, Sucu, Serkan, Yılmaz, Serkan, Uludağ, Server Sezgin, Torres Rodríguez, Servio Tulio, Ooi, Sett, Luciano, Severino, Houndji, Sèwou Francklin Albert, Agordjor, Seyram, Ward, Sezar, Samardali, Shaden, Altoume, Shadi, Mahfoud, Shafik, Razaq, Shahad, Khan, Shahbano, Husanov, Shahboz, Ahmed, Shaheer, Islam, Shahnoor, Waqar, Shahzad Hussain, Kumaran, Shairashree, Magrhi, Shamsa, Zhang, Shane, Kashyap, Shankarsai, Karandikar, Sharad, Sundaramurthy, Sharada, Chowdhury, Sharfuddin, Jayasekara, Sharitha, Laura, Sharon, Shanker, Shashwat, Ababneh, Shatha, Gilbert, Shaun, Kenworthy, Shaunna, Ng, Shawn Hong Ming, Mackenzie, Shawn, Salindera, Shehnarz, Khattak, Shehrbano, Loke, Sheih Nee, Manzoor, Sheikh Viqar, Alwardi, Sheikha, Allam, Shereen, Tawfik, Sherifa, Francis, Shikha, Cai, Shirley, Dindyal, Shiva, Pandya, Shivangi, Chopra, Shreya, Ingley, Shreya, Kulkarni, Shrirang, Kosna, Shuba, Nayak, Shubhalaxmi, Ahuja, Shubham, Hariharan, Shubhang, Karuppusamy Krishnasamy, Shyam, Khare, Siddhant, Handa, Siddhartha, Amin Omar Alsiddig, Siddig, Alqurashi, Siddiga, Al-Tahayneh, Sief-Addeen, Sibiya, Silindokuhle, Perretta, Silvana, Ibarra Camargo, Silvia Alejandra, Montisci, Silvia, Mungo, Silvia, Puddu, Silvia, Severi, Silvia, Agudelo Mendoza, Silvia Valentina, Makkai-Popa, Silviu Tiberiu, Boyes, Simon, Monkhouse, Simon, Stock, simon, Alberti, Simona, Meneghini, Simona, Giudici, Simone, Guadagni, Simone, Birolo, Simone Lorenzo, Novello, Simone, Oliveira, Simone, Gumede, Simphiwe, Dhole, Simran, Budhwani, Simran Saleem, Ramjit, Sinead, Yumurtacilar, Sinem, Mahendra, Sirigi Naga, Abeykoon, Sithira, Moh Pauzi, Siti Farhan, Rajendra, Sittampalam, Sundararajan, Siva, Gananadha, Sivakumar, Kamarajah, Sivesh K, Marawu, Siyasanga, Basu, Sk, Hassan, Sleman, Reddy, Snigdha Mettu, Anaya Sanchez, Sofia, Gaspar Reis, Sofia, Gomez, Sofía, Gamba, Sofia Lucia, Pimentel Morais, Sofia, Ashry, Soha, Abdullateef, Sohaila, Bandyopadhyay, Soham, Samadi, Soheil, Pathan, Sohilkhan R., Lakew, Solomon, Basu, Somprakas, Ohri, Sonali, Alonso Marcos, Sonia, Amoza Pais, Sonia, Fortuna Martins, Sónia, Gill, Sonia, Matthiess, Sonia, Sabbatini, Sonia, Soto Schütte, Sonia, Engel, Sophie, Eam, Sothseyhakmonique, Botaitis, Sotirios, Lawani, Souliath, Jamil, Soumaya, Kondpan, Sourav, Oum, Sovannarith, Govender, Sovishnee, Christodoulou, Spyridon, Davakis, Spyridon, Vernadakis, Spyridon, Gkogkos, Spyros, Gobishangar, Sreekanthan, Suresh, Sreelakshmi, Vembar, Sridhar, M, Srikanth, Abdelrasoul Elnour Ismail, Srraa, Zourntou, Stamatina-Emmanouela, Nwabuoku, Stanley Emeka, Ideh, Stanley, Charitonos, Stavria, Liapis, Stavros Chrysovalantis, Faber, Stefan, Piccioni, Stefania Angela, Romano, Stefania, Silvestre, Stefania, Jarmusch, Stefanie, Soelling, Stefanie, Cardelli, Stefano, Chaifouroosh Mamagany, Stefano, Corso, Stefano, Basso, Stefano Maria Massimiliano, Megna, Stefano, Bitsianis, Stefanos, Tsatsos, Stefanos, Morales, Steffanía, Gerdes, Stephan, Göller, Stephanie, Hanna, Stephanie, Tabiri, Stephen, Agana, Stephen, Theivendran, Stephen Arthur, Kache, Stephen, Knight, Stephen R, Smith, Stephen, Stonelake, Stephen, Wrenn, Stephen, Gopaul, Steven, Vederaki, Styliani, Kapiris, Stylianos, Kykalos, Stylianos, Hlaing, Su Su, Chia, Su Yin Denise, Abu Khousa, Suad, M. Udwan, Suad, Raul, Subrat, Chase, Suchita, Nair, Sudharrshan, Joseph, Sudhir, Singh, Sudhir Kumar, Singh, Sudhir, Timmalah, Suhaylah, Alsuwiyah, Suhir, Thalgaspitiya, Sujeewa Priyantha Bandara, Sellahewa, Sujeewa, Neogi, Sujoy, Burger, Sule, Polat, Süleyman, Alkadi, Sulman, Asiri, Sultan, Otho, Sumaira, Mewa Kinoo, Suman, Ebrahim, Sumayyah, Tontus, Sumeyya, Midya, Sumit, Thuraisamy Sarma, Sundaramoorthy Iyer, Payyanur Thotan, Sundeep, Kumar Venkatappa, Sunil, Techapongsatorn, Suphakarn, Kaur, Supreet, Jp, Supritha, Tan, Suqi, Djote, Surafel Mulatu, Surendran, Suraj, Singh, Surendra, Chilaka, Suresh, Lee, Susan, Henriques, Susana, Giridaran, Suseendirarajah, Achugatla, Sushma, Kumar, Suvam, Brincat, Svetlana, Deshpande, Swati, Batista, Sylvia, Akharaekpanya, Tachporn, Moges, Tadesse Girma, Türkmen, Taha Berkay, Alhaj Hasan, Taima, Alshawabkeh, Taima', Majed, Taima', Lawal, Taiwo Akeem, Ibiyeye, Taiye Taibat, Rashid, Tajamul, Košir Božič, Tajda, Mohammed, Tajudeen, Khewater, Talal, Abelman, Talia, Al Barhi, Tamadher, Mogne, Tamiris, Salazar-Lorenzana, Tania Abril, Akter, Tania, Gómez Sanz, Tania, Motiwala, Tanmay, Valizadeh Elizeh, Tanya, Almahdi, Tanzeel, Albushary, Tanzel Alrahman, Abdulrahman, Taofeeq, Finlay, Tara, Chouari, Tarak, Awad, Tarek, Sabra, Tarek, M. Abubasheer, Tareq, Alhusban, Tariq, Yılmaz, Tarık Emre, Aloqaili, Tasneem, Aldirawi, Tayef, Karahasanoğlu, Tayfun, Gülşen, Taygun, Jemal, Tebarek, Nadeem, Tehmina, Singh, Tejinder Paul, Alinger, Temsula, Longkumer, Temsutoshi, Lo, Terence, Gimenez Maurel, Teresa, Uprak, Tevfik Kıvılcım, Petropoulou, Thalia, Rawther, Thampi, Techapongsatorn, Thawin, Manickam, Thendral, Padioti, Theodora, Kozonis, Theodoros, Sidiropoulos, Theodoros, Tsirlis, Theodoros, Theodosopoulos, Theodosios, Hessou, Thierry Kinnongni, Uiyapat, Thitapon, Agyen, Thomas, Harris, Thomas, Hugh, Thomas J, Jorgensen, Thomas W., Theivendrampillai, Thrshegan, Pham, Thuy Vy, Branco, Tiago, Nagwamutse, Tijjani Nasiru, Tony V, Tina, Devabalan Koil, Titus, Pilia, Tiziana, Abdulmola, Tmador Mahmed Ali, Oyeyemi, Tobiloba, Kebede, Tolera, Ibarra-Hurtado, Tomás Ramón, Reichelt, Tomas, Gach, Tomasz, Stefura, Tomasz, Wojewoda, Tomasz, Soric, Tomislav, Risteski, Toni, Tridip, Tridip Dutta Baruah, Yotsov, Tsanko, Doma Bhutia, Tshering, Girma, Tsion, Kwan, Tsun Yu, Ivanov, Tsvetomir, Iahmo, TT, Ashkar, Tuleen, Mabogoane, Tumi, Olobatoke, Tunde, Sholadoye, Tunde T., Mishra, Tushar Subhadarshan, Parker, Tyla, Ezomike, Uchechukwu, Dilibe, Uchenna, Kumbhar, Uday, Una, Uduak-Abasi, Grossi, Ugo, Ezidiegwu, Ugochukwu, Edith, Ugwuoke, Daspal, Ujjwal, Kalu, Ukoha Agwu, Dietz, Ulrich, Ronellenfitsch, Ulrich, Wirth, Ulrich, Abdullah, Umar, Rivolta, Umberto, Jayarajah, Umesh, Kanyan Kassim, Umu-Hera, Govindan, Unnikrishnan, Fernandes, Urânia, Akram, Usman, Mohammed Bello, Usman, Omara, Usra, Naidoo, Uvarasen, Mahendravarman, Vaishnaivy, Negoita, Valentina Madalina, Mariottini, Valentina, Murzi, Valentina, Zucchini, Valentina, Agbakwuru, Valentine, Armenta Tapia, Valeria Estefania, Gentilino, Valerio, Borgogni, Vanessa, Ng, Vanessa, Wolfschluckner, Vanessa, Silvestri, Vania, Žufić, Vanja, Gunasaegaram, Varman, Kamalathevan, Vasan, Pillay, Vasanthan, Neykov, Vasil, Kalles, Vasileios, Mousafeiris, Vasileios, Papadopoulos, Vasileios, Tsaousis, Vasileios, Tselepidis, Vasileios, Vougas, Vasileios, Georgilaki, Vasiliki, Nikolaou, Vasiliki, Themelidi, Vasiliki, Manchev, Vassil, Ioannou, Veatriki, Jha, Vedant Shekhar, Dragisic, Vedran, Sutharshan, Vengadasalam, Alonso, Veronica, Brocco, Veronica, Ongil Rodríguez, Verónica, Schirinzi, Veronica, Budyakova, Veronika, Naunova, Vesna, Panduro-Correa, Vicky, Ruiz López, Víctor Andrés, Bill, Victor, Dassah, Victor, Gonzabay, Víctor Eduardo, Etwire, Victor, Modekwe, Victor, Serna-Alarcon, Victor, De Donato, Victor Ugo, Duque Mallén, Victoria, Liu, Victoria, Sharma, Vidushi, Kumar, Vijaya, Muralidharan, Vijayaragavan, Kakotkin, Viktor, Enemuo, Vincent, Kudoh, Vincent, Osoka, Vincent, Siepaal, Vincent, Granata, Vincenza, Dinuzzi, Vincenza Paola, Lizzi, Vincenzo, Ricchiuti, Vincenzo, Mosca, Vinicio, Kanna D, Vinoth, Nair, Vipin Venugopal, Ledda, Virginia, Michael, Vishal, Singh, Vishavdeep, Govindasamy, Vishendran, Kollengode, Viswanathan V, Giordano, Vittoria, Morinelli, Vittoria, Lin, Vivian, Cuk, Vladica, Cijan, Vladimir, Çalik, Volkan, Bakshi, Vrushank, Ten, Vyacheslav, Ratheesh, Vysakh, Alsado, Wael, Mayo, Wafik, Yang, Wah, Rehman, Wajeeh Ur, Abbas, Walaa, Al-Khyatt, Waleed, Mabood, Waleed, Santucci, Walter, Yew, Wan Ting, Tahir, Warda, De Silva, Warusha Dhammika Dulantha, Wijenayake, Wasantha, Almadhoun, Waseem J.N., Alhroub, Wasef, Ebrahim, Wesam, Jabłoński, Wiktor, Krawczyk, Wiktor, Bhatti, William, Lai, William Kwan Ho, Petrushnko, Wilson, Afedo, Wisdom, Kasetsermwiriya, Wisit, Serednicki, Wojciech, Wysocki, Wojciech, Zerefa, Wondwossen Amtataw, Vagena, Xanthoula, Tarrado, Xavier, Papazarkadas, Xenofon, Po, Xiang Yuen, Ouadi, Yacine, Myla, Yacob, Haido, Yacoub, Hasan, Yafea, Karataş, Yağmur, Carpio Colmenares, Yahaira, Galvañ Félix, Yaiza, Balogun, Yakub Lekan, Maktabi, Yaman, Nerabani, Yaman, Fulgence, Yamuremye, De Silva, Yannick, Asar, Yara, Samer Morsy, Yara, Ghaleb, Yasameen Saif Saeed Mohammed, Vashishth, Yash, M S, Yashas, Manickchund, Yashoda, Sakaray, Yashwant, Kara, Yasin, Tosun, Yasin, Zwain, Yasir, Farag, Yasmeen, Jedidi, Yasmine, Seada, Yasmine, Aldebasi, Yasser, Ashour, Yasser, Badr, Yassin, Sarpong, Yaw, Alawneh, Yazan, Aung, Yee Lay, Orabi, Yehia, Lam, Yick Ho, Şen, Yigit Kaan, Koyluoglu, Yilmaz Onat, Huang, Yining, Mintz, Yoav, Perez, Yocarli, Chamara, Yohan, Melkamu, Yohannes, Maestre González, Yolanda, Dean, Yomna, Metaferia, Yonas Yilma, Malki, Yosra, Mohamed, Younis, A. Omar, Yousef, Alhammoud, Yousef, Allaoua, Yousef, Tanas, Yousef, El Okazy, Youssef, Kerolous, Youssef, Mohamed, Youssef, Al-Junaidi, Youssuf, Lakdawala, Yousuf, Lu, Yuann, Asano, Yukio, Altinel, Yuksel, Aktimur, Yunus Emre, Fishman, Yuri, Kudryavcev, Yurii, Tandoğan, Yusuf Iskender, Razafimandimby, Yves Michaël, Adofo-Asamoah, Yvonne, Şenol, Zafer, Odeh, Zahra, Benamrouche, Zahra Rayane, Alkhaier, Zahraa, Al-Sheikh Ali, Zaid, Zaher, Zain Aldin, Alnajjar, Zaina, Al-Balushi, Zainab, Alkhuzaie, Zainab, Khraim, Zakaria, Toutounji, Zakaria, Djama, Zakarya, Farraj, Zamil, Shah, Zamir Ahmad, Khan, Zara, Khan, Zarnigar, Abo Alarous, Zayn Alabden, Asaad, Zaynab, Demetrashvili, Zaza, Lorenc, Zbigniew, Brekalo, Zdrinko, Hannouneh, Zein Alabdin, Robertson, Zelda, Bady, Zeyad, Durna, Zeynep, Wong, Zhen Yu, Fozo, Zien Alabdin, Klib, Zienab, Chin, Ziling, Tamou, Zime Farid, Johnson, Zina, Shabello, Ziyad, Orzeszko, Zofia, Aljalabi, Zohal, Al-Azher El-Hamel, Zohour, Karampotaki, Zoi Rafaila, Valera Sanchez, Zoraida, Matkovic, Zoran, Azhar, Zubair, Qureshi, Zubaria, Correa López, Zulema Margarita, Balciscueta, Zutoia, Musilová, Zuzana, Katusic, Zvonimir, Osama, Zyad, and Dauksa, Zygimantas

Published
2024
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26. Exposure to benzene, toluene, ethylbenzene, and xylene (BTEX) at Nigeria's petrol stations: a review of current status, challenges and future directions

Author

Emmanuel Ademola Anigilaje, Zaheer Ahmad Nasir, and Christopher Walton

Subjects
narrative review, BTEX exposure, cancer and non-cancer risks, petrol stations, Sustainable Development Goals, Nigeria, Public aspects of medicine, RA1-1270
Abstract

IntroductionIn Nigeria, because of increasing population, urbanization, industrialization, and auto-mobilization, petrol is the most everyday non-edible commodity, and it is the leading petroleum product traded at the proliferating Nigeria's petrol stations (NPSs). However, because of inadequate occupational health and safety (OHS) regulatory measures, working at NPSs exposes petrol station workers (PSWs) to a large amount of hazardous benzene, toluene, ethylbenzene, and xylene (BTEX) compounds.MethodsStudies on BTEX exposures among Nigerian PSWs are scarce. Thus, constraints in quantifying the health risks of BTEX limit stakeholders' ability to design practical risk assessment and risk control strategies. This paper reviews studies on the OHS of Nigerian PSWs at the NPSs.ResultsAlthough knowledge, attitude, and practices on OHS in NPSs vary from one Nigeria's study setting to another, generally, safety practices, awareness about hazards and personal protective equipment (PPE), and the use of PPE among PSWs fell below expectations. Additionally, air quality at NPSs was poor, with a high content of BTEX and levels of carbon monoxide, hydrogen sulfide, particulate matter, and formaldehyde higher than the World Health Organization guideline limits.DiscussionCurrently, regulatory bodies' effectiveness and accountability in safeguarding OHS at NPSs leave much to be desired. Understanding the OHS of NPSs would inform future initiatives, policies, and regulations that would promote the health and safety of workers at NPSs. However, further studies need to be conducted to describe the vulnerability of PSWs and other Nigerians who are occupationally exposed to BTEX pollution. More importantly, controlling air pollution from hazardous air pollutants like BTEX is an essential component of OHS and integral to attaining the Sustainable Development Goals (SDG) 3, 7, and 11.

Published
2024
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28. Two stages upgrading of bio-oil through esterification and hydrodeoxygenation reactions using Fe2O3-CoO supported catalyst.

Author

Pulungan, Ahmad Nasir, Goei, Ronn, Kembaren, Agus, Nurfajriani, Nurfajriani, Sihombing, Junifa Layla, Gea, Saharman, Wong, Hana Ria, Hasibuan, Muhammad Irvan, Rahayu, Rahayu, and Tok, Alfred Iing Yoong

Abstract

Bio-oil contains many oxygenated compounds, as well as high acid and water content, which can reduce the stability of its components and have poor overall physicochemical properties. In this study, the quality of bio-oil produced from the pyrolysis of oil palm fronds was enhanced through a hydrodeoxygenation (HDO) reaction that was preceded by esterification as a pre-treatment. The catalyst used in the HDO reaction is mixed metal oxide (Fe2O3-CoO) anchored within zeolite mordenite (Fe2O3-CoO/Mor). The catalysts were characterized using XRD, SEM-EDX, and BET methods. The presence of metal oxides on the surface of mordenite increases the activity of the catalyst in producing liquid products while reducing the formation of coke. Upgrading of bio-oil has improved the physicochemical properties of bio-oil compared to the one-stage upgrading process. The analysis of product showed that the C and H content increased from 11.5 to 23.5 wt% and from 9.76 to 11.2 wt%, respectively. On the other hand, the O content decreased from 78.7 to 65.2 wt% with a degree of deoxygenation of 59.8%. Moreover, higher heating value (HHV) of the bio-oil increased by 38% from 11.6 to 16.0 MJ/kg. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Regenerable chitosan-embedded magnetic iron oxide beads for nitrate removal from industrial wastewater

Author

Nasir, Muntaha, Javaid, Farhan, Masood, M. Talha, Arshad, Muhammad, Yasir, Muhammad, Sedlařík, Vladimír, Qadir, Muhammad Abdel, Qiblawey, Hazim, Zhang, Wenjuan, Deen, Kashif Mairaj, Asselin, Edouard, Ahmad, Nasir M., Nasir, Muntaha, Javaid, Farhan, Masood, M. Talha, Arshad, Muhammad, Yasir, Muhammad, Sedlařík, Vladimír, Qadir, Muhammad Abdel, Qiblawey, Hazim, Zhang, Wenjuan, Deen, Kashif Mairaj, Asselin, Edouard, and Ahmad, Nasir M.

Abstract

Industrial sites worldwide significantly contribute to water pollution. Nitrates are a common effluent pollutant from such sites. Effective means to remove nitrate ions (NO3-) from polluted waters are needed. Chitosan beads, which are a non-toxic, biocompatible, and biodegradable polymer, are used for this purpose in this research. Iron-oxide nanoparticles are synthesized via the co-precipitation route and embedded into chitosan by chemical co-precipitation to form ion exchange chitosan beads (IECBs) for NO3- removal. The performance of the IECBs in a batch system was studied against NO3- adsorption from industrial water. Morphological, structural, and chemical characterization was performed by SEM, EDX mapping, BET, XRD, and FTIR, while the extent of NO3- adsorption was quantified using UV-vis spectroscopy. Different factors influencing the adsorption of NO3- on the IECBs were investigated, including the adsorbent dosage, pH of the solution, initial concentration, and interaction time. It is demonstrated that pseudo-second-order isothermal and kinetic models were best fits to the experimental data. It was found that the IECBs had a maximum adsorption capacity of 47.07 mg g-1 and could load up to similar to 93% of the NO3- from the batch system. The regeneration efficiency for the IECBs over 5 cycles remained high in the range of 93% to 79%, indicating their potential for industrial water treatment use. Synthesis of regenerable chitosan-embedded magnetic iron oxide beads.

Published
2024

34. Performance of a Ship-Based Cupronickel Alloy in Exposure Conditions of Arabian Seawater—A Comparative Study.

Author

Sarfraz, Syed Ali, Abbas, Muntazir, and Ahmad, Nasir Mahmood

Subjects
SEAWATER composition, SEAWATER corrosion, RAMAN scattering, SCANNING electron microscopy, HEAT exchangers
Abstract

Cupronickel-based alloys are widely known for their excellent resistance against aqueous corrosion, however, they can be susceptible to corrosion at accelerated rates and premature failure when exposed to a polluted or brackish seawater medium, even for short-term exposure durations. This unfamiliar corrosion behavior may be a result of the formation of an unprotected corrosion film during the early exposure durations. The paper investigates the corrosion phenomenon in cupronickel 90/10 alloy, by exposing the coupons in two different seawater compositions in the Arabian Sea region. Corrosion losses were investigated on the experimental coupons in a submerged position, for a maximum exposure duration of 150 days, using the conventional weight loss method and a new dimensional metrology-based measurement technique. Additionally, in this research the tubes of a marine heat exchanger having similar material that failed prematurely during operation in the Arabian Sea were also investigated for corrosion losses, followed by the characterization of the corrosion deposits using following analytical techniques: SEM, EDS, XRD and Raman Scattering. The experimental results showed significantly higher corrosion losses on coupons exposed to seawater site rich in pollutants and nutrients including dissolved inorganic nitrogenous compounds, compared to those subjected to a natural seawater solution in corrosion tanks maintained in a controlled environment. [ABSTRACT FROM AUTHOR]

Published
2024
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35. Homology modeling and molecular docking study of metabotropic glutamate receptor 5 variant F: an attempt to develop drugs for treating CNS diseases.

Author

Ahmad, Nasir, Khan, Khalid, Rashid, Haroon ur, Khan, Sher Wali, Umar, Muhammad Naveed, Gulfam, Naila, Zahoor, Muhammad, Ullah, Riaz, and Ali, Essam A.

Subjects
TRANSMEMBRANE domains, FRAGILE X syndrome, ALTERNATIVE RNA splicing, CENTRAL nervous system, G protein coupled receptors
Abstract

G protein-coupled receptors (GPCRs) constitute the largest protein family involved in signal transduction and are the main targets for drug delivery. The metabotropic glutamate receptors (mGluRs) are class C of GPCRs that contribute to the modulation of glutamatergic neurotransmission which regulates vital physiological processes and is recognized as a potential therapeutic target throughout the central nervous system. Intracellular C-terminal domains of mGluR are the main targets for proteins regulating these receptors and are also involved in alternative splicing, regulation by phosphorylation, and modulatory protein-protein interactions. Class C of GPCRs exist as dimers and is mediated by interactions between the venus tryflap domain and the transmembrane domain. The mGluR5 variant F can be regulated by both positive and negative allosteric modulators that can potentiate or inhibit the endogenous ligand and glutamate, respectively. Moreover, mGluR5 is involved in many disorders including fragile X syndrome/autism spectrum disorder, schizophrenia, anxiety, addiction, chronic pain and epilepsy, etc. The main purpose of current computational work is to determine the 3D structures of the target protein and their active sites to design new drug molecules as potential biochemical agents. The 3D model of the mGluR5 variant F was constructed through homology modeling techniques using MOE and I-TESSER programs. RAMPAGE and ERRATE online servers were used for the 3D structure evaluation and validation. Furthermore, the mGluR5 variant F was docked with 20 mavoglurant derivatives that act as antagonists. Mavoglurant derivatives 3, 4, 6, 10, 13, 18, and 19 showed a maximum of four interactions with the mGluR5 variant F, whereas derivatives 7, 8, 9, 11, 12, 15, 16, 17 and 20 showed a maximum of three interactions with the mGluR5 variant F. The remaining four mavoglurant derivatives expressed two interactions each with mGluR5 variant F. The docking score for these derivatives ranged between −15.55 and −08.210 kcal mol−1 suggesting their strong interactions with the mGluR5 variant F. Their 3D structure and docking study provides a potential base for the synthesis of new drug candidates to treat brain disorders. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Regenerable chitosan-embedded magnetic iron oxide beads for nitrate removal from industrial wastewater

Author

Nasir, Muntaha, primary, Javaid, Farhan, additional, Masood, M. Talha, additional, Arshad, Dr Muhammad, additional, Yasir, Muhammad, additional, Sedlarik, Vladimir, additional, Qadir, Muhammad Abdel, additional, Qiblawey, Hazim, additional, Zhang, Wenjuan, additional, Deen, Kashif Mairaj, additional, Asselin, Edouard, additional, and Ahmad, Nasir M., additional

Published
2024
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42. Hydrocracking Rubber Seeds Oil for Biofuel Production Using Bifunctional Sarulla‐Derived Natural Zeolite–Ni and Ni–Mo/SNZ Catalyst.

Author

Sihombing, Junifa Layla, Kembaren, Agus, Herlinawati, Herlinawati, Dewi, Ratna Sari, Pulungan, Ahmad Nasir, Veronika, Nia, Karimah, Fithriyyah, Pangaribuan, Rabiatul Adawiyah, Rahayu, Rahayu, and Wibowo, Ary Anggara

Subjects
ZEOLITE catalysts, BIOMASS energy, HYDROCRACKING, VEGETABLE oils, CATALYSTS, ATMOSPHERIC pressure, RUBBER, CRUMB rubber, GASOLINE
Abstract

Rubber seeds, due to their rich vegetable oil content, emerge as a promising substrate for biofuel production. Harnessing the progressive catalytic hydrocracking methodology, this research delves into the activation of Sarulla‐derived natural zeolite followed by Ni and Ni–Mo metal impregnation, subsequently subjecting rubber seed oil to hydrocracking at 400, 450, and 500 °C under atmospheric pressure at 0.1 MPa. Zeolite characteristics undergo notable transformations postmetal impregnation. Importantly, at 500 °C, gasoline fraction selectivity exhibits superior efficacy, with the Ni/SNZ‐A catalyst demonstrating consistently high selectivity (>85%) across varied temperatures. Posthydrocracking reveals an amplification in n‐paraffin, aromatic, olefin, and methyl ester profiles to 19.6%, 7.3%, 25.7%, and 17.7%, respectively, contrasting the diminution of cycloparaffin, carboxylic acid, and ketones to 3.6%, 0.2%, and 2.5%, respectively. The aforementioned discoveries hold significant importance in the realm of further investigation into the generation of gasoline fractions through the utilization of natural zeolite catalysts and the incorporation of metals with lower mass, all conducted under atmospheric pressure conditions with the ultimate objective of mitigating production expenses. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Ultrafiltration polyanionic poly (3‐sulfopropyl methacrylate) membranes with enhanced antifouling and water flux.

Author

Khan, Raja Muhammad Asif, Nasir, Habib, Mahmood, Azhar, Iqbal, Mudassir, Janjua, Hussnain A., and Ahmad, Nasir M.

Subjects
ULTRAFILTRATION, CONTACT angle, METHACRYLATES, SURFACE energy, ESCHERICHIA coli, WATER purification, POLYETHERSULFONE
Abstract

Polyethersulfone (PES) membranes are prevalent in the field of water treatment owing to their exceptional separation efficiency, robust mechanical properties, and resistance to chemical degradation. Nevertheless, these membranes are prone to fouling, resulting in a decrease in both flux and ultrafiltration efficiency. In the present study, PES membranes are blended with poly (3‐Sulfopropyl Methacrylate) (PSPMA) in various weight percentages (0%–3%) to improve their antifouling and ultrafiltration properties. The physicochemical properties of the blended membranes, including surface morphology, contact angle, hydrophilicity and surface energy are evaluated. The findings indicate that incorporation PSPMA results in an enhancement of the hydrophilic properties and surface charge of the PES membranes, assessed by employing Bovine Serum Albumin (BSA) as a representative protein. Modified blended membranes display greater Flux Recovery Ratio (FRR%) and exhibit superior fouling resistance. Under the same experimental conditions (0.2 MPa applied pressure), a pure water flux of 154.18 L·m−2·h−1 for PES/PSPMA membrane found substantially greater than pure PES membrane (103.52 L·m−2·h−1) along with Total Fouling Ratio (TFR) of 36% and 64.9% respectively. Exceptional antimicrobial efficacy for modified membranes is revealed against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) using disc diffusion technique rendering them well‐suited for water treatment applications. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Good vs bad returns spillover in regional energy markets.

Author

Naeem, Muhammad Abubakr, Rehman, Mobeen Ur, Ahmad, Nasir, Vo, Xuan Vinh, and Karim, Sitara

Subjects
ENERGY industries
Abstract

In this paper, we examine the presence of spillover among the regional energy markets in Asia, Europe, North America, Pacific region, and South America from January 2, 1995 to May 27, 2021. We report heterogeneous results for spillover between the regional energy markets. Our work separately highlights the presence of negative and positive returns spillover across sampled energy markets. We also report a significant increase in spillover during different crisis periods, supporting the contagion phenomena. Finally, we also report the asymmetry in short- and long-run spillover and negative and positive returns during normal and crisis periods. Our results carry implications for investments in the regional energy markets under different market conditions and investment periods. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Fabrication of Fe3O4based cellulose acetate mixed matrix membranes for As(iii) removal from wastewater

Author

Liaquat, Sidra, Farrukh, Sarah, Ahmad, Nasir, Karim, Syed Shujaat, Pervaiz, Erum, Sultan, Ayesha, and Ali, Subhan

Abstract

Water poisoning due to arsenic is getting worse worldwide because of its serious health hazards and carcinogenic nature. A productive method is required to remove it from water to protect the environment and human life. In this direction, iron oxide (Fe3O4)/cellulose acetate (CA)-based mixed matrix membranes (MMMs) were fabricated by varying the concentration of Fe3O4nanoparticles from 0–2 wt% using the phase inversion method for efficient As(iii) removal. The impact of Fe3O4on the membranes' surface morphology and mechanical properties was analyzed through scanning electron microscopy (SEM) and ultimate tensile strength (UTS). Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) were performed for chemical functionalities and phase structure analysis. Atomic Adsorption Spectrophotometry (AAS) is used to detect the As(iii) concentration in water samples. The As(iii) adsorption experiments were performed at different concentrations with varying time intervals, and the coefficient of determination and sum of square error function were used to conduct the analysis. The results were best fitted into the Langmuir isotherm model (R2> 0.99) with a maximum adsorption capacity of 90.3 mg g−1. The pseudo-second-order and Weber-Morris models were used to examine intra-particle diffusion as a rate-limiting step. According to membrane performance tests, the nanoparticles' addition increased the hydrophilicity and water flux, improving the membranes' permeability, wettability, and porosity. It was found that a 2 wt% loading of Fe3O4nanoparticles in the MMM achieved a maximum percentage As(iii) removal efficiency of 93%. This study shows that these membranes can efficiently remove As(iii) from contaminated water because of their adsorption and filtration properties.

Published
2024
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46. The Impact of a Modular Robotic Total Mesorectal Excision Training Program on Perioperative and Oncological Outcomes in Robotic Rectal Cancer Surgery.

Author

Stefan S, Piozzi GN, Tejedor P, Liao CCL, Ahmad A, Ahmad NZ, Naqvi SAH, Heald RJ, and Khan JS

Subjects
Humans, Male, Female, Retrospective Studies, Middle Aged, Aged, Operative Time, Proctectomy methods, Proctectomy education, Treatment Outcome, Clinical Competence, Robotic Surgical Procedures education, Robotic Surgical Procedures methods, Rectal Neoplasms surgery, Rectal Neoplasms pathology
Abstract

Background: Structured training programs for robotic colorectal surgery are limited, and there are concerns about surgical outcomes and operating times., Objective: To compare perioperative and oncological outcomes of robotic total mesorectal excision for rectal cancer performed by expert consultants and surgical trainees in a modular surgical training program., Design: Retrospective cohort study., Settings: Conducted at a colorectal training referral center for robotic surgery., Patients: Consecutive robotic total mesorectal excision cases between May 2013 and December 2017 were evaluated retrospectively from a prospectively maintained institutional database and divided into 2 groups: group I comprised expert surgeons and group II comprised supervised trainees. Robotic total mesorectal excision training modules (5 modules) were performed stepwise with increasing complexity. Patients' demographic, perioperative, and oncological data were collected., Interventions: Modular robotic training., Main Outcome Measures: Comparable R0 resection rate, lymph node harvest, and oncological outcomes between experts and trainees, suggesting good quality in oncological resection., Results: A total of 177 robotic total mesorectal excision resections were performed (group I: n = 80, group II: n = 97). Four trainees completed 37.5 modules each. Patients' age, sex, and BMI were similar between groups. Group II had a higher ASA III score (6.3% vs 25.8%, p = 0.002). Clinical TNM and neoadjuvant chemoradiotherapy rates were similar. Group II had a longer operative time (225 [197.5-297.5] vs 250 [230-300] minutes, p = 0.004). No conversion occurred. There were no differences in intra- or postoperative outcomes between groups. The rate of R0 resection and the number of harvested lymph nodes were also similar between groups. The median follow-up was 75 (64.0-81.7) and 47 (38.0-55.0) months, respectively. Local and distant recurrence rates, 5-year overall survival (81.1% group I vs 81.3% group II, p = 0.832), and 5-year disease-free survival (79.7% group I vs 80.7% group II, p = 0.725) were similar between groups., Limitations: The groups operated in 2 consecutive periods., Conclusions: The robotic total mesorectal excision modular surgical training program maximizes training experience without significantly affecting the perioperative and oncological outcomes of patients with rectal cancer. See Video Abstract., El Impacto Del Programa Modular De Entrenamiento En Escisin Mesorrectal Total Robtica En Los Resultados Perioperatorios Y Oncolgicos En La Ciruga Robtica Del Cncer De Recto: ANTECEDENTES:Los programas de entrenamiento estructurados para la cirugía colorrectal robótica están limitados debido a preocupaciones sobre los resultados quirúrgicos y los tiempos de operación.OBJETIVO:Comparar los resultados perioperatorios y oncológicos de la escisión mesorrectal total robótica para el cáncer de recto realizada por consultores expertos y aprendices de cirugía en un programa modular de entrenamiento quirúrgica.DISEÑO:Estudio de cohorte retrospectivo.AJUSTES:Realizado en un centro de referencia de entrenamiento colorrectal para cirugía robótica.PACIENTES:Se evaluaron retrospectivamente casos consecutivos de escisión mesorrectal total robótica entre mayo de 2013 y diciembre de 2017 a partir de una base de datos institucional mantenida prospectivamente y se dividieron en dos grupos: Grupo I: cirujanos expertos; Grupo II: aprendices supervisados. Los módulos de entrenamiento robótico de escisión mesorrectal total (cinco módulos) se realizaron paso a paso con complejidad creciente. Se recogieron datos demográficos, perioperatorios y oncológicos.INTERVENCIONES:Entrenamiento modular en robótica.PRINCIPALES MEDIDAS DE RESULTADO:Tasa de resección R0 comparable, extracción de ganglios linfáticos y resultados oncológicos entre expertos y aprendices que sugieren buena calidad en la resección oncológica.RESULTADOS:Se realizaron un total de 177 resecciones por escisión mesorrectal total robótica (Grupo I: n = 80, Grupo II: n = 97). Cuatro alumnos completaron 37,5 módulos cada uno. La edad, el sexo y el IMC fueron similares entre los grupos. El grupo II tuvo una puntuación más alta de la Sociedad Americana de Anestesiólogos III (6,3% frente a 25,8%, p = 0,002). Las tasas clínicas de TNM y quimiorradioterapia neoadyuvante fueron similares. El grupo II tuvo mayor tiempo operatorio (225 (197,5-297,5) vs 250 (230-300) minutos, p = 0,004). No se produjo ninguna conversión. No hubo diferencias en los resultados intra o posoperatorios entre los grupos. La tasa de resección R0 y el número de ganglios linfáticos extraídos también fueron similares entre los grupos. La mediana de seguimiento fue de 75 (64,0-81,7) y 47 (38,0-55,0) meses, respectivamente. Tasas de recurrencia local y a distancia, supervivencia general a 5 años (81,1% Grupo I vs. 81,3% Grupo II, p = 0,832) y supervivencia libre de enfermedad a 5 años (79,7% Grupo I vs. 80,7% Grupo II, p = 0,725) fueron similares entre los grupos.LIMITACIONES:Los grupos operaron en dos períodos consecutivos.CONCLUSIONES:El programa de entrenamiento quirúrgico modular para la escisión mesorrectal total robótica maximiza la experiencia de capacitación sin afectar significativamente los resultados perioperatorios y oncológicos de los pacientes con cáncer de recto. (Traducción-Dr. Aurian Garcia Gonzalez)., (Copyright © The ASCRS 2024.)

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2024
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47. Bioactivity of a dihydroxy flavone produced by Penicillium EU0013 against the wilt pathogen of tomato.

Author

Zulqarnain, Iqbal Z, Anwar J, Iqbal M, Manzoor N, Ahmad N, Khattak SU, Alam SS, and Sakamoto K

Abstract

Bioassay-guided isolation of a dihydroxy flavone from the cell extract of Penicillium EU0013 was carried out using preparative LCMS and the structure was interpreted using 1D and 2D NMR spectra. The fungus was fermented in three different nutrient media i.e. Glucose Nutrient Broth, Glucose Peptone Yeast Broth, and Yeast Extract Broth and the cell extract was obtained using organics. Comparative LCMS profiles of the fungus confirmed the enhanced production of dihydroxy flavone in GPYB media. In this study, the pathogenicity of the dihydroxy flavone is reported for the first time against Fusarium oxysporum f.sp. lycopersici , wilt causing pathogen of a tomato plant. In MIC experiments, the compound inhibited the pathogen at 80 µg mL -1 . Molecular docking studies of the compound with Fol tomatinase showed five binding interactions. These docking studies may help explore dihydroxy flavones as a lead for developing new fungicides to prevent wilt disease in tomatoes.

Published
2024
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48. Utilizing Un-enhanced Chest Computed Tomography Screening for Blunt Trauma Surgery Decisions.

Author

Baseer A, Noor N, Aman N, and Qureshi AN

Abstract

Background Blunt chest trauma is a common and potentially life-threatening condition that requires prompt assessment for potential surgical intervention. Computed tomography (CT) of the chest has emerged as a valuable tool due to its heightened sensitivity and specificity in detecting thoracic injuries compared to conventional chest radiography. Objective This study aims to assess the impact of non-contrast CT chest findings on surgical decision-making and compare these findings with those from chest radiographs. Methods The study was conducted at the Accident and Emergency Department of Medical Teaching Institute, Lady Reading Hospital, Peshawar, Khyber Pakhtunkhwa, Pakistan. Patients of all ages and genders who presented with blunt chest trauma were included. Non-contrast CT chest scans were used as an initial screening tool and compared with traditional chest radiographs. Data collected included patient demographics, mechanism of injury, diagnostic findings, and treatment decisions. Imaging was performed using a GE Optima 16-slice scanner (Medsystems Sp. z o.o., Lublin, Poland). Results The study included 246 patients, of whom 210 (85.4%) were males. The most common age group was 50 years or older, comprising 71 (28.9%) of the sample. The predominant mechanism of trauma was road traffic accidents, reported by 188 (76.4%) patients. Hemopneumothorax was detected in 121 (49.2%) patients on CT scans compared to 34 (13.8%) patients on chest radiographs. On chest radiograph, the pneumothorax component was missed in 43 (17.5%) patients, and the hemothorax component was not detected in 21 (8.5%) patients. Patient management included conservative management in 30 (12.2%) cases and surgical intervention in the form of unilateral tube thoracostomy in 173 (70.3%) patients or bilateral tube thoracostomy in 43 (17.5%) patients. Conclusion Our study supports the use of non-contrast CT scans as a reliable diagnostic tool for blunt chest trauma, consistent with current literature. This approach facilitates prompt management decisions, particularly for initiating tube thoracostomy based on findings of pneumothorax and hemothorax. The rarity of mediastinal great vessel trauma further justifies minimizing routine contrast use, thereby enhancing the efficiency of trauma evaluations., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Institutional Review Board, Lady Reading Hospital, Peshawar, Pakistan issued approval 257/LRH/MTI/IRB. All the protocols were approved by the Institutional Review Board (IRB), Lady Reading Hospital, Peshawar, Pakistan (Ref #257/LRH/MTI/IRB), Dated 11-03-2024. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Baseer et al.)

Published
2024
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49. Meckel's "Wallet": A Unique Case of Intestinal Obstruction.

Author

Syeda WE, Azim SA, and Ahmad NZ

Abstract

While bowel obstruction is the most common surgical disorder of the small intestine, small bowel obstruction due to Meckel's diverticulum is a relatively rare occurrence. We encountered a compelling case of small bowel obstruction that turned out to be more complex than anticipated, involving a Meckel's diverticulum with some unforeseen findings. We followed standard guidelines for history-taking, examination, investigations, and management of the intestinal obstruction. After exhausting conservative treatment options, we opted for surgical intervention, and the unexpected cause of the obstruction took us by surprise. This case report highlights an exceedingly rare entity: Meckel's diverticulum precipitating uncommon complications., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Syeda et al.)

Published
2024
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50. Direct synthesis, characterization, in vitro and in silico studies of simple chalcones as potential antimicrobial and antileishmanial agents.

Author

Ur Rashid H, Khan S, Irum, Khan A, Ahmad N, Shah T, and Khan K

Abstract

Chalcone represents a vital biosynthetic scaffold owing to its numerous therapeutic effects. The present study was intended to synthesize 17 chalcone derivatives ( 3a - q ) by direct coupling of substituted acetophenones and benzaldehyde. The target chalcones were characterized by spectroscopic analyses followed by their in vitro antimicrobial, and antileishmanial investigations with reference to standard drugs. The majority of the chalcones displayed good to excellent biological activities. Chalcone 3q (1000 µg ml -1 ) exhibited the most potent antibacterial effect with its zone of inhibition values of 30, 33 and 34 mm versus Staphylococcus aureus , Escherichia coli and Pseudomonas aeruginosa respectively. The results also confirmed chalcone 3q to be the most potent versus Leishmania major with the lowest IC 50 value of 0.59 ± 0.12 µg ml -1 . Chalcone 3i (500 µg ml -1 ) was noticed to be the most potent antifungal agent with its zone of inhibition being 29 mm against Candida albicans . Computational studies of chalcones 3i and 3q supported the preliminary in vivo results. The existence of the amino moiety and bromine atom on ring-A and methoxy moieties on ring-B caused better biological effects of the chalcones. In brief, the investigations reveal that chalcones ( 3i and 3q ) can be employed as building blocks to discover novel antimicrobial agents., Competing Interests: The authors declare no conflict of interest., (© 2024 The Authors.)

Published
2024
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