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4. The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions

Author

Ullah, Amin, Qi, Guilin, Hussain, Saddam, Ullah, Irfan, and Ali, Zafar

Subjects
Computer Science - Artificial Intelligence
Abstract

Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living standards, facilitating the rapid expansion of urban areas while efficiently managing resources through sustainable and scalable innovations. In this regard, as emerging technologies like Artificial Intelligence (AI), the Internet of Things (IoT), big data analytics, and fog and edge computing have become increasingly prevalent, smart city applications grapple with various challenges, including the potential for unauthorized disclosure of confidential and sensitive data. The seamless integration of emerging technologies has played a vital role in sustaining the dynamic pace of their development. This paper explores the substantial potential and applications of Deep Learning (DL), Federated Learning (FL), IoT, Blockchain, Natural Language Processing (NLP), and large language models (LLMs) in optimizing ICT processes within smart cities. We aim to spotlight the vast potential of these technologies as foundational elements that technically strengthen the realization and advancement of smart cities, underscoring their significance in driving innovation within this transformative urban milieu. Our discourse culminates with an exploration of the formidable challenges that DL, FL, IoT, Blockchain, NLP, and LLMs face within these contexts, and we offer insights into potential future directions.

Published
2024

22. RweetMiner: Automatic identification and categorization of help requests on twitter during disasters

Author

Ullah, Irfan, Khan, Sharifullah, Imran, Muhammad, and Lee, Young-Koo

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Catastrophic events create uncertain situations for humanitarian organizations locating and providing aid to affected people. Many people turn to social media during disasters for requesting help and/or providing relief to others. However, the majority of social media posts seeking help could not properly be detected and remained concealed because often they are noisy and ill-formed. Existing systems lack in planning an effective strategy for tweet preprocessing and grasping the contexts of tweets. This research, first of all, formally defines request tweets in the context of social networking sites, hereafter rweets, along with their different primary types and sub-types. Our main contributions are the identification and categorization of rweets. For rweet identification, we employ two approaches, namely a rule-based and logistic regression, and show their high precision and F1 scores. The rweets classification into sub-types such as medical, food, and shelter, using logistic regression shows promising results and outperforms existing works. Finally, we introduce an architecture to store intermediate data to accelerate the development process of the machine learning classifiers.

Published
2023
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24. 3D UAV Trajectory Design for Fair and Energy-Efficient Communication: A Deep Reinforcement Learning Technique

Author

Rasool, Shahid, Ullah, Irfan, Ali, Abid, and Ahmad, Ishtiaq

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Systems and Control
Abstract

In different situations, like disaster communication and network connectivity for rural locations, unmanned aerial vehicles (UAVs) could indeed be utilized as airborne base stations to improve both the functionality and coverage of communication networks. Ground users can employ mobile UAVs to establish communication channels and deliver packages. UAVs, on the other hand, have restricted transmission capabilities and fuel supplies. They can't always cover the full region or continue to fly for a long time, especially in a huge territory. Controlling a swarm of UAVs to yield a relatively long communication coverage while maintaining connectivity and limiting energy usage is so difficult. We use modern deep reinforcement learning (DRL) for UAV connectivity to provide an innovative and extremely energy-efficient DRL-based algorithm. The proposed method: 1) enhances novel energy efficiency while taking into account communications throughput, energy consumption, fairness, and connectivity; 2) evaluates the environment and its dynamics; and 3) makes judgments using strong deep neural networks. For performance evaluation, we have performed comprehensive simulations. In terms of energy consumption and fairness, simulation results show that the DRL-based algorithm consistently outperforms two commonly used baseline techniques.

Published
2023

25. Citation Recommendation Employing Proximity-Based Heterogeneous Network Embeddings

Author

Ali, Zafar, Ullah, Irfan, Kefalas, Pavlos, Thierry, Nimbeshaho, Haq, Kalim Ul, Sarkar, Anupam, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, and Arai, Kohei, editor

Published
2024
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26. Precise Single-stage Detector

Author

Chandio, Aisha, Gui, Gong, Kumar, Teerath, Ullah, Irfan, Ranjbarzadeh, Ramin, Roy, Arunabha M, Hussain, Akhtar, and Shen, Yao

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

There are still two problems in SDD causing some inaccurate results: (1) In the process of feature extraction, with the layer-by-layer acquisition of semantic information, local information is gradually lost, resulting into less representative feature maps; (2) During the Non-Maximum Suppression (NMS) algorithm due to inconsistency in classification and regression tasks, the classification confidence and predicted detection position cannot accurately indicate the position of the prediction boxes. Methods: In order to address these aforementioned issues, we propose a new architecture, a modified version of Single Shot Multibox Detector (SSD), named Precise Single Stage Detector (PSSD). Firstly, we improve the features by adding extra layers to SSD. Secondly, we construct a simple and effective feature enhancement module to expand the receptive field step by step for each layer and enhance its local and semantic information. Finally, we design a more efficient loss function to predict the IOU between the prediction boxes and ground truth boxes, and the threshold IOU guides classification training and attenuates the scores, which are used by the NMS algorithm. Main Results: Benefiting from the above optimization, the proposed model PSSD achieves exciting performance in real-time. Specifically, with the hardware of Titan Xp and the input size of 320 pix, PSSD achieves 33.8 mAP at 45 FPS speed on MS COCO benchmark and 81.28 mAP at 66 FPS speed on Pascal VOC 2007 outperforming state-of-the-art object detection models. Besides, the proposed model performs significantly well with larger input size. Under 512 pix, PSSD can obtain 37.2 mAP with 27 FPS on MS COCO and 82.82 mAP with 40 FPS on Pascal VOC 2007. The experiment results prove that the proposed model has a better trade-off between speed and accuracy., Comment: We will submit it soon to the IEEE transaction. Due to characters limitation, we can not upload the full abstract. Please read the pdf file for more detail

Published
2022

40. A network analysis of the Internet Disorder Scale-Short Form (IDS9-SF): A large-scale cross-cultural study in Iran, Pakistan, and Bangladesh

Author

Li, Li, Mamun, Mohammed A., Al-Mamun, Firoj, Ullah, Irfan, Hosen, Ismail, Zia, Syed Ahsan, Poorebrahim, Ali, Pourgholami, Morteza, Lin, Chung-Ying, Pontes, Halley M., Griffiths, Mark D., and Pakpour, Amir H.

Subjects
Psychological research, Pathological Internet Use -- Diagnosis, Ethnopsychology -- Research, Psychological tests -- Evaluation, Psychology and mental health
Abstract

The Internet Disorder Scale-Short Form (IDS9-SF) is a validated instrument assessing internet disorder which modified the internet gaming disorder criteria proposed in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). However, the relationships between the nine items in the IDS9-SF are rarely investigated. The present study used network analysis to investigate the features of the IDS9-SF among three populations in Bangladesh, Iran, and Pakistan. Data were collected (N = 1901; 957 [50.3%] females; 666 [35.0%] Pakistani, 533 [28.1%] Bangladesh, and 702 [36.9%] Iranians) using an online survey platform (e.g., Google Forms). All the participants completed the IDS9-SF. The central-stability-coefficients of the nine IDS9-SF items were 0.71, 0.89, 0.96, 0.98, 0.98, 1.00, 0.67, 0.79, and 0.91, respectively. The node centrality was stable and interpretable in the network. The Network Comparison Test (NCT) showed that the network structure had no significant differences among Pakistani, Bangladeshi, and Iranian participants (p-values = 0.172 to 0.371). Researchers may also use the IDS9-SF to estimate underlying internet addiction for their target participants and further explore and investigate the phenomenon related to internet addiction., Author(s): Li Li [sup.1] , Mohammed A. Mamun [sup.2] [sup.14] [sup.15] [sup.16] , Firoj Al-Mamun [sup.2] [sup.14] [sup.16] , Irfan Ullah [sup.3] , Ismail Hosen [sup.2] , Syed Ahsan Zia [...]

Published
2023
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42. Cutaneous signs of selected cardiovascular disorders: A narrative review

Author

Asif Marium, Yousuf Muhammad Hamza, Farooqui Usman Shakeel, Nashwan Abdulqadir J., and Ullah Irfan

Subjects
skin manifestations, cutaneous signs, cardiovascular diseases, diagnosis, treatment, Medicine
Abstract

Cardiovascular diseases are the leading cause of mortality and morbidity globally. Clinicians must know cutaneous signs of cardiovascular disease, including petechiae, macules, purpura, lentigines, and rashes. Although cutaneous manifestations of diseases like infectious endocarditis and acute rheumatic fever are well established, there is an indispensable need to evaluate other important cardiovascular diseases accompanied by cutaneous signs. Moreover, discussing the latest management strategies in this regard is equally imperative. This review discusses distinctive skin findings that help narrow the diagnosis of cardiovascular diseases and recommendations on appropriate treatment.

Published
2024
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44. Results of the COVID-19 mental health international for the health professionals (COMET-HP) study: depression, suicidal tendencies and conspiracism

Author

N. Fountoulakis, Konstantinos, N. Karakatsoulis, Grigorios, Abraham, Seri, Adorjan, Kristina, Ahmed, Helal Uddin, Alarcón, Renato D., Arai, Kiyomi, Auwal, Sani Salihu, Bobes, Julio, Bobes-Bascaran, Teresa, Bourgin-Duchesnay, Julie, Bredicean, Cristina Ana, Bukelskis, Laurynas, Burkadze, Akaki, Cabrera Abud, Indira Indiana, Castilla-Puentes, Ruby, Cetkovich, Marcelo, Colon-Rivera, Hector, Corral, Ricardo, Cortez-Vergara, Carla, Crepin, Piirika, de Berardis, Domenico, Zamora Delgado, Sergio, de Lucena, David, de Sousa, Avinash, di Stefano, Ramona, Dodd, Seetal, Elek, Livia Priyanka, Elissa, Anna, Erdelyi-Hamza, Berta, Erzin, Gamze, Etchevers, Martin J., Falkai, Peter, Farcas, Adriana, Fedotov, Ilya, Filatova, Viktoriia, Fountoulakis, Nikolaos K., Frankova, Iryna, Franza, Francesco, Frias, Pedro, Galako, Tatiana, Garay, Cristian J., Garcia-Álvarez, Leticia, García-Portilla, Paz, Gonda, Xenia, Gondek, Tomasz M., Morera González, Daniela, Gould, Hilary, Grandinetti, Paolo, Grau, Arturo, Groudeva, Violeta, Hagin, Michal, Harada, Takayuki, Hasan, Tasdik M., Azreen Hashim, Nurul, Hilbig, Jan, Hossain, Sahadat, Iakimova, Rossitza, Ibrahim, Mona, Iftene, Felicia, Ignatenko, Yulia, Irarrazaval, Matias, Ismail, Zaliha, Ismayilova, Jamila, Jacobs, Asaf, Jakovljević, Miro, Jakšić, Nenad, Javed, Afzal, Yilmaz Kafali, Helin, Karia, Sagar, Kazakova, Olga, Khalifa, Doaa, Khaustova, Olena, Koh, Steve, Kopishinskaia, Svetlana, Kosenko, Korneliia, Koupidis, Sotirios A., Kovacs, Illes, Kulig, Barbara, Lalljee, Alisha, Liewig, Justine, Majid, Abdul, Malashonkova, Evgeniia, Malik, Khamelia, Iqbal Malik, Najma, Mammadzada, Gulay, Mandalia, Bilvesh, Marazziti, Donatella, Marčinko, Darko, Martinez, Stephanie, Matiekus, Eimantas, Mejia, Gabriela, Memon, Roha Saeed, Meza Martínez, Xarah Elenne, Mickevičiūtė, Dalia, Milev, Roumen, Mohammed, Muftau, Molina-López, Alejandro, Morozov, Petr, Muhammad, Nuru Suleiman, Mustač, Filip, Naor, Mika S., Nassieb, Amira, Navickas, Alvydas, Okasha, Tarek, Pandova, Milena, Panfil, Anca-Livia, Panteleeva, Liliya, Papava, Ion, Patsali, Mikaella E., Pavlichenko, Alexey, Pejuskovic, Bojana, Pinto da Costa, Mariana, Popkov, Mikhail, Popovic, Dina, Raduan, Nor Jannah Nasution, Vargas Ramírez, Francisca, Rancans, Elmars, Razali, Salmi, Rebok, Federico, Rewekant, Anna, Reyes Flores, Elena Ninoska, Rivera-Encinas, María Teresa, Saiz, Pilar A., Sánchez de Carmona, Manuel, Saucedo Martínez, David, Saw, Jo Anne, Saygili, Görkem, Schneidereit, Patricia, Shah, Bhumika, Shirasaka, Tomohiro, Silagadze, Ketevan, Sitanggang, Satti, Skugarevsky, Oleg, Spikina, Anna, Mahalingappa, Sridevi Sira, Stoyanova, Maria, Szczegielniak, Anna, Tamasan, Simona Claudia, Tavormina, Giuseppe, Tavormina, Maurilio Giuseppe Maria, Theodorakis, Pavlos N., Tohen, Mauricio, Tsapakis, Eva-Maria, Tukhvatullina, Dina, Ullah, Irfan, Vaidya, Ratnaraj, Vega-Dienstmaier, Johann M., Vrublevska, Jelena, Vukovic, Olivera, Vysotska, Olga, Widiasih, Natalia, Yashikhina, Anna, Prezerakos, Panagiotis E., Berk, Michael, Levaj, Sarah, and Smirnova, Daria

Published
2023
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45. Examining Fruit Demand Elasticities In Pakistan

Author

Iqbal Sarah, Fayaz Muhammad, Ullah Irfan, Uçak Harun, Shah Syed Attaullah, and Sayam Farheen

Subjects
fruits, la/aids, expenditures elasticities, marshallian elasticities, hicksian elasticities, pakistan, d12, q02, q10, q11, Finance, HG1-9999, Economic theory. Demography, HB1-3840
Abstract

Income and prices are important factors that determine and decide households consumption decisions and behavior.

Published
2023
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47. Global, regional, and national burden of injuries, and burden attributable to injuries risk factors, 1990 to 2019: results from the Global Burden of Disease study 2019

Author

Malekpour, Mohammad-Reza, Rezaei, Negar, Azadnajafabad, Sina, Khanali, Javad, Azangou-Khyavy, Mohammadreza, Moghaddam, Sahar Saeedi, Heidari-Foroozan, Mahsa, Rezazadeh-Khadem, Sahba, Ghamari, Seyyed-Hadi, Abbasi-Kangevari, Mohsen, Abady, Gdiom Gebreheat, Abdulkader, Rizwan Suliankatchi, Abebe, Ayele Mamo, Abu-Gharbieh, Eman, Acharya, Dilaram, Addo, Isaac Yeboah, Adeagbo, Oluwafemi Atanda, Adegboye, Oyelola A., Adeyinka, Daniel Adedayo, Sakilah Adnani, Qorinah Estiningtyas, Afolabi, Aanuoluwapo Adeyimika, Afzal, Saira, Afzal, Muhammad Sohail, Ahmad, Sajjad, Ahmad, Aqeel, Ahmadi, Ali, Ahmadieh, Hamid, Ahmed, Haroon, Ahmed, Mehrunnisha Sharif, Ajami, Marjan, Akbarialiabad, Hossein, Akunna, Chisom Joyqueenet, Alahdab, Fares, Alanezi, Fahad Mashhour, Alanzi, Turki M., Alhassan, Robert Kaba, Ali, Liaqat, Samakkhah, Shohreh Alian, Alimohamadi, Yousef, Aljunid, Syed Mohamed, Almustanyir, Sami, Al-Sabah, Salman Khalifah, Altirkawi, Khalid A., Amare, Hiwot, Ameyaw, Edward Kwabena, Amin, Tarek Tawfik, Amiri, Sohrab, Andrei, Tudorel, Andrei, Catalina Liliana, Anvari, Davood, Anwar, Sumadi Lukman, Aqeel, Muhammad, Arab-Zozani, Morteza, Arumugam, Ashokan, Aryal, Umesh Raj, Asaad, Malke, Asgary, Saeed, Ashraf, Tahira, Astell-Burt, Thomas, Athari, Seyyed Shamsadin, Atreya, Alok, Aujayeb, Avinash, Awedew, Atalel Fentahun F., Quintanilla, Beatriz Paulina Ayala, Aychiluhm, Setognal Birara, Ayele, Alemu Degu, Azizi, Hosein, Azzam, Ahmed Y., Bakkannavar, Shankar M., Bardhan, Mainak, Barker-Collo, Suzanne Lyn, Barqawi, Hiba Jawdat, Barrow, Amadou, Bashiri, Azadeh, Baskaran, Pritish, Basu, Saurav, Bedi, Neeraj, Bekele, Alehegn, Belo, Luis, Bennett, Derrick A., Bensenor, Isabela M., Berhie, Alemshet Yirga, Bhagavathula, Akshaya Srikanth, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A., Bitaraf, Saeid, Boloor, Archith, Borges, Guilherme, Borschmann, Rohan, Boufous, Soufiane, Brauer, Michael, Briggs, Andrew M., Brown, Julie, Bryazka, Dana, Cámera, Luis Alberto, Cárdenas, Rosario, Carvalho, Márcia, Catalá-López, Ferrán, Cerin, Ester, Charan, Jaykaran, Chattu, Vijay Kumar, Chien, Wai Tong, Chitheer, Abdulaal, Cho, Daniel Youngwhan, McPhee Christensen, Steffan Wittrup, Christopher, Devasahayam J., Chu, Dinh-Toi, Chukwu, Isaac Sunday, Cislaghi, Beniamino, Clark, Scott Richard, Cruz-Martins, Natalia, Cullen, Patricia, Dadras, Omid, Dai, Xiaochen, Damiani, Giovanni, Dandona, Rakhi, Darmstadt, Gary L., Soltani, Reza Darvishi Cheshmeh, Darwesh, Aso Mohammad, Dávila-Cervantes, Claudio Alberto, De Leo, Diego, de Luca, Katie, Demetriades, Andreas K., Demisse, Biniyam, Demisse, Fitsum Wolde, Demissie, Solomon, Desye, Belay, Dharmaratne, Samath Dhamminda, Diress, Mengistie, Djalalinia, Shirin, Dodangeh, Milad, Dongarwar, Deepa, Edinur, Hisham Atan, Eini, Ebrahim, Ekholuenetale, Michael, Elgar, Frank J., Elgendy, Islam Y., Elhabashy, Hala Rashad, Elhadi, Muhammed, El-Huneidi, Waseem, Emamian, Mohammad Hassan, Bain, Luchuo Engelbert, Enyew, Daniel Berhanie, Eshetu, Habitu Birhan, Eskandarieh, Sharareh, Etaee, Farshid, Fagbamigbe, Adeniyi Francis, Faro, Andre, Fasanmi, Abidemi Omolara, Fatehizadeh, Ali, Feng, Xiaoqi, Fereshtehnejad, Seyed-Mohammad, Ferrara, Pietro, Fetensa, Getahun, Fischer, Florian, Franklin, Richard Charles, Fukumoto, Takeshi, Galali, Yaseen, Galehdar, Nasrin, Gankpe, Fortune Gbetoho, Gebrehiwot, Mesfin, Gebremeskel, Teferi Gebru, Geleta, Leta Adugna, Getachew, Motuma Erena, Ghafourifard, Mansour, Nour, Mohammad Ghasemi, Ghashghaee, Ahmad, Gholamrezanezhad, Ali, Gill, Tiffany K., Ginindza, Themba G., Glasbey, James C., Göbölös, Laszlo, Gohari, Kimiya, Golechha, Mahaveer, Goleij, Pouya, Grivna, Michal, Gunawardane, Damitha Asanga, Gupta, Bhawna, Hall, Brian J., Hamadeh, Randah R., Hamal, Pawan Kumar, Hameed, Sajid, Hamidi, Samer, Hamiduzzaman, Mohammad, Hanif, Asif, Haque, Syed Emdadul, Hargono, Arief, Harlianto, Netanja I., Hartono, Risky Kusuma, Hasaballah, Ahmed I., Hasani, Hamidreza, Hassanian-Moghaddam, Hossein, Hassanipour, Soheil, Hassankhani, Hadi, Hayat, Khezar, Heidari, Mohammad, Hendrie, Delia, Heyi, Demisu Zenbaba, Hiraike, Yuta, Horita, Nobuyuki, Hossain, Mohammad Bellal, Hosseinzadeh, Mehdi, Hoveidaei, Amir Human, Hu, Guoqing, Ilesanmi, Olayinka Stephen, Immurana, Mustapha, Inbaraj, Leeberk Raja, Shariful Islam, Sheikh Mohammed, Islam, Rakibul M., Ismail, Nahlah Elkudssiah, Jagnoor, Jagnoor, Jahrami, Haitham, Jakovljevic, Mihajlo, Jamshidi, Elham, Janodia, Manthan Dilipkumar, Javaheri, Tahereh, Jayapal, Sathish Kumar, Jeganathan, Jayakumar, Jonas, Jost B., Joseph, Nitin, Joukar, Farahnaz, Jürisson, Mikk, Kabir, Ali, Kadashetti, Vidya, Kamath, Rajesh, Kamath, Ashwin, Kamble, Bhushan Dattatray, Kandel, Himal, Kantar, Rami S., Karaye, Ibraheem M., Karkhah, Samad, Kashoo, Faizan Zaffar, Kassa, Bekalu Getnet, Kauppila, Joonas H., Keikavoosi-Arani, Leila, Kemp Bohan, Phillip M., Keykhaei, Mohammad, Khalid, Nauman, Khammarnia, Mohammad, Khan, Moien A.B., Khan, M. Nuruzzaman, Khan, Ejaz Ahmad, Khan, Maseer, Khatatbeh, Moawiah Mohammad, Khubchandani, Jagdish, Kim, Yun Jin, Kim, Gyu Ri, Kisa, Adnan, Kisa, Sezer, Kompani, Farzad, Shivakumar, K.M. Marulasiddaiah Kondlahalli, Koul, Parvaiz A., Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Vijay, Kruger, Estie, Bicer, Burcu Kucuk, Kumar, Nithin, Kumar, Narinder, La Vecchia, Carlo, Lam, Hilton, Lami, Faris Hasan, Landires, Iván, Lansingh, Van Charles, Lauriola, Paolo, Dao Le, Long Khanh, Leasher, Janet L., Ledda, Caterina, Lee, Doo Woong, Han Lee, Yo, Lee, Wei-Chen, Makhiringa Likaka, Andrew Tiyamike, Lim, Stephen S., Linn, Shai, Lucchetti, Giancarlo, Lunevicius, Raimundas, Lyons, Ronan A., Abd El Razek, Mohammed Magdy, Prasad, Mahadeshwara, Mahmoudi, Razzagh, Majeed, Azeem, Malagón-Rojas, Jeadran N., Malakan Rad, Elaheh, Malta, Deborah Carvalho, Manla, Yosef, Mansouri, Borhan, Mansournia, Mohammad Ali, Maravilla, Joemer C., Mathews, Elezebeth, Maulik, Pallab K., Mechili, Enkeleint A., Nasab, Entezar Mehrabi, Mendoza, Walter, Mengistu, Dechasa Adare, Mentis, Alexios-Fotios A., Mesregah, Mohamed Kamal, Mestrovic, Tomislav, Miazgowski, Tomasz, Mir, Shabir Ahmad, Mirica, Andreea, Mirrakhimov, Erkin M., Mirza, Moonis, Mohammadi, Soheil, Mohammed, Shafiu, Moitra, Modhurima, Mokdad, Ali H., Molokhia, Mariam, Monasta, Lorenzo, Moradi, Maryam, Morrison, Shane Douglas, Mubarik, Sumaira, Murillo-Zamora, Efren, Mustafa, Ghulam, Fawzy Nabhan, Ashraf, Nangia, Vinay, Ramos Nascimento, Bruno, Natto, Zuhair S., Negoi, Ionut, Nejadghaderi, Seyed Aria, Nena, Evangelia, Nepal, Samata, Nggada, Haruna Asura, Ngunjiri, Josephine W., Nnaji, Chukwudi A., Nzoputam, Ogochukwu Janet, Nzoputam, Chimezie Igwegbe, Oancea, Bogdan, Obamiro, Kehinde O., Odukoya, Oluwakemi Ololade, Oghenetega, Onome Bright, In-Hwan, Oh, Okati-Aliabad, Hassan, Okonji, Osaretin Christabel, Oladunjoye, Adeolu Olufunso, Olagunju, Andrew T., Olana, Diriba Dereje, Bali, Ahmed Omar, Otoiu, Adrian, Owolabi, Mayowa O., Padukudru P A, Mahesh, Padron-Monedero, Alicia, Panda-Jonas, Songhomitra, Pandi-Perumal, Seithikurippu R., Pardhan, Shahina, Eun-Kee, Park, Patel, Jay, Paudel, Uttam, Pawar, Shrikant, Toroudi, Hamidreza Pazoki, Peden, Amy E., Pedersini, Paolo, Pereira, Marcos, Pesudovs, Konrad, Petcu, Ionela-Roxana, Pham, Tom, Phillips, Michael R., Piracha, Zahra Zahid, Polinder, Suzanne, Qattea, Ibrahim, Rafiee, Ata, Raghav, Pankaja, Aziz Rahman, Muhammad, Rahman, Mosiur, Rahmani, Amir Masoud, Rahmanian, Vahid, Ramazanu, Sheena, Rani, Usha, Raru, Temam Beshir, Rashidi, Mohammad-Mahdi, Rastogi, Prateek, Rasul, Azad, Ratan, Zubair Ahmed, Rawassizadeh, Reza, Rezaei, Maryam, Rezaei, Nazila, Rezaeian, Mohsen, Riaz, Muhammad, Rickard, Jennifer, Roberts, Nicholas L.S., Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Ronfani, Luca, Roy, Bedanta, Manjula, S., Chandan, S.N., Sabour, Siamak, Reza Saeb, Mohammad, Saeed, Umar, Safi, Sare, Sahebkar, Amirhossein, Sahiledengle, Biniyam, Ali Sahraian, Mohammad, Salamati, Payman, Sanabria, Juan, Nadeem Saqib, Muhammad Arif, Sarikhani, Yaser, Sarveazad, Arash, Sattin, Davide, Saya, Ganesh Kumar, Schwebel, David C., Seboka, Binyam Tariku, Seidu, Abdul-Aziz, Seylani, Allen, Shah, Pritik A., Shahbandi, Ataollah, Shaheen, Amira A., Shaikh, Masood Ali, Shanawaz, Mohd, Sharew, Nigussie Tadesse, Sharifi, Azam, Sharma, Neeraj, Sharma, Vishal, Shashamo, Bereket Beyene, Sheidaei, Ali, Sheikhi, Rahim Ali, Shen, Jiabin, Shetty, Adithi, Shetty, B. Suresh Kumar, Shiri, Rahman, Shorofi, Seyed Afshin, Shrestha, Roman, Sidamo, Negussie Boti, Silva, Luís Manuel Lopes Rodrigues, Simegn, Wudneh, Singh, Jasvinder A., Singh, Surjit, Singh, Ambrish, Skryabin, Valentin Yurievich, Skryabina, Anna Aleksandrovna, Sleet, David A., Socea, Bogdan, Solomon, Yonatan, Song, Yi, Sotoudeh, Houman, Sousa, Raul A.R. C., Stanaway, Jeffrey D., Stein, Dan J., Steiropoulos, Paschalis, Stokes, Mark A., Subedi, Narayan, Sun, Jing, Tabarés-Seisdedos, Rafael, Soodejani, Moslem Taheri, Tampa, Mircea, Tan, Ker-Kan, Tariqujjaman, M.d., Tarkang, Elvis Enowbeyang, Tat, Nathan Y., Tefera, Yibekal Manaye, Thapar, Rekha, Ticoalu, Jansje Henny Vera, Tripathy, Jaya Prasad, Car, Lorainne Tudor, Tufa, Derara Girma, Ullah, Sana, Ullah, Irfan, Umapathi, Krishna Kishore, Upadhyay, Era, Tahbaz, Sahel Valadan, Valdez, Pascual R., Varthya, Shoban Babu, Veroux, Massimiliano, Vervoort, Dominique, Violante, Francesco S., Vlassov, Vasily, Vo, Bay, Waheed, Yasir, Wang, Yanzhong, Wassie, Gizachew Tadesse, Wiangkham, Taweewat, Wilkerson, Caroline, Wolde, Asrat Arja, Xiao, Hong, Yano, Yuichiro, Yaya, Sanni, Ye, Pengpeng, Yip, Paul, Yonemoto, Naohiro, Younis, Mustafa Z., Yu, Chuanhua, Zaki, Leila, Zastrozhin, Michael, Zhang, Yunquan, Zhang, Zhi-Jiang, Zodpey, Sanjay, Naghavi, Mohsen, Larijani, Bagher, and Farzadfar, Farshad

Published
2024
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