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525 results on '"Pavithra, M."'

8. Illuminating Agriculture: Crafting a Strategy IoT-Based Architectural Design for Future Growth

Author

Pavithra, M., Duraisamy, S., Shankar, R., 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, Kaiser, M. Shamim, editor, Xie, Juanying, editor, and Rathore, Vijay Singh, editor

Published
2024
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12. Implementing the WHO Labour Care Guide to reduce the use of Caesarean section in four hospitals in India: protocol and statistical analysis plan for a pragmatic, stepped-wedge, cluster-randomized pilot trial

Author

Vogel, Joshua P., Pingray, Veronica, Althabe, Fernando, Gibbons, Luz, Berrueta, Mabel, Pujar, Yeshita, Somannavar, Manjunath, Vernekar, Sunil S., Ciganda, Alvaro, Rodriguez, Rocio, Welling, Saraswati A., Revankar, Amit, Bendigeri, Savitri, Kumar, Jayashree Ashok, Patil, Shruti Bhavi, Karinagannanavar, Aravind, Anteen, Raveendra R., Pavithra, M. R., Shetty, Shukla, Latha, B., Megha, H. M., Gaddi, Suman S., Chikkagowdra, Shaila, Raghavendra, Bellara, Armari, Elizabeth, Scott, Nick, Eddy, Katherine, Homer, Caroline S. E., and Goudar, Shivaprasad S.

Published
2023
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13. Protein Dynamics to Define and Refine Disordered Protein Ensembles

Author

Naullage, Pavithra M, Haghighatlari, Mojtaba, Namini, Ashley, Teixeira, João MC, Li, Jie, Zhang, Oufan, Gradinaru, Claudiu C, Forman-Kay, Julie D, and Head-Gordon, Teresa

Subjects
Neurosciences, Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Fluorescence Resonance Energy Transfer, Intrinsically Disordered Proteins, Nuclear Magnetic Resonance, Biomolecular, Protein Conformation, Protein Folding, src Homology Domains, Physical Sciences, Chemical Sciences, Engineering
Abstract

Intrinsically disordered proteins and unfolded proteins have fluctuating conformational ensembles that are fundamental to their biological function and impact protein folding, stability, and misfolding. Despite the importance of protein dynamics and conformational sampling, time-dependent data types are not fully exploited when defining and refining disordered protein ensembles. Here we introduce a computational framework using an elastic network model and normal-mode displacements to generate a dynamic disordered ensemble consistent with NMR-derived dynamics parameters, including transverse R2 relaxation rates and Lipari-Szabo order parameters (S2 values). We illustrate our approach using the unfolded state of the drkN SH3 domain to show that the dynamical ensembles give better agreement than a static ensemble for a wide range of experimental validation data including NMR chemical shifts, J-couplings, nuclear Overhauser effects, paramagnetic relaxation enhancements, residual dipolar couplings, hydrodynamic radii, single-molecule fluorescence Förster resonance energy transfer, and small-angle X-ray scattering.

Published
2022

23. Effective Plant Leaf Disease Detection for Farmers

Author

Jose, Deepa, Pavithra, M., Sasipriya, S., Satya Venkata Santosh, M., Cartegana, Jhonatan Fabricio Meza, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, 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, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Marriwala, N., editor, Tripathi, C. C., editor, Jain, Shruti, editor, and Mathapathi, Shivakumar, editor

Published
2022
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28. Key Object Classification for Action Recognition in Tennis Using Cognitive Mask RCNN

Author

Kanimozhi, S., Mala, T., Kaviya, A., Pavithra, M., Vishali, P., 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, Saraswat, Mukesh, editor, Roy, Sarbani, editor, Chowdhury, Chandreyee, editor, and Gandomi, Amir H., editor

Published
2022
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29. Multi-Function Digital Mirror Using Raspberry Pi with IOT

Author

Sneha, A. S., Sonica, J., Pavithra, M., Luqman, Syed, Rohith, S., Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, 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, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Kumar, Amit, editor, Senatore, Sabrina, editor, and Gunjan, Vinit Kumar, editor

Published
2022
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33. Muscular Dystrophy

Author

Kumar, T. Ananth, primary, Rajmohan, R., additional, Pavithra, M., additional, and Balamurugan, S., additional

Published
2022
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35. Tuberculosis

Author

Kumar, T. Ananth, primary, Rajmohan, R., additional, Pavithra, M., additional, and Balamurugan, S., additional

Published
2022
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46. Accelerating graph analytics

Author

Divya, P., primary, Jayalakshmi, S., additional, Pavithra, M., additional, Rajmohan, R., additional, Ananth Kumar, T., additional, and Khalaf, Osamah Ibrahim, additional

Published
2022
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47. Why graph analytics?

Author

Padmapriya, N., primary, Kumaratharan, N., additional, Rajmohan, R., additional, Ananth Kumar, T., additional, Pavithra, M., additional, and Dinesh Jackson Samuel, R., additional

Published
2022
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48. Resilience of hospital and allied infrastructure during pandemic and post pandemic periods for maternal health care of pregnant women and infants in Tamil Nadu, India - A counterfactual analysis.

Author

Kandaswamy Paramasivan, Ashwin Prakash, Sarthak Gupta, Bhairav Phukan, Pavithra M R, and Balaji Venugopal

Subjects
Medicine, Science
Abstract

COVID-19 has impacted the healthcare system across the globe. The study will span three pandemic waves in 2020, 2021, and 2022. The goal is to learn how the pandemic affects antenatal care (ANC) and emergency delivery care for pregnant women in Tamil Nadu, India, and how medical services respond. The study employs counterfactual analysis to evaluate the causal impact of the pandemic. A feedforward in combination with a simple auto-regressive neural network (AR-Net) is used to predict the daily number of calls for ambulance services (CAS). Three categories of the daily CAS count between January 2016 and December 2022 are utilised. The total CAS includes all types of medical emergencies; the second group pertains to planned ANC for high-risk pregnant women and the third group comprises CAS from pregnant women for medical emergencies. The second wave's infection and mortality rates were up to six times higher than the first. The phases in wave-II, post-wave-II, wave-III, and post-wave-III experienced a significant increase in both total IFT (inter-facility transfer) and total non-IFT calls covering all emergencies relative to the counterfactual, as evidenced by reported effect sizes of 1 and a range of 0.65 to 0.85, respectively. This highlights overwhelmed health services. In Tamil Nadu, neither emergency prenatal care nor planned prenatal care was affected by the pandemic. In contrast, the increase in actual emergency-related IFT calls during wave-II, post-wave-II, wave-III, and post-wave-III was 62%, 160%, 141%, and 165%, respectively, relative to the counterfactual. During the same time periods, the mean daily CAS related to prenatal care increased by 47%, 51%, 38%, and 38%, respectively, compared to pre-pandemic levels. The expansion of ambulance services and increased awareness of these services during wave II and the ensuing phases of Covid-19 pandemic have enhanced emergency care delivery for all, including obstetric and neonatal cohorts.

Published
2023
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