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1,737 results on '"Singh, Gautam"'

1. Slot State Space Models

Author

Jiang, Jindong, Deng, Fei, Singh, Gautam, Lee, Minseung, and Ahn, Sungjin

Subjects
Computer Science - Artificial Intelligence
Abstract

Recent State Space Models (SSMs) such as S4, S5, and Mamba have shown remarkable computational benefits in long-range temporal dependency modeling. However, in many sequence modeling problems, the underlying process is inherently modular and it is of interest to have inductive biases that mimic this modular structure. In this paper, we introduce SlotSSMs, a novel framework for incorporating independent mechanisms into SSMs to preserve or encourage separation of information. Unlike conventional SSMs that maintain a monolithic state vector, SlotSSMs maintains the state as a collection of multiple vectors called slots. Crucially, the state transitions are performed independently per slot with sparse interactions across slots implemented via the bottleneck of self-attention. In experiments, we evaluate our model in object-centric video understanding, 3D visual reasoning, and video prediction tasks, which involve modeling multiple objects and their long-range temporal dependencies. We find that our proposed design offers substantial performance gains over existing sequence modeling methods. Project page is available at https://slotssms.github.io/

Published
2024

4. Parallelized Spatiotemporal Binding

Author

Singh, Gautam, Wang, Yue, Yang, Jiawei, Ivanovic, Boris, Ahn, Sungjin, Pavone, Marco, and Che, Tong

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

While modern best practices advocate for scalable architectures that support long-range interactions, object-centric models are yet to fully embrace these architectures. In particular, existing object-centric models for handling sequential inputs, due to their reliance on RNN-based implementation, show poor stability and capacity and are slow to train on long sequences. We introduce Parallelizable Spatiotemporal Binder or PSB, the first temporally-parallelizable slot learning architecture for sequential inputs. Unlike conventional RNN-based approaches, PSB produces object-centric representations, known as slots, for all time-steps in parallel. This is achieved by refining the initial slots across all time-steps through a fixed number of layers equipped with causal attention. By capitalizing on the parallelism induced by our architecture, the proposed model exhibits a significant boost in efficiency. In experiments, we test PSB extensively as an encoder within an auto-encoding framework paired with a wide variety of decoder options. Compared to the state-of-the-art, our architecture demonstrates stable training on longer sequences, achieves parallelization that results in a 60% increase in training speed, and yields performance that is on par with or better on unsupervised 2D and 3D object-centric scene decomposition and understanding., Comment: See project page at https://parallel-st-binder.github.io

Published
2024

6. Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models

Author

Kim, Yeongbin, Singh, Gautam, Park, Junyeong, Gulcehre, Caglar, and Ahn, Sungjin

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

Systematic compositionality, or the ability to adapt to novel situations by creating a mental model of the world using reusable pieces of knowledge, remains a significant challenge in machine learning. While there has been considerable progress in the language domain, efforts towards systematic visual imagination, or envisioning the dynamical implications of a visual observation, are in their infancy. We introduce the Systematic Visual Imagination Benchmark (SVIB), the first benchmark designed to address this problem head-on. SVIB offers a novel framework for a minimal world modeling problem, where models are evaluated based on their ability to generate one-step image-to-image transformations under a latent world dynamics. The framework provides benefits such as the possibility to jointly optimize for systematic perception and imagination, a range of difficulty levels, and the ability to control the fraction of possible factor combinations used during training. We provide a comprehensive evaluation of various baseline models on SVIB, offering insight into the current state-of-the-art in systematic visual imagination. We hope that this benchmark will help advance visual systematic compositionality., Comment: Published as a conference paper at NeurIPS 2023. The first two authors contributed equally. To download the benchmark, visit https://systematic-visual-imagination.github.io

Published
2023

7. Neuroprotective Effect of Ashtanga Ghrita on Spatial Learning and Memory in Scopolamine-Induced Amnesia in Rat Model

Author

Yashika Singh and DevNath Singh Gautam

Subjects
barnes maze model, dementia, goghrita, medhya rasayana, nootropics, Other systems of medicine, RZ201-999
Abstract

Introduction: Ashtanga Ghrita (AG), Medhya Rasayana (nervine rejuvenator), is used for the treatment of neurodegenerative disorders. The contents of AG specifically act on Medha (intellect), whereas the lipid part, Go Ghrita, serves as a medium for the transfer of active phytoconstituents. Treatment of cognitive disorders associated with Alzheimer’s disease (AD) is to date inadequate in the field of medical science. Nootropic agents such as piracetam are used to improve memory and cognition; however, due to higher side effects, their use has become substantially limited. Methods: AG was administered orally to rat at dose of 48 ml/kg. Piracetam (200 mg/kg of body weight [b.w.], i.p.) was used as a standard nootropic agent, whereas scopolamine (SC, 2 mg/kg, of b.w., i.p.) was used as an amnestic agent. The learning and memory activities of AG were investigated in Charles Foster rat for 21 days, and its effects on learning and memory were examined using Barnes Maze Model. Results: Administration of AG (48 g/kg of b.w., i.p.) significantly (P < 0.05, P < 0.01) decreased transfer latency on day 21 with respect to the disease control group (29.33 ± 15.2 and 54.50 ± 30.69). Rats receiving piracetam showed significant memory improvement compared to SC group (30 ± 5.96). The nootropic effect on rats receiving AG and piracetam individually was significantly comparable (29.33 ± 15.201 and 30 ± 5.96). Conclusion: AG exerts antiamnesic effect in SC-induced rats and can be used in the treatment of memory impairment (dementia) predominantly produced in neurocognitive disorders such as AD.

Published
2024
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8. Context-dependent agricultural intensification pathways to increase rice production in India

Author

Hari Sankar Nayak, Andrew J. McDonald, Virender Kumar, Peter Craufurd, Shantanu Kumar Dubey, Amaresh Kumar Nayak, Chiter Mal Parihar, Panneerselvam Peramaiyan, Shishpal Poonia, Kindie Tesfaye, Ram K. Malik, Anton Urfels, Udham Singh Gautam, and João Vasco Silva

Subjects
Science
Abstract

Abstract Yield gap analysis is used to characterize the untapped production potential of cropping systems. With emerging large-n agronomic datasets and data science methods, pathways for narrowing yield gaps can be identified that provide actionable insights into where and how cropping systems can be sustainably intensified. Here we characterize the contributing factors to rice yield gaps across seven Indian states, with a case study region used to assess the power of intervention targeting. Primary yield constraints in the case study region were nitrogen and irrigation, but scenario analysis suggests modest average yield gains with universal adoption of higher nitrogen rates. When nitrogen limited fields are targeted for practice change (47% of the sample), yield gains are predicted to double. When nitrogen and irrigation co-limitations are targeted (20% of the sample), yield gains more than tripled. Results suggest that analytics-led strategies for crop intensification can generate transformative advances in productivity, profitability, and environmental outcomes.

Published
2024
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9. The Impact of Job Satisfaction on Teacher Mental Health: A Call to Action for Educational Policymakers

Author

Yogendra Kumar Singh and Dev Nath Singh Gautam

Abstract

Job satisfaction significantly impacts teachers' overall well-being and mental health. Research reveals a strong connection between employment status and mental health, with teaching being a particularly stressful profession. The COVID-19 pandemic exacerbated these challenges, with the shift to online education and limited support causing heightened stress, anxiety, and depression. This study analyses scientific literature exploring the link between job satisfaction and mental health (depression, stress, and anxiety) in teachers. By examining relevant articles in major databases like Web of Science, PSYNDEX, PsycINFO, MEDLINE, EMBASE, and Google Scholar, the research identifies numerous sociodemographic and institutional factors contributing to teachers' mental health struggles, including workload, teaching experience, job satisfaction, gender, and the nature of online education. The findings highlight the urgent need for educational policymakers to develop policies prioritizing teacher well-being, especially during times of crisis. This involves addressing factors affecting job satisfaction and implementing strategies to promote mental health support for educators.

Published
2024
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10. Object-Centric Slot Diffusion

Author

Jiang, Jindong, Deng, Fei, Singh, Gautam, and Ahn, Sungjin

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

The recent success of transformer-based image generative models in object-centric learning highlights the importance of powerful image generators for handling complex scenes. However, despite the high expressiveness of diffusion models in image generation, their integration into object-centric learning remains largely unexplored in this domain. In this paper, we explore the feasibility and potential of integrating diffusion models into object-centric learning and investigate the pros and cons of this approach. We introduce Latent Slot Diffusion (LSD), a novel model that serves dual purposes: it is the first object-centric learning model to replace conventional slot decoders with a latent diffusion model conditioned on object slots, and it is also the first unsupervised compositional conditional diffusion model that operates without the need for supervised annotations like text. Through experiments on various object-centric tasks, including the first application of the FFHQ dataset in this field, we demonstrate that LSD significantly outperforms state-of-the-art transformer-based decoders, particularly in more complex scenes, and exhibits superior unsupervised compositional generation quality. In addition, we conduct a preliminary investigation into the integration of pre-trained diffusion models in LSD and demonstrate its effectiveness in real-world image segmentation and generation. Project page is available at https://latentslotdiffusion.github.io, Comment: Accepted to NeurIPS 2023 as a Spotlight paper

Published
2023

11. Oral pyogenic granuloma with calcification

Author

Akancha Singh Gautam, Sneh Mandal, and V. C. Divya

Subjects
calcification, pyogenic granuloma, reactive lesion, surgical excision, Dentistry, RK1-715
Abstract

Rationale: Pyogenic granuloma (PG) is a commonly observed reactive soft-tissue lesion, often arising due to prolonged mild irritation or hormonal fluctuations in the oral cavity. Clinically, PG presents as a lesion with a smooth or lobulated appearance, which can be either sessile or pedunculated, and typically exhibits an hemorrhagic tendency. Very few cases of calcification in a PG have been reported in the past as these rarely exhibit ossification when viewed under a microscope. Patient Concerns: The following report is a case of a PG, that presented as a growth with occasional pain in the right upper back region of a 54 year old female. The patient reported no other concerns. Diagnosis: A provisional diagnosis of PG was given following thorough clinical and radiographic investigations. This was confirmed by a histopathological examination following an excisional biopsy. Intervention: The patient was treated with surgical excision as a part of the excisional biopsy of the lesion. Follow-up for the patient was done after 6 months, and there were no signs or indications of recurrence. Outcomes: The histopathological examination revealed regions of calcification, which are uncommon in PG, in addition to the characteristic hallmarks of proliferating endothelial cells, blood vessels, and inflammatory cells.

Published
2024
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14. Exploring Explainable Machine Learning in Healthcare: Closing the Predictive Accuracy and Clinical Interpretability Gap

Author

Singh, Gautam, Pal, Ashok, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Singh, Yashwant, editor, Singh, Pradeep Kumar, editor, Gonçalves, Paulo J. Sequeira, editor, and Kar, Arpan Kumar, editor

Published
2024
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16. Development of Witricity Based Wireless Power Transmission System

Author

Mishra, Kanhaiya, Kushawaha, Arjun, Chaurasia, Neetigya, Kumar, Sudhanshu, Singh, Gautam Kr., Shahid, Mohammad, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Malik, Hasmat, editor, Mishra, Sukumar, editor, Sood, Y. R., editor, Iqbal, Atif, editor, and Ustun, Taha Selim, editor

Published
2024
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17. Neural Systematic Binder

Author

Singh, Gautam, Kim, Yeongbin, and Ahn, Sungjin

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

The key to high-level cognition is believed to be the ability to systematically manipulate and compose knowledge pieces. While token-like structured knowledge representations are naturally provided in text, it is elusive how to obtain them for unstructured modalities such as scene images. In this paper, we propose a neural mechanism called Neural Systematic Binder or SysBinder for constructing a novel structured representation called Block-Slot Representation. In Block-Slot Representation, object-centric representations known as slots are constructed by composing a set of independent factor representations called blocks, to facilitate systematic generalization. SysBinder obtains this structure in an unsupervised way by alternatingly applying two different binding principles: spatial binding for spatial modularity across the full scene and factor binding for factor modularity within an object. SysBinder is a simple, deterministic, and general-purpose layer that can be applied as a drop-in module in any arbitrary neural network and on any modality. In experiments, we find that SysBinder provides significantly better factor disentanglement within the slots than the conventional object-centric methods, including, for the first time, in visually complex scene images such as CLEVR-Tex. Furthermore, we demonstrate factor-level systematicity in controlled scene generation by decoding unseen factor combinations., Comment: Project Page: https://sites.google.com/view/neural-systematic-binder

Published
2022

19. Impact of environmental efficiency on tourism export under the moderation of inflation: a cross-country analysis

Author

Shailesh Rastogi, Jagjeevan Kanoujiya, Rahul Singh Gautam, and Neha Parashar

Subjects
DEA, tourism, export, environment, efficiency, economic growth, Finance, HG1-9999, Economic theory. Demography, HB1-3840
Abstract

AbstractA country’s tourism sector plays an essential role in the nation’s economy and aids in globalization. With the advanced technological establishments, this sector becomes more promising for economic growth. However, the connection of tourism development to environmental effects cannot be denied. Tourism export is also a recent term in this sector that needs to be explored. Therefore, this study aims to determine the impact of environmental efficiency (EE) on tourism export using the cross-country data of 90 countries for the sample period 2011–2020. The panel data is used for the analysis. The findings suggest that EE adversely affects tourism exports. A negative relationship between the two is also observed under the moderating effect of inflation. It means EE reduces tourism exports under higher inflation. This study notably contributes to existing literature through its unique and novel evidence on the EE and tourism export connection. This study recommends that EE be treated as a critical component of tourism policymaking. Figure A presents the graphical abstract.

Published
2024
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20. Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos

Author

Singh, Gautam, Wu, Yi-Fu, and Ahn, Sungjin

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

Unsupervised object-centric learning aims to represent the modular, compositional, and causal structure of a scene as a set of object representations and thereby promises to resolve many critical limitations of traditional single-vector representations such as poor systematic generalization. Although there have been many remarkable advances in recent years, one of the most critical problems in this direction has been that previous methods work only with simple and synthetic scenes but not with complex and naturalistic images or videos. In this paper, we propose STEVE, an unsupervised model for object-centric learning in videos. Our proposed model makes a significant advancement by demonstrating its effectiveness on various complex and naturalistic videos unprecedented in this line of research. Interestingly, this is achieved by neither adding complexity to the model architecture nor introducing a new objective or weak supervision. Rather, it is achieved by a surprisingly simple architecture that uses a transformer-based image decoder conditioned on slots and the learning objective is simply to reconstruct the observation. Our experiment results on various complex and naturalistic videos show significant improvements compared to the previous state-of-the-art.

Published
2022

25. Illiterate DALL-E Learns to Compose

Author

Singh, Gautam, Deng, Fei, and Ahn, Sungjin

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

Although DALL-E has shown an impressive ability of composition-based systematic generalization in image generation, it requires the dataset of text-image pairs and the compositionality is provided by the text. In contrast, object-centric representation models like the Slot Attention model learn composable representations without the text prompt. However, unlike DALL-E its ability to systematically generalize for zero-shot generation is significantly limited. In this paper, we propose a simple but novel slot-based autoencoding architecture, called SLATE, for combining the best of both worlds: learning object-centric representations that allows systematic generalization in zero-shot image generation without text. As such, this model can also be seen as an illiterate DALL-E model. Unlike the pixel-mixture decoders of existing object-centric representation models, we propose to use the Image GPT decoder conditioned on the slots for capturing complex interactions among the slots and pixels. In experiments, we show that this simple and easy-to-implement architecture not requiring a text prompt achieves significant improvement in in-distribution and out-of-distribution (zero-shot) image generation and qualitatively comparable or better slot-attention structure than the models based on mixture decoders., Comment: Published as a conference paper at ICLR 2022

Published
2021

27. Access to and quality of elective care: a prospective cohort study using hernia surgery as a tracer condition in 83 countries

Author

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

Published
2024
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30. Structured World Belief for Reinforcement Learning in POMDP

Author

Singh, Gautam, Peri, Skand, Kim, Junghyun, Kim, Hyunseok, and Ahn, Sungjin

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

Object-centric world models provide structured representation of the scene and can be an important backbone in reinforcement learning and planning. However, existing approaches suffer in partially-observable environments due to the lack of belief states. In this paper, we propose Structured World Belief, a model for learning and inference of object-centric belief states. Inferred by Sequential Monte Carlo (SMC), our belief states provide multiple object-centric scene hypotheses. To synergize the benefits of SMC particles with object representations, we also propose a new object-centric dynamics model that considers the inductive bias of object permanence. This enables tracking of object states even when they are invisible for a long time. To further facilitate object tracking in this regime, we allow our model to attend flexibly to any spatial location in the image which was restricted in previous models. In experiments, we show that object-centric belief provides a more accurate and robust performance for filtering and generation. Furthermore, we show the efficacy of structured world belief in improving the performance of reinforcement learning, planning and supervised reasoning., Comment: Published in ICML 2021

Published
2021

33. Identification of benzothiazole derived monosaccharides as potent, selective, and orally bioavailable inhibitors of human and mouse galectin-3; a rare example of using a S···O binding interaction for drug design

Author

Liu, Chunjian, Wang, Wei, Feng, Jianxin, Beno, Brett, Raja, Thiruvenkadam, Swidorski, Jacob, Manepalli, Raju K.V.L.P., Vetrichelvan, Muthalagu, Rao Jalagam, Prasada, Nair, Satheesh K., Gupta, Anuradha, Panda, Manoranjan, Ghosh, Kaushik, Kaushikkumar Shukla, Jinal, Sale, Harinath, Shah, Devang, Singh Gautam, Shashyendra, Patel, Dipal, Mathur, Arvind, Ellsworth, Bruce A., Cheng, Dong, and Regueiro-Ren, Alicia

Published
2024
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34. The NHLBI Study on Long-terM OUtcomes after the Multisystem Inflammatory Syndrome In Children (MUSIC): Design and Objectives

Author

Truong, Dongngan T, Trachtenberg, Felicia L, Pearson, Gail D, Dionne, Audrey, Elias, Matthew D, Friedman, Kevin, Hayes, Kerri H, Mahony, Lynn, McCrindle, Brian W, Oster, Matthew E, Pemberton, Victoria, Powell, Andrew J, Russell, Mark W, Shekerdemian, Lara S, Son, Mary Beth, Taylor, Michael, Newburger, Jane W, Investigators, for the MUSIC Study, Giglia, Therese M, McHugh, Kimberly E, Atz, Andrew M, Pletzer, Scott A, Lang, Sean M, Payne, R Mark, Patel, Jyoti K, Pignatelli, Ricardo H, Sexson, Kristen, Lam, Christopher, Dragulescu, Andreea, Young, Rae SM, Gamulka, Beth, Krishnan, Anita, Anderson, Brett R, Farooqi, Kanwal M, Shakti, Divya, Parnell, Aimee S, Osakwe, Onyekachukwu J, Sykes, Michelle C, Morgan, Lerraughn, Owada, Carl Y, Forsha, Daniel, Carr, Michael R, Watanabe, Kae, Portman, Michael A, Dummer, Kristen B, Burns, Jane C, Tremoulet, Adriana H, Sharma, Kavita, Jone, Pei-Ni, Heizer, Michelle Hite Heather, Hasbani, Keren, Srivastava, Shubhika, Mitchell, Elizabeth C, Hebson, Camden L, Szmuszkovicz, Jacqueline R, Wong, Pierre C, Cheng, Andrew L, Votava-Smith, Jodie K, Wang, Shuo, Mohandas, Sindhu, Singh, Gautam K, Aggarwal, Sanjeev, Sanil, Yamuna, Bradford, Tamara T, Muniz, Juan Carlos G, Li, Jennifer S, Campbell, Michael Jay, Handler, Stephanie S, Shea, J Ryan, Hoffman, Timothy M, Franklin, Wayne J, Sabati, Arash A, Nowlen, Todd T, and Chrisant, Maryanne

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Heart Disease, Biomedical Imaging, Clinical Trials and Supportive Activities, Cardiovascular, Clinical Research, Prevention, Pediatric, Patient Safety, Adult, COVID-19, Child, Heart, Humans, Magnetic Resonance Imaging, National Heart, Lung, and Blood Institute (U.S.), SARS-CoV-2, Stroke Volume, Systemic Inflammatory Response Syndrome, United States, Ventricular Function, Left, Young Adult, MUSIC Study Investigators, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundThe Long-terM OUtcomes after the Multisystem Inflammatory Syndrome In Children (MUSIC) study aims to characterize the frequency and time course of acute and long-term cardiac and non-cardiac sequelae in multisystem inflammatory syndrome in children associated with COVID-19 (MIS-C), which are currently poorly understood.MethodsThis multicenter observational cohort study will enroll at least 600 patients

Published
2022

36. Robustifying Sequential Neural Processes

Author

Yoon, Jaesik, Singh, Gautam, and Ahn, Sungjin

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

When tasks change over time, meta-transfer learning seeks to improve the efficiency of learning a new task via both meta-learning and transfer-learning. While the standard attention has been effective in a variety of settings, we question its effectiveness in improving meta-transfer learning since the tasks being learned are dynamic and the amount of context can be substantially smaller. In this paper, using a recently proposed meta-transfer learning model, Sequential Neural Processes (SNP), we first empirically show that it suffers from a similar underfitting problem observed in the functions inferred by Neural Processes. However, we further demonstrate that unlike the meta-learning setting, the standard attention mechanisms are not effective in meta-transfer setting. To resolve, we propose a new attention mechanism, Recurrent Memory Reconstruction (RMR), and demonstrate that providing an imaginary context that is recurrently updated and reconstructed with interaction is crucial in achieving effective attention for meta-transfer learning. Furthermore, incorporating RMR into SNP, we propose Attentive Sequential Neural Processes-RMR (ASNP-RMR) and demonstrate in various tasks that ASNP-RMR significantly outperforms the baselines., Comment: Accepted in ICML 2020

Published
2020

37. Fair Transfer of Multiple Style Attributes in Text

Author

Dabas, Karan, Madan, Nishtha, Arya, Vijay, Mehta, Sameep, Singh, Gautam, and Chakraborty, Tanmoy

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

To preserve anonymity and obfuscate their identity on online platforms users may morph their text and portray themselves as a different gender or demographic. Similarly, a chatbot may need to customize its communication style to improve engagement with its audience. This manner of changing the style of written text has gained significant attention in recent years. Yet these past research works largely cater to the transfer of single style attributes. The disadvantage of focusing on a single style alone is that this often results in target text where other existing style attributes behave unpredictably or are unfairly dominated by the new style. To counteract this behavior, it would be nice to have a style transfer mechanism that can transfer or control multiple styles simultaneously and fairly. Through such an approach, one could obtain obfuscated or written text incorporated with a desired degree of multiple soft styles such as female-quality, politeness, or formalness. In this work, we demonstrate that the transfer of multiple styles cannot be achieved by sequentially performing multiple single-style transfers. This is because each single style-transfer step often reverses or dominates over the style incorporated by a previous transfer step. We then propose a neural network architecture for fairly transferring multiple style attributes in a given text. We test our architecture on the Yelp data set to demonstrate our superior performance as compared to existing one-style transfer steps performed in a sequence.

Published
2020

38. SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition

Author

Lin, Zhixuan, Wu, Yi-Fu, Peri, Skand Vishwanath, Sun, Weihao, Singh, Gautam, Deng, Fei, Jiang, Jindong, and Ahn, Sungjin

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing, Statistics - Machine Learning
Abstract

The ability to decompose complex multi-object scenes into meaningful abstractions like objects is fundamental to achieve higher-level cognition. Previous approaches for unsupervised object-oriented scene representation learning are either based on spatial-attention or scene-mixture approaches and limited in scalability which is a main obstacle towards modeling real-world scenes. In this paper, we propose a generative latent variable model, called SPACE, that provides a unified probabilistic modeling framework that combines the best of spatial-attention and scene-mixture approaches. SPACE can explicitly provide factorized object representations for foreground objects while also decomposing background segments of complex morphology. Previous models are good at either of these, but not both. SPACE also resolves the scalability problems of previous methods by incorporating parallel spatial-attention and thus is applicable to scenes with a large number of objects without performance degradations. We show through experiments on Atari and 3D-Rooms that SPACE achieves the above properties consistently in comparison to SPAIR, IODINE, and GENESIS. Results of our experiments can be found on our project website: https://sites.google.com/view/space-project-page, Comment: Accepted in ICLR 2020

Published
2020

41. Role of Moringa oleifera Lam. in cancer: Phytochemistry and pharmacological insights

Author

Jyoti Singh, Dev Nath Singh Gautam, Simant Sourav, and Rohit Sharma

Subjects
anticancer, Moringa oleifera, nutrition, pharmacological action, phytochemistry, Shigru, Nutrition. Foods and food supply, TX341-641, Food processing and manufacture, TP368-456
Abstract

Abstract Moringa oleifera Lam. (M. oleifera), aka “Shigru,” “mother's best friend,” “miracle tree,” “horseradish tree,” “drumstick tree,” and “oil tree,” native of the sub‐Himalayan region of northern India, belongs to the Moringaceae family. The high nutritional value of M. oleifera makes it suitable for both nutritional and medicinal purposes. Because of its chemical constituents, M. oleifera is used to treat and combat malnutrition, especially in infants and nursing mothers. These days, herbal medicine and its phytocompound derivatives are also being recognized as effective complementary therapies for cancer treatment. So, in this study, M. oleifera is reviewed for its anticancer property. By thoroughly scanning the PubMed, Embase, SinoMed, and China National Knowledge Infrastructure databases, an extensive up‐to‐date report on its ethnomedicinal use, nutritional, phytochemistry, and pharmacotherapeutic potential is done. It has valuable nutrients such as vitamins, proteins, iron, calcium, antioxidants (flavonoids, carotenoids, and phenols) and ascorbic acid. Additionally, it is used as an antioxidant, anti‐inflammatory, antispasmodic, antimicrobial, anticancer, and antidiabetic agent. There are also concrete evidence that this plant's bioactive constituents, numerous extracts have a high biopotential in a number of cancer cells, through its antioxidative, anti‐inflammatory, antiproliferative, and cell cycle arresting properties. This extensive literature review will provide insights into several mechanisms and signaling pathways of its various phytoconstituents that can mitigate the growth of cancer cells in various experimental models, safety and toxicity concerns, and drug–drug interactions.

Published
2023
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47. Sequential Neural Processes

Author

Singh, Gautam, Yoon, Jaesik, Son, Youngsung, and Ahn, Sungjin

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

Neural Processes combine the strengths of neural networks and Gaussian processes to achieve both flexible learning and fast prediction in stochastic processes. However, a large class of problems comprises underlying temporal dependency structures in a sequence of stochastic processes that Neural Processes (NP) do not explicitly consider. In this paper, we propose Sequential Neural Processes (SNP) which incorporates a temporal state-transition model of stochastic processes and thus extends its modeling capabilities to dynamic stochastic processes. In applying SNP to dynamic 3D scene modeling, we introduce the Temporal Generative Query Networks. To our knowledge, this is the first 4D model that can deal with the temporal dynamics of 3D scenes. In experiments, we evaluate the proposed methods in dynamic (non-stationary) regression and 4D scene inference and rendering., Comment: NeurIPS 2019 Spotlight. First two authors contributed equally

Published
2019

49. Knowledge on child rights among private and government school teachers, Pokhara, Kaski district

Author

Indu Sah, Harikala Soti, Laxmi Paudyal, and Nitu Singh Gautam

Subjects
child rights, government school teacher, knowledge, private school teacher, Medicine (General), R5-920
Abstract

Introduction: Children play vital role to the nation’s present and its future. The healthy and educated child of today is the intelligent and active citizen of tomorrow. Hence, the objective of our study was to assess the level of knowledge regarding child rights among teachers, compare the knowledge about child rights in context of private and government school, measure the association between knowledge regarding child rights with selected demographic variables. Methods: This is a cross-sectional comparative study conducted among 200 school teachers 100 each from four government and three private schools of Pokhara using purposive sampling method. Data was collected from November 1 to December 1, 2021. Structured self-administered questionnaire tool on knowledge regarding child rights was prepared by the researcher herself. The data were collected by self-administered tool by researcher herself within 30 minutes. The quantitative data was analyzed using statistical package for social sciences version 20.0 descriptive statistics and non-parametric test were used for analyzing knowledge and association. P-value of

Published
2022
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