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6. A Study on Customer Preference Towards Coupon – Code Based Promotional Activities in Various Selected Fields with Special Reference to Coimbatore City

Author

Anitha, D., Kavitha, N., Krupa, M. Esther, Priyanka, B., Hemaprasanna, S., 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, Alareeni, Bahaaeddin, editor, and Hamdan, Allam, editor

Published
2024
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9. Improving Problem-Solving Skills through Technology Assisted Collaborative Learning in a First Year Engineering Mathematics Course

Author

Anitha, D. and Kavitha, D.

Abstract

Purpose: The purpose of this research study is to explore simple collaborative technique for teaching mathematics and thus improving the problem solving skills of the students. Better pedagogic activities are required to motivate the students to perceive mathematics as a subject that stimulates problem-solving skills required for engineers. Design/Methodology/Approach: This paper presents a research study on the application of technology-supported collaborative learning in improving the problem-solving skills of first-year engineering students in a mathematics course. The experiment was conducted in a mathematics course "Engineering Calculus" with 286 first-year engineering students in two groups: experimental group (N = 60) and controlled group (N = 226). The academic performance of the students was measured and analyzed with statistical techniques. Findings: From the results obtained, it was found that the academic performance of the experimental group was better than the controlled group. Also, interest shown by the students in the topic that dealt with collaborative learning was more than in other topics taught using conventional teaching methods. Research Limitations/Implications: The teachers are required to find effective pedagogical activities to improve the problem-solving skills in mathematics. The research work proposes a collaborative method in mathematics for attaining higher cognitive level in an entry level engineering course. The limitation of this study lies in group formation techniques and the grading policy which deals only with individual assessment scores. Practical Implications: Practice of collaborative learning is made easy with simple technology. A clear strategy for the conduct of collaborative learning sessions has been presented. The solutions recommended are practically feasible and does not require any special infrastructure or specific training. Social Implications: Using technology in mathematics teaching may not be very easy for all teachers. Especially, for an undergraduate engineering fresher, mathematics may not be a very easy task. This work shall bridge the gap with simple technology-assisted collaborative learning. The teachers need not spend too much time and effort in learning technology for mathematics teaching. The effect of this learning is significant in terms of the performance and satisfaction evaluation. Originality/Value: This work presents a systematic implementation of collaborative learning that shall result in improved problem-solving skills and engaging learning sessions. The statistical analysis methods and the visualization of obtained results shall help in understanding the implications of the presented work. Practice of collaborative learning is made easy with simple technology. The solutions recommended are practically feasible and does not require any special infrastructure or specific training.

Published
2023
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11. Bacteriological profile and antibiotic susceptibility pattern of secondary peritonitis in correlation to the anatomical site of gastrointestinal perforation: A Retrospective Study

Author

Anitha D, Bharathi R, and Krishna Prasad

Subjects
Intra-abdominal infection, Poly-microbial infection, Empirical antibiotics,Multidrug resistant Bacteria, Gastro intestinal perforation., Medicine
Abstract

Background The mortality and morbidity due to secondary peritonitis is high. Timely surgical intervention of secondary peritonitis due to Gastrointestinal (GI) perforation and appropriate empirical antibiotic therapy are prerequisites for a good outcome in these cases. The study aims to investigate the bacterial profile and the antibiotic susceptibility pattern of bacterial isolates in cases of secondary peritonitis following GI perforation and the correlation of bacterial spectrum with the different anatomical sites of GI perforation. Methods The retrospective study includes 44 patients operated on for secondary peritonitis following GI perforation between Jan 2019 to March 2020. The peritoneal fluid samples from these patients were subjected to bacterial culture and sensitivity. The bacterial isolates were identified by standard microbiological techniques and antibiotic susceptibility pattern was determined by the Kirby Bauer disk diffusion method and E test. The clinical data about the anatomical site of gastrointestinal perforation was collected from the medical records of these patients and were analyzed. Results Out of 44 peritoneal fluid samples obtained from secondary peritonitis cases due to GI perforation, 58 bacterial strains were isolated. The majority of the bacterial isolates were Gram-negative bacilli; Escherichia coli 31/58 (53.44%), Klebsiella pneumoniae 16/58 (27.58%) and Enterobacter spp. 5/58 (8.62%). The Gram-positive bacteria accounted for 10.33% of the infections; Enterococcus spp. 4/58 (6.89%) and Staphylococcus aureus 2/58 (3.44%). The most common anatomical site of GI perforation was Appendix in 63% of the cases, followed by the stomach in 16% and the small intestine in 14% of the study cases. Meropenem was found to have the highest susceptibility rate among all Gram-negative bacteria. Vancomycin and Linezolid were effective in all localizations with a sensitivity rate of 100%. Conclusion By evaluating the microbial flora and its antibiotic susceptibility pattern in relation to the location of perforation and microbial flora, we recommend Meropenem and Linezolid as the choice for empirical antibiotic therapy in cases of secondary peritonitis following GI perforation.

Published
2024

20. AIM-CARE: Autonomous intelligent modular charging apparatus for roadway electrics.

Author

Chattopadhyay, Suranyo, Muduli, Ayan, Anitha, D., Gupta, Shivansh, Adarsh, T. S., Sundriyal, Nitin, Vishuram, Pradeep, and Bajaj, Mohit

Subjects
ELECTRIC vehicle charging stations, CONVOLUTIONAL neural networks, AUTOMOBILE size, DEGREES of freedom, ELECTRIC charge
Abstract

AIM-CARE introduces a groundbreaking solution aimed at transforming the electric vehicle (EV) charging landscape through a cutting-edge approach centered on Automatic EV Charging. Prioritizing versatility, user-friendliness, and accessibility, AIM-CARE aims to redefine the EV charging experience. This research focuses on the development of an Automated Charging Station featuring a 5 Degree of Freedom (DoF) Robotic Manipulator. The integration of this robotic manipulator with a visual detection system enables autonomous charging capabilities. The system not only identifies potential obstacles but also adapts its actions based on the size of the vehicle, enabling simultaneous charging of multiple vehicles through the deployment of a robotic arm. A camera, equipped with Convolutional Neural Networks (CNNs), is utilized to precisely locate the charging port on the vehicle. To showcase feasibility within defined constraints, the research adopts a miniaturization approach, employing a scaled Electric Vehicle model and a custom charging port adhering to industry standards. This forward-looking automated charging system is designed to facilitate efficient charging and seamless data communication between the robotic charging unit and Electric Vehicles. Ultimately, AIM-CARE presents an optimal solution for future electric vehicles, paving the way for a streamlined and autonomous charging process. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Intelligent Wireless Sensor Networks for Precision Agriculture

Author

Anitha, D., Shelke, Vaibhav D., Anupama, C. G., Rajan, Pooja, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Dash, Subhransu Sekhar, editor, Lakshmi, C., editor, Das, Swagatam, editor, and Panigrahi, Bijaya Ketan, editor

Published
2020
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26. Communicationless Adaptive Control Strategy for Effective Reactive Power Sharing in a Grid-Independent AC Microgrid

Author

Suchitra D, Anitha D, George Fernandez S, Zuhair Muhammed Alaas, Ziad M. Ali, and Shady H. E. Abdel Aleem

Subjects
reactive power sharing, communicationless control, grid-independent microgrid, equivalent impedance, virtual impedance, General Works
Abstract

The microgrid (MG) ensures a reliable power supply as it can work in a grid-independent mode. This mode requires a coordinated control strategy among distributed generators (DGs). One major challenge in a grid-independent MG is the reactive power-sharing issue. The reactive power sharing is affected by the mismatch of feeder impedance and private loads. This study thus proposed a proportionate reactive power-sharing scheme in a grid-independent mode by mathematically computing the equivalent impedance without the need for communication lines. A mathematical formula is derived to compute the equivalent impedance as a function of the total power output of DG and the power fed to the feeder. Based on the computed equivalent impedance, the virtual impedance is added to each feeder. The inclusion of virtual impedance in each line compensates the mismatch in feeder impedance and private loads providing accurate reactive power sharing among DGs. MATLAB Simulink was used to verify the effectiveness of the proposed control strategy. Furthermore, the real-time OPAL-RT simulator was used to verify the results.

Published
2022
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28. Low-Power Process-Insensitive Operational Amplifier Design

Author

Anitha, D., Manjunatha Chari, K., Satish Kumar, P., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Satapathy, Suresh Chandra, editor, Bhateja, Vikrant, editor, Somanah, Radhakhrishna, editor, Yang, Xin-She, editor, and Senkerik, Roman, editor

Published
2019
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32. Beyond Limits: Envisioning Sustainable Design and Production Ecosystems

Author

Anitha D., Awasthi Ankita, Dwivedi Shashi Prakash, Kumar Ravinder, Pahwa Shilpa, Rajalakshmi B., and Alkhafaji Mohammed Ayad

Subjects
Environmental sciences, GE1-350
Abstract

The use of sustainability is of utmost importance when it comes to tackling the environmental issues that our global community is currently confronting, ranging from climate change to the depletion of natural resources. The publication titled “Beyond Limits: Envisioning Sustainable Design and Production Ecosystems” delves into the imperative need for a paradigm shift in order to effectively address the aforementioned difficulties. This paradigm shift necessitates a break from conventional, sequential frameworks towards circular and regenerative systems, signifying a fundamental shift in our design and production methodologies. The concept of sustainable design and production ecosystems is intrinsically characterised by its complex nature. The dimensions encompassed by these practises are broad, encompassing the reimagining of design processes, the careful selection of materials, the optimisation of production procedures, the rethinking of supply chain management, and the consideration of end-of-life scenarios. Each of these characteristics plays a crucial role in establishing a comprehensive and enduring environment. The fundamental objective of this notion is to develop a state of peaceful coexistence between human activities and the ecosystems of the earth. In addition to the reduction of harm, it promotes active engagement in activities that contribute to the overall welfare of our environment. By exploring this paradigm-shifting perspective, we establish the foundation for a forthcoming era in which human pursuits harmoniously integrate with the ecological systems of the Earth, ensuring a sustainable and wealthy global community for future generations.

Published
2023
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33. Marburg and Ebola Virus Infections Elicit a Complex, Muted Inflammatory State in Bats

Author

Anitha D. Jayaprakash, Adam J. Ronk, Abhishek N. Prasad, Michael F. Covington, Kathryn R. Stein, Toni M. Schwarz, Saboor Hekmaty, Karla A. Fenton, Thomas W. Geisbert, Christopher F. Basler, Alexander Bukreyev, and Ravi Sachidanandam

Subjects
bat, transcriptome, Ebola virus, Marburg virus, inflammation, Microbiology, QR1-502
Abstract

The Marburg and Ebola filoviruses cause a severe, often fatal, disease in humans and nonhuman primates but have only subclinical effects in bats, including Egyptian rousettes, which are a natural reservoir of Marburg virus. A fundamental question is why these viruses are highly pathogenic in humans but fail to cause disease in bats. To address this question, we infected one cohort of Egyptian rousette bats with Marburg virus and another cohort with Ebola virus and harvested multiple tissues for mRNA expression analysis. While virus transcripts were found primarily in the liver, principal component analysis (PCA) revealed coordinated changes across multiple tissues. Gene signatures in kidney and liver pointed at induction of vasodilation, reduction in coagulation, and changes in the regulation of iron metabolism. Signatures of immune response detected in spleen and liver indicated a robust anti-inflammatory state signified by macrophages in the M2 state and an active T cell response. The evolutionary divergence between bats and humans of many responsive genes might provide a framework for understanding the differing outcomes upon infection by filoviruses. In this study, we outline multiple interconnected pathways that respond to infection by MARV and EBOV, providing insights into the complexity of the mechanisms that enable bats to resist the disease caused by filoviral infections. The results have the potential to aid in the development of new strategies to effectively mitigate and treat the disease caused by these viruses in humans.

Published
2023
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35. Hybrid anomaly detection: Leveraging autoencoder for feature learning and random forest neural network for discriminative classification.

Author

Maheswari, M., Anitha, D., Sharma, Aditi, Kaur, Kiranpreet, Balamurugan, V., Garikapati, Bindu, Dineshkumar, R., and Karunakaran, P.

Abstract

Anomaly detection, a critical aspect of data analysis and cybersecurity, aims to identify unusual patterns that deviate from the expected norm. In this study, we propose a hybrid approach that combines the strengths of Autoencoder neural networks and Multiclass Support Vector Machines (SVM) for robust anomaly detection. The Autoencoder is utilized for feature learning and extraction, capturing intricate patterns in the data, while the Multiclass SVM provides a discriminative classification mechanism to distinguish anomalies from normal patterns. Specifically, the Autoencoder is trained on normal data to acquire a compact and efficient representation of the underlying patterns, with the reconstruction errors serving as indicative measures of anomalies. Concurrently, a Multiclass SVM is trained to classify instances into multiple classes, including an anomaly class. The anomaly scores from the Autoencoder and the decision function of the Multiclass SVM, along with that of the Random Forest Neural Network (AE-RFNN), are combined, leveraging their complementary strengths. A thresholding mechanism is then employed to classify instances as normal or anomalous based on the combined scores. The performance of the hybrid model is evaluated using standard metrics such as precision, recall, F1-score, and the area under the Receiver Operating Characteristic (ROC) curve. The proposed hybrid anomaly detection approach demonstrates effectiveness in capturing complex patterns and discerning anomalies across diverse datasets. Additionally, the model offers flexibility for adaptation to evolving data distributions. This study contributes to the advancement of anomaly detection methodologies by presenting a hybrid solution that combines feature learning and discriminative classification for improved accuracy and generalization. [ABSTRACT FROM AUTHOR]

Published
2024
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38. YES1 amplification is a mechanism of acquired resistance to EGFR inhibitors identified by transposon mutagenesis and clinical genomics

Author

Fan, Pang-Dian, Narzisi, Giuseppe, Jayaprakash, Anitha D., Venturini, Elisa, Robine, Nicolas, Smibert, Peter, Germer, Soren, Yu, Helena A., Jordan, Emmet J., Paik, Paul K., Janjigian, Yelena Y., Chaft, Jamie E., Wang, Lu, Jungbluth, Achim A., Middha, Sumit, Spraggon, Lee, Qiao, Huan, Lovly, Christine M., Kris, Mark G., Riely, Gregory J., Politi, Katerina, Varmus, Harold, and Ladanyi, Marc

Published
2018

40. Wear behavior of glass fiber reinforced composite with nanoparticles of Al2O3 through artificial neural network.

Author

Khan, Mohd Abraar Ali, Anitha, D., and Balguri, Praveen Kumar

Subjects
*FIBROUS composites, *MECHANICAL wear, *WEAR resistance, *NANOPARTICLES, *ALUMINUM oxide, *GLASS fibers
Abstract

This research investigates the wear behavior of glass fiber reinforced with nanoparticles of Al2O3 through an experimental analysis using artificial neural network (ANN). Three different percentages of Al2O3 reinforcement, namely 1%, 3%, and 5%, were used to research the wear properties of the prepared material. The wear experiment was planned using Taguchi design, with composition (C), load (L), speed (Vs), and distance of sliding (Ds) as input parameters, and specific rate of wear (Rw) and friction coefficient (Fc) as output responses. The Taguchi optimization technique was used to optimize the responses. The results show that the wear resistance and friction coefficient of the composite increased with increasing percentage of Al2O3 reinforcement. The Taguchi optimization technique was effective in optimizing the input parameters, and the ANN model developed to predict the responses showed higher accuracy. The ANN model was able to predict the wear properties of the composite with high precision, indicating that it could be used to optimize the wear behavior of similar composites. Overall, the study provides valuable insights into the wear behavior of glass fiber reinforced with nanoparticles of Al2O3 and highlights the effectiveness of Taguchi optimization and ANN modelling in predicting the wear properties of composite materials. The findings of this research could be useful in developing more durable and wear-resistant materials for various industrial applications, including aerospace, automotive, and biomedical industries. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Transposon mutagenesis in Mycobacterium kansasii links a small RNA gene to colony morphology and biofilm formation and identifies 9,885 intragenic insertions that do not compromise colony outgrowth

Author

William C. Budell, Gabrielle A. Germain, Niklas Janisch, Zaid McKie‐Krisberg, Anitha D. Jayaprakash, Andrew E. Resnick, and Luis E. N. Quadri

Subjects
biofilm, Galleria mellonella, gene essentiality, Mycobacterium kansasii, nontuberculous mycobacteria, small noncoding RNA, Microbiology, QR1-502
Abstract

Abstract Mycobacterium kansasii (Mk) is a resilient opportunistic human pathogen that causes tuberculosis‐like chronic pulmonary disease and mortality stemming from comorbidities and treatment failure. The standard treatment of Mk infections requires costly, long‐term, multidrug courses with adverse side effects. The emergence of drug‐resistant isolates further complicates the already challenging drug therapy regimens and threatens to compromise the future control of Mk infections. Despite the increasingly recognized global burden of Mk infections, the biology of this opportunistic pathogen remains essentially unexplored. In particular, studies reporting gene function or generation of defined mutants are scarce. Moreover, no transposon (Tn) mutagenesis tool has been validated for use in Mk, a situation limiting the repertoire of genetic approaches available to accelerate the dissection of gene function and the generation of gene knockout mutants in this poorly characterized pathogen. In this study, we validated the functionality of a powerful Tn mutagenesis tool in Mk and used this tool in conjunction with a forward genetic screen to establish a previously unrecognized role of a conserved mycobacterial small RNA gene of unknown function in colony morphology features and biofilm formation. We also combined Tn mutagenesis with next‐generation sequencing to identify 12,071 Tn insertions that do not compromise viability in vitro. Finally, we demonstrated the susceptibility of the Galleria mellonella larva to Mk, setting the stage for further exploration of this simple and economical infection model system to the study of this pathogen.

Published
2020
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47. Fruit, vegetable, and legume intake, and cardiovascular disease and deaths in 18 countries (PURE): a prospective cohort study

Author

Diaz, R, Orlandini, A, Linetsky, B, Toscanelli, S, Casaccia, G, Cuneo, JM Maini, Rahman, O, Yusuf, R, Azad, AK, Rabbani, KA, Cherry, HM, Mannan, A, Hassan, I, Talukdar, AT, Tooheen, RB, Khan, MU, Sintaha, M, Choudhury, T, Haque, R, Parvin, S, Avezum, A, Oliveira, GB, Marcilio, CS, Mattos, AC, Teo, K, Yusuf, S, Dejesus, J, Agapay, D, Tongana, T, Solano, R, Kay, I, Trottier, S, Rimac, J, Elsheikh, W, Heldman, L, Ramezani, E, Dagenais, G, Poirier, P, Turbide, G, Auger, D, De Bluts, A LeBlanc, Proulx, MC, Cayer, M, Bonneville, N, Lear, S, Gasevic, D, Corber, E, de Jong, V, Vukmirovich, I, Wielgosz, A, Fodor, G, Pipe, A, Shane, A, Lanas, F, Seron, P, Martinez, S, Valdebenito, A, Oliveros, M, Wei, Li, Lisheng, Liu, Chunming, Chen, Xingyu, Wang, Wenhua, Zhao, Hongye, Zhang, Xuan, Jia, Bo, Hu, Yi, Sun, Jian, Bo, Xiuwen, Zhao, Xiaohong, Chang, Tao, Chen, Hui, Chen, Qing, Deng, Xiaoru, Cheng, Xinye, He, Jian, Li, Juan, Li, Xu, Liu, Bing, Ren, Wei, Wang, Yang, Wang, Jun, Yang, Yi, Zhai, Manlu, Zhu, Fanghong, Lu, Jianfang, Wu, Yindong, Li, Yan, Hou, Liangqing, Zhang, Baoxia, Guo, Xiaoyang, Liao, Shiying, Zhang, Rongwen, Bian, Xiuzhen, Tian, Dong, Li, Di, Chen, Jianguo, Wu, Yize, Xiao, Tianlu, Liu, Peng, Zhang, Changlin, Dong, Ning, Li, Xiaolan, Ma, Yuqing, Yang, Rensheng, Lei, Minfan, Fu, Jing, He, Yu, Liu, Xiaojie, Xing, Qiang, Zhou, Lopez-Jaramillo, P, Lopez, PA Camacho, Garcia, R, Jurado, LJA, Gómez-Arbeláez, D, Arguello, JF, Dueñas, R, Silva, S, Pradilla, LP, Ramirez, F, Molina, DI, Cure-Cure, C, Perez, M, Hernandez, E, Arcos, E, Fernandez, S, Narvaez, C, Paez, J, Sotomayor, A, Garcia, H, Sanchez, G, David, T, Rico, A, Mony, P, Vaz, M, Bharathi, A V, Swaminathan, S, Kurpad, K Shankar AV, Jayachitra, KG, Kumar, N, Hospital, HAL, Mohan, V, Deepa, M, Parthiban, K, Anitha, M, Hemavathy, S, Rahulashankiruthiyayan, T, Anitha, D, Sridevi, K, Gupta, R, Panwar, RB, Mohan, I, Rastogi, P, Rastogi, S, Bhargava, R, Kumar, R, Thakur, J S, Patro, B, Lakshmi, PVM, Mahajan, R, Chaudary, P, Kutty, V Raman, Vijayakumar, K, Ajayan, K, Rajasree, G, Renjini, AR, Deepu, A, Sandhya, B, Asha, S, Soumya, HS, Kelishadi, R, Bahonar, A, Mohammadifard, N, Heidari, H, Yusoff, K, Ismail, TST, Ng, KK, Devi, A, Nasir, NM, Yasin, MM, Miskan, M, Rahman, EA, Arsad, MKM, Ariffin, F, Razak, SA, Majid, FA, Bakar, NA, Yacob, MY, Zainon, N, Salleh, R, Ramli, MKA, Halim, NA, Norlizan, SR, Ghazali, NM, Arshad, MN, Razali, R, Ali, S, Othman, HR, Hafar, CWJCW, Pit, A, Danuri, N, Basir, F, Zahari, SNA, Abdullah, H, Arippin, MA, Zakaria, NA, Noorhassim, I, Hasni, MJ, Azmi, MT, Zaleha, MI, Hazdi, KY, Rizam, AR, Sazman, W, Azman, A, Khatib, R, Khammash, U, Khatib, A, Giacaman, R, Iqbal, R, Afridi, A, Khawaja, R, Raza, A, Kazmi, K, Zatonski, W, Szuba, A, Zatonska, K, Ilow, R, Ferus, M, Regulska-Ilow, B, Rózanska, D, Wolyniec, M, Alkamel, Ali, M, Kruger, M A, Voster, H H, Schutte, A E, Wentzel-Viljoen, E, Eloff, FC, de Ridder, H, Moss, H, Potgieter, J, Roux, AA, Watson, M, de Wet, G, Olckers, A, Jerling, JC, Pieters, M, Hoekstra, T, Puoane, T, Igumbor, E, Tsolekile, L, Sanders, D, Naidoo, P, Steyn, N, Peer, N, Mayosi, B, Rayner, B, Lambert, V, Levitt, N, Kolbe-Alexander, T, Ntyintyane, L, Hughes, G, Swart, R, Fourie, J, Muzigaba, M, Xapa, S, Gobile, N, Ndayi, K, Jwili, B, Ndibaza, K, Egbujie, B, Rosengren, A, Boström, K Bengtsson, Gustavsson, A, Andreasson, M, Snällman, M, Wirdemann, L, Oguz, A, Imeryuz, N, Altuntas, Y, Gulec, S, Temizhan, A, Karsidag, K, Calik, KBT, Akalin, AAK, Caklili, OT, Keskinler, MV, Erbakan, AN, Yusufali, AM, Almahmeed, W, Swidan, H, Darwish, EA, Hashemi, ARA, Al-Khaja, N, Muscat-Baron, JM, Ahmed, SH, Mamdouh, TM, Darwish, WM, Abdelmotagali, MHS, Awed, SA Omer, Movahedi, GA, Hussain, F, Al Shaibani, H, Gharabou, RIM, Youssef, DF, Nawati, AZS, Salah, ZAR Abu, Abdalla, RFE, Al Shuwaihi, SM, Al Omairi, MA, Cadigal, OD, Alejandrino, R.S., Chifamba, J, Gwaunza, L, Terera, G, Mahachi, C, Murambiwa, P, Machiweni, T, Mapanga, R, Miller, Victoria, Mente, Andrew, Dehghan, Mahshid, Rangarajan, Sumathy, Zhang, Xiaohe, Swaminathan, Sumathi, Dagenais, Gilles, Gupta, Rajeev, Mohan, Viswanathan, Lear, Scott, Bangdiwala, Shrikant I, Schutte, Aletta E, Wentzel-Viljoen, Edelweiss, Avezum, Alvaro, Altuntas, Yuksel, Yusoff, Khalid, Ismail, Noorhassim, Peer, Nasheeta, Chifamba, Jephat, Diaz, Rafael, Rahman, Omar, Mohammadifard, Noushin, Lana, Fernando, Zatonska, Katarzyna, Wielgosz, Andreas, Yusufali, Afzalhussein, Iqbal, Romaina, Lopez-Jaramillo, Patricio, Khatib, Rasha, Rosengren, Annika, Li, Wei, Liu, Jiankang, Liu, Xiaoyun, Yin, Lu, Teo, Koon, Anand, Sonia, and Yusuf, Salim

Published
2017
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48. Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE): a prospective cohort study

Author

Diaz, R, Orlandini, A, Linetsky, B, Toscanelli, S, Casaccia, G, Cuneo, JM Maini, Rahman, O, Yusuf, R, Azad, AK, Rabbani, KA, Cherry, HM, Mannan, A, Hassan, I, Talukdar, AT, Tooheen, RB, Khan, MU, Sintaha, M, Choudhury, T, Haque, R, Parvin, S, Avezum, A, Oliveira, GB, Marcilio, CS, Mattos, AC, Teo, K, Yusuf, S, Dejesus, J, Agapay, D, Tongana, T, Solano, R, Kay, I, Trottier, S, Rimac, J, Elsheikh, W, Heldman, L, Ramezani, E, Dagenais, G, Poirier, P, Turbide, G, Auger, D, De Bluts, A LeBlanc, Proulx, MC, Cayer, M, Bonneville, N, Lear, S, Gasevic, D, Corber, E, de Jong, V, Vukmirovich, I, Wielgosz, A, Fodor, G, Pipe, A, Shane, A, Lanas, F, Seron, P, Martinez, S, Valdebenito, A, Oliveros, M, Wei, Li, Lisheng, Liu, Chunming, Chen, Xingyu, Wang, Wenhua, Zhao, Hongye, Zhang, Xuan, Jia, Bo, Hu, Yi, Sun, Jian, Bo, Xiuwen, Zhao, Xiaohong, Chang, Tao, Chen, Hui, Chen, Qing, Deng, Xiaoru, Cheng, Xinye, He, Jian, Li, Juan, Li, Xu, Liu, Bing, Ren, Wei, Wang, Yang, Wang, Jun, Yang, Yi, Zhai, Manlu, Zhu, Fanghong, Lu, Jianfang, Wu, Yindong, Li, Yan, Hou, Liangqing, Zhang, Baoxia, Guo, Xiaoyang, Liao, Shiying, Zhang, Rongwen, Bian, Xiuzhen, Tian, Dong, Li, Di, Chen, Jianguo, Wu, Yize, Xiao, Tianlu, Liu, Peng, Zhang, Changlin, Dong, Ning, Li, Xiaolan, Ma, Yuqing, Yang, Rensheng, Lei, Minfan, Fu, Jing, He, Yu, Liu, Xiaojie, Xing, Qiang, Zhou, Lopez-Jaramillo, P, Lopez, PA Camacho, Garcia, R, Jurado, LJA, Gómez-Arbeláez, D, Arguello, JF, Dueñas, R, Silva, S, Pradilla, LP, Ramirez, F, Molina, DI, Cure-Cure, C, Perez, M, Hernandez, E, Arcos, E, Fernandez, S, Narvaez, C, Paez, J, Sotomayor, A, Garcia, H, Sanchez, G, David, T, Rico, A, Mony, P, Vaz, M, Bharathi, A V, Swaminathan, S, Kurpad, K Shankar AV, Jayachitra, KG, Kumar, N, Hospital, HAL, Mohan, V, Deepa, M, Parthiban, K, Anitha, M, Hemavathy, S, Rahulashankiruthiyayan, T, Anitha, D, Sridevi, K, Gupta, R, Panwar, RB, Mohan, I, Rastogi, P, Rastogi, S, Bhargava, R, Kumar, R, Thakur, J S, Patro, B, Lakshmi, PVM, Mahajan, R, Chaudary, P, Kutty, V Raman, Vijayakumar, K, Ajayan, K, Rajasree, G, Renjini, AR, Deepu, A, Sandhya, B, Asha, S, Soumya, HS, Kelishadi, R, Bahonar, A, Mohammadifard, N, Heidari, H, Yusoff, K, Ismail, TST, Ng, KK, Devi, A, Nasir, NM, Yasin, MM, Miskan, M, Rahman, EA, Arsad, MKM, Ariffin, F, Razak, SA, Majid, FA, Bakar, NA, Yacob, MY, Zainon, N, Salleh, R, Ramli, MKA, Halim, NA, Norlizan, SR, Ghazali, NM, Arshad, MN, Razali, R, Ali, S, Othman, HR, Hafar, CWJCW, Pit, A, Danuri, N, Basir, F, Zahari, SNA, Abdullah, H, Arippin, MA, Zakaria, NA, Noorhassim, I, Hasni, MJ, Azmi, MT, Zaleha, MI, Hazdi, KY, Rizam, AR, Sazman, W, Azman, A, Khatib, R, Khammash, U, Khatib, A, Giacaman, R, Iqbal, R, Afridi, A, Khawaja, R, Raza, A, Kazmi, K, Zatonski, W, Szuba, A, Zatonska, K, Ilow, R, Ferus, M, Regulska-Ilow, B, Rózanska, D, Wolyniec, M, Alkamel, Ali, M, Kruger, M A, Voster, H H, Schutte, A E, Wentzel-Viljoen, E, Eloff, FC, de Ridder, H, Moss, H, Potgieter, J, Roux, AA, Watson, M, de Wet, G, Olckers, A, Jerling, JC, Pieters, M, Hoekstra, T, Puoane, T, Igumbor, E, Tsolekile, L, Sanders, D, Naidoo, P, Steyn, N, Peer, N, Mayosi, B, Rayner, B, Lambert, V, Levitt, N, Kolbe-Alexander, T, Ntyintyane, L, Hughes, G, Swart, R, Fourie, J, Muzigaba, M, Xapa, S, Gobile, N, Ndayi, K, Jwili, B, Ndibaza, K, Egbujie, B, Rosengren, A, Boström, K Bengtsson, Gustavsson, A, Andreasson, M, Snällman, M, Wirdemann, L, Oguz, A, Imeryuz, N, Altuntas, Y, Gulec, S, Temizhan, A, Karsidag, K, Calik, KBT, Akalin, AAK, Caklili, OT, Keskinler, MV, Erbakan, AN, Yusufali, AM, Almahmeed, W, Swidan, H, Darwish, EA, Hashemi, ARA, Al-Khaja, N, Muscat-Baron, JM, Ahmed, SH, Mamdouh, TM, Darwish, WM, Abdelmotagali, MHS, Awed, SA Omer, Movahedi, GA, Hussain, F, Al Shaibani, H, Gharabou, RIM, Youssef, DF, Nawati, AZS, Salah, ZAR Abu, Abdalla, RFE, Al Shuwaihi, SM, Al Omairi, MA, Cadigal, OD, Alejandrino, R.S., Chifamba, J, Gwaunza, L, Terera, G, Mahachi, C, Murambiwa, P, Machiweni, T, Mapanga, R, Dehghan, Mahshid, Mente, Andrew, Zhang, Xiaohe, Swaminathan, Sumathi, Li, Wei, Mohan, Viswanathan, Iqbal, Romaina, Kumar, Rajesh, Wentzel-Viljoen, Edelweiss, Rosengren, Annika, Amma, Leela Itty, Avezum, Alvaro, Chifamba, Jephat, Diaz, Rafael, Khatib, Rasha, Lear, Scott, Lopez-Jaramillo, Patricio, Liu, Xiaoyun, Gupta, Rajeev, Mohammadifard, Noushin, Gao, Nan, Oguz, Aytekin, Ramli, Anis Safura, Seron, Pamela, Sun, Yi, Szuba, Andrzej, Tsolekile, Lungiswa, Wielgosz, Andreas, Yusuf, Rita, Hussein Yusufali, Afzal, Teo, Koon K, Rangarajan, Sumathy, Dagenais, Gilles, Bangdiwala, Shrikant I, Islam, Shofiqul, Anand, Sonia S, and Yusuf, Salim

Published
2017
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49. Association of dietary nutrients with blood lipids and blood pressure in 18 countries: a cross-sectional analysis from the PURE study

Author

Yusuf, S, Rangarajan, S, Teo, K K, Chow, C K, O'Donnell, M, Mente, A, Leong, D, Smyth, A, Joseph, P, Merchant, A, Islam, S, Zhang, M, Hu, W, Ramasundarahettige, C, Wong, G, Bangdiwala, S, Dyal, L, Casanova, A, Dehghan, M, Lewis, G, Aliberti, A, Arshad, A, Reyes, A, Zaki, A, Lewis, B, Zhang, B, Agapay, D, Hari, D, Milazzo, E, Ramezani, E, Hussain, F, Shifaly, F, McAlpine, G, Kay, I, Lindeman, J, Rimac, J, Swallow, J, Heldman, L, Mushtaha, M(a), Mushtaha, M(o), Trottier, M, Riggi, M, Aoucheva, N, Kandy, N, Mackie, P, Solano, R, Chin, S, Ramacham, S, Shahrook, S, Trottier, S, Tongana, T, ElSheikh, W, Iyengar, Y, McQueen, M, Hall, K, Keys, J, Wang, X, Keneth, J, Devanath, A, Diaz, R, Orlandini, A, Linetsky, B, Toscanelli, S, Casaccia, G, Cuneo, JM Maini, Rahman, O, Yusuf, R, Azad, AK, Rabbani, KA, Cherry, HM, Mannan, A, Hassan, I, Talukdar, AT, Tooheen, RB, Khan, MU, Sintaha, M, Choudhury, T, Haque, R, Parvin, S, Avezum, A, Oliveira, GB, Marcilio, CS, Mattos, AC, Teo, K, Dejesus, J, Elsheikh, W, Dagenais, G, Poirier, P, Turbide, G, Auger, D, De Bluts, A LeBlanc, Proulx, MC, Cayer, M, Bonneville, N, Lear, S, Gasevic, D, Corber, E, de Jong, V, Vukmirovich, I, Wielgosz, A, Fodor, G, Pipe, A, Shane, A, Lanas, F, Seron, P, Martinez, S, Valdebenito, A, Oliveros, M, Wei, Li, Lisheng, Liu, Chunming, Chen, Xingyu, Wang, Wenhua, Zhao, Hongye, Zhang, Xuan, Jia, Bo, Hu, Yi, Sun, Jian, Bo, Xiuwen, Zhao, Xiaohong, Chang, Tao, Chen, Hui, Chen, Qing, Deng, Xiaoru, Cheng, Xinye, He, Jian, Li, Juan, Li, Xu, Liu, Bing, Ren, Wei, Wang, Yang, Wang, Jun, Yang, Yi, Zhai, Manlu, Zhu, Fanghong, Lu, Jianfang, Wu, Yindong, Li, Yan, Hou, Liangqing, Zhang, Baoxia, Guo, Xiaoyang, Liao, Shiying, Zhang, Rongwen, Bian, Xiuzhen, Tian, Dong, Li, Di, Chen, Jianguo, Wu, Yize, Xiao, Tianlu, Liu, Peng, Zhang, Changlin, Dong, Ning, Li, Xiaolan, Ma, Yuqing, Yang, Rensheng, Lei, Minfan, Fu, Jing, He, Yu, Liu, Xiaojie, Xing, Qiang, Zhou, Lopez-Jaramillo, P, Lopez, PA Camacho, Garcia, R, Jurado, LJA, Gómez-Arbeláez, D, Arguello, JF, Dueñas, R, Silva, S, Pradilla, LP, Ramirez, F, Molina, DI, Cure-Cure, C, Perez, M, Hernandez, E, Arcos, E, Fernandez, S, Narvaez, C, Paez, J, Sotomayor, A, Garcia, H, Sanchez, G, David, T, Rico, A, Mony, P, Vaz, M, Bharathi, A V, Swaminathan, S, Kurpad, K Shankar AV, Jayachitra, KG, Kumar, N, Hospital, HAL, Mohan, V, Deepa, M, Parthiban, K, Anitha, M, Hemavathy, S, Rahulashankiruthiyayan, T, Anitha, D, Sridevi, K, Gupta, R, Panwar, RB, Mohan, I, Rastogi, P, Rastogi, S, Bhargava, R, Kumar, R, Thakur, J S, Patro, B, Lakshmi, PVM, Mahajan, R, Chaudary, P, Kutty, V Raman, Vijayakumar, K, Ajayan, K, Rajasree, G, Renjini, AR, Deepu, A, Sandhya, B, Asha, S, Soumya, HS, Kelishadi, R, Bahonar, A, Mohammadifard, N, Heidari, H, Yusoff, K, Ismail, TST, Ng, KK, Devi, A, Nasir, NM, Yasin, MM, Miskan, M, Rahman, EA, Arsad, MKM, Ariffin, F, Razak, SA, Majid, FA, Bakar, NA, Yacob, MY, Zainon, N, Salleh, R, Ramli, MKA, Halim, NA, Norlizan, SR, Ghazali, NM, Arshad, MN, Razali, R, Ali, S, Othman, HR, Hafar, CWJCW, Pit, A, Danuri, N, Basir, F, Zahari, SNA, Abdullah, H, Arippin, MA, Zakaria, NA, Noorhassim, I, Hasni, MJ, Azmi, MT, Zaleha, MI, Hazdi, KY, Rizam, AR, Sazman, W, Azman, A, Khatib, R, Khammash, U, Khatib, A, Giacaman, R, Iqbal, R, Afridi, A, Khawaja, R, Raza, A, Kazmi, K, Dans, A, Co, HU, Sanchez, JT, Pudol, L, Zamora-Pudol, C, Palileo-Villanueva, LAM, Aquino, MR, Abaquin, C, Pudol, SL, Cabral, ML, Zatonski, W, Szuba, A, Zatonska, K, Ilow, R, Ferus, M, Regulska-Ilow, B, Rózanska, D, Wolyniec, M, AlHabib, KF, Hersi, A, Kashour, T, Alfaleh, H, Alshamiri, M, Altaradi, HB, Alnobani, O, Bafart, A, Alkamel, N, Ali, M, Abdulrahman, M, Nouri, R, Kruger, A, Voster, H H, Schutte, A E, Wentzel-Viljoen, E, Eloff, FC, de Ridder, H, Moss, H, Potgieter, J, Roux, AA, Watson, M, de Wet, G, Olckers, A, Jerling, JC, Pieters, M, Hoekstra, T, Puoane, T, Igumbor, E, Tsolekile, L, Sanders, D, Naidoo, P, Steyn, N, Peer, N, Mayosi, B, Rayner, B, Lambert, V, Levitt, N, Kolbe-Alexander, T, Ntyintyane, L, Hughes, G, Swart, R, Fourie, J, Muzigaba, M, Xapa, S, Gobile, N, Ndayi, K, Jwili, B, Ndibaza, K, Egbujie, B, Rosengren, A, Bengtsson Boström, K, Gustavsson, A, Andreasson, M, Snällman, M, Wirdemann, L, Yeates, K, Sleeth, J, Kilonzo, K, Oguz, A, Imeryuz, N, Altuntas, Y, Gulec, S, Temizhan, A, Karsidag, K, Calik, KBT, Akalin, AAK, Caklili, OT, Keskinler, MV, Erbakan, AN, Yusufali, AM, Almahmeed, W, Swidan, H, Darwish, EA, Hashemi, ARA, Al-Khaja, N, Muscat-Baron, JM, Ahmed, SH, Mamdouh, TM, Darwish, WM, Abdelmotagali, MHS, Awed, SA Omer, Movahedi, GA, Al Shaibani, H, Gharabou, RIM, Youssef, DF, Nawati, AZS, Salah, ZAR Abu, Abdalla, RFE, Al Shuwaihi, SM, Al Omairi, MA, Cadigal, OD, Alejandrino, R.S., Chifamba, J, Gwaunza, L, Terera, G, Mahachi, C, Murambiwa, P, Machiweni, T, Mapanga, R, Mente, Andrew, Dehghan, Mahshid, Rangarajan, Sumathy, McQueen, Matthew, Dagenais, Gilles, Wielgosz, Andreas, Lear, Scott, Li, Wei, Chen, Hui, Wang, Yang, Diaz, Rafael, Avezum, Alvaro, Lopez-Jaramillo, Patricio, Seron, Pamela, Kumar, Rajesh, Gupta, Rajeev, Mohan, Viswanathan, Swaminathan, Sumathi, Kutty, Raman, Zatonska, Katarzyna, Iqbal, Romaina, Yusuf, Rita, Mohammadifard, Noushin, Khatib, Rasha, Nasir, Nafiza Mat, Ismail, Noorhassim, Oguz, Aytekin, Rosengren, Annika, Yusufali, Afzalhussein, Wentzel-Viljoen, Edelweiss, Puoane, Thandi, Chifamba, Jephat, Teo, Koon, Anand, Sonia S, and Yusuf, Salim

Published
2017
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50. Availability and affordability of blood pressure-lowering medicines and the effect on blood pressure control in high-income, middle-income, and low-income countries: an analysis of the PURE study data

Author

Yusuf, S, Rangarajan, S, Teo, K K, Chow, C K, O'Donnell, M, Mente, A, Leong, D, Smyth, A, Joseph, P, Islam, S, Zhang, M, Hu, W, Ramasundarahettige, C, Wong, G, Dayal, L, Casanova, A, Dehghan, M, Lewis, G, Aliberti, A, Reyes, A, Zaki, A, Lewis, B, Zhang, B, Agapay, D, Hari, D, Milazzo, E, Ramezani, E, Hussain, F, Shifaly, F, Kay, I, Rimac, J, Swallow, J, Heldman, L, Mushtaha, M(a), Mushtaha, M(o), Trottier, M, Aoucheva, N, Kandy, N, Mackie, P, Solano, R, Chin, S, Ramacham, S, Shahrook, S, Trottier, S, Tongana, T, ElSheikh, W, Lindeman, J, McQueen, M, Hall, K, Keys, J, Wang, X, Keneth, J, Devanath, A, Diaz, R, Orlandini, A, Linetsky, B, Toscanelli, S, Casaccia, G, Maini Cuneo, JM, Rahman, O, Yusuf, R, Azad, AK, Rabbani, KA, Cherry, HM, Mannan, A, Hassan, I, Talukdar, AT, Tooheen, RB, Khan, MU, Sintaha, M, Choudhury, T, Haque, R, Parvin, S, Avezum, A, Oliveira, GB, Marcilio, CS, Mattos, AC, Teo, K, Dejesus, J, Elsheikh, W, Dagenais, G, Poirier, P, Turbide, G, Auger, D, De Bluts, A LeBlanc, Proulx, MC, Cayer, M, Bonneville, N, Lear, S, Gasevic, D, Corber, E, de Jong, V, Vukmirovich, I, Wielgosz, A, Fodor, G, Pipe, A, Shane, A, Lanas, F, Seron, P, Martinez, S, Valdebenito, A, Oliveros, M, Wei, Li, Lisheng, Liu, Chunming, Chen, Xingyu, Wang, Wenhua, Zhao, Hongye, Zhang, JiaXuan, Bo, Hu, Yi, Sun, Jian, Bo, Xiuwen, Zhao, Xiaohong, Chang, Tao, Chen, Hui, Chen, Qing, Deng, Xiaoru, Cheng, Xinye, He, Jian, Li, Juan, Li, Xu, Liu, Bing, Ren, Wei, Wang, Yang, Wang, Jun, Yang, Yi, Zhai, Manlu, Zhu, Fanghong, Lu, Jianfang, Wu, Yindong, Li, Yan, Hou, Liangqing, Zhang, Baoxia, Guo, Xiaoyang, Liao, Shiying, Zhang, BianRongwen, TianXiuzhen, Dong, Li, Di, Chen, Jianguo, Wu, Yize, Xiao, Tianlu, Liu, Peng, Zhang, Changlin, Dong, Ning, Li, Xiaolan, Ma, Yuqing, Yang, Rensheng, Lei, Minfan, Fu, Jing, He, Yu, Liu, Xiaojie, Xing, Qiang, Zhou, Lopez-Jaramillo, P, Lopez, PA Camacho, Garcia, R, Jurado, LJA, Gómez-Arbeláez, D, Arguello, JF, Dueñas, R, Silva, S, Pradilla, LP, Ramirez, F, Molina, DI, Cure-Cure, C, Perez, M, Hernandez, E, Arcos, E, Fernandez, S, Narvaez, C, Paez, J, Sotomayor, A, Garcia, H, Sanchez, G, David, T, Rico, A, Mony, P, Vaz, M, Bharathi, A V, Swaminathan, S, Shankar, K, Kurpad, AV, Jayachitra, KG, Kumar, N, Hospital, HAL, Mohan, V, Deepa, M, Parthiban, K, Anitha, M, Hemavathy, S, Rahulashankiruthiyayan, T, Anitha, D, Sridevi, K, Gupta, R, Panwar, RB, Mohan, I, Rastogi, P, Rastogi, S, Bhargava, R, Kumar, R, Thakur, J S, Patro, B, Lakshmi, PVM, Mahajan, R, Chaudary, P, Kutty, V Raman, Vijayakumar, K, Ajayan, K, Rajasree, G, Renjini, AR, Deepu, A, Sandhya, B, Asha, S, Soumya, HS, Kelishadi, R, Bahonar, A, Mohammadifard, N, Heidari, H, Yusoff, K, Ismail, TST, Ng, KK, Devi, A, Nasir, NM, Yasin, MM, Miskan, M, Rahman, EA, Arsad, MKM, Ariffin, F, Razak, SA, Majid, FA, Bakar, NA, Yacob, MY, Zainon, N, Salleh, R, Ramli, MKA, Halim, NA, Norlizan, SR, Ghazali, NM, Arshad, MN, Razali, R, Ali, S, Othman, HR, Hafar, CWJCW, Pit, A, Danuri, N, Basir, F, Zahari, SNA, Abdullah, H, Arippin, MA, Zakaria, NA, Noorhassim, I, Hasni, MJ, Azmi, MT, Zaleha, MI, Hazdi, KY, Rizam, AR, Sazman, W, Azman, A, Khatib, R, Khammash, U, Khatib, A, Giacaman, R, Iqbal, R, Afridi, A, Khawaja, R, Raza, A, Kazmi, K, Dans, A, Co, HU, Sanchez, JT, Pudol, L, Zamora-Pudol, C, Palileo-Villanueva, LAM, Aquino, MR, Abaquin, C, Pudol, SL, Cabral, ML, Zatonski, W, Szuba, A, Zatonska, K, Ilow#, R, Ferus, M, Regulska-Ilow, B, Różańska, D, Wolyniec, M, AlHabib, KF, Hersi, A, Kashour, T, Alfaleh, H, Alshamiri, M, Altaradi, HB, Alnobani, O, Bafart, A, Alkamel, N, Ali, M, Abdulrahman, M, Nouri, R, Kruger, A, Voster, H H, Schutte, A E, Wentzel-Viljoen, E, Eloff, FC, de Ridder, H, Moss, H, Potgieter, J, Roux, AA, Watson, M, de Wet, G, Olckers, A, Jerling, JC, Pieters, M, Hoekstra, T, Puoane, T, Igumbor, E, Tsolekile, L, Sanders, D, Naidoo, P, Steyn, N, Peer, N, Mayosi, B, Rayner, B, Lambert, V, Levitt, N, Kolbe-Alexander, T, Ntyintyane, L, Hughes, G, Swart, R, Fourie, J, Muzigaba, M, Xapa, S, Gobile, N, Ndayi, K, Jwili, B, Ndibaza, K, Egbujie, B, Rosengren, A, Boström, K Bengtsson, Lindblad, U, Langkilde, P, Gustavsson, A, Andreasson, M, Snällman, M, Wirdemann, L, Pettersson, K, Moberg, E, Yeates, K, Sleeth, J, Kilonzo, K, Oguz, A, Akalin, AAK, Calik, KBT, Imeryuz, N, Temizhan, A, Alphan, E, Gunes, E, Sur, H, Karsidag, K, Gulec, S, Altuntas, Y, Yusufali, AM, Almahmeed, W, Swidan, H, Darwish, EA, Hashemi, ARA, Al-Khaja, N, Muscat-Baron, JM, Ahmed, SH, Mamdouh, TM, Darwish, WM, Abdelmotagali, MHS, Awed, SA Omer, Movahedi, GA, Shaibani, H Al, Gharabou, RIM, Youssef, DF, Nawati, AZS, Salah, ZAR Abu, Abdalla, RFE, Shuwaihi, SM Al, Omairi, MA Al, Cadigal, OD, Alejandrino, R.S., Chifamba, J, Gwaunza, L, Terera, G, Mahachi, C, Murambiwa, P, Machiweni, T, Mapanga, R, Attaei, Marjan W, Khatib, Rasha, McKee, Martin, Lear, Scott, Dagenais, Gilles, Igumbor, Ehimario U, AlHabib, Khalid F, Kaur, Manmeet, Kruger, Lanthe, Teo, Koon, Lanas, Fernando, Yusoff, Khalid, Oguz, Aytekin, Gupta, Rajeev, Yusufali, Afzalhussein M, Bahonar, Ahmad, Kutty, Raman, Rosengren, Annika, Mohan, Viswanathan, Avezum, Alvaro, Yusuf, Rita, Szuba, Andrzej, Rangarajan, Sumathy, Chow, Clara, and Yusuf, Salim

Published
2017
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