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3,391 results on '"Madhu, S."'

13. Viscous Ricci Dark Energy Cosmological Models in Brans-Dicke Theory

Author

Vijayasanthi, M., Chinnappalanaidu, T., and Madhu, S. Srivani

Subjects
General Relativity and Quantum Cosmology
Abstract

The whole article deals with the analysis of the cosmic model of Ruban's space-time in the context of a bulk viscosity impact in the form of Ricci dark energy within the framework Brans-Dicke theory (Brans and Dicke, Phys. Rev. 124, 925 (1961)). We believe that outer space is filled with dark matter and viscous Ricci dark energy (VRDE) under the pressureless situation. The velocity and rate at which the Universe is expanding are presumed to be proportional to the coefficient of total bulk viscosity, is in the form, -- , are the constants. To solve the RDE model's field equations, we utilize the relation among the metric potentials and also the power-law relation among the average scale factor a(t) and scalar field . To examine the evolutionary dynamics of the Universe, we investigate the deceleration parameter(q), jerk parameter(j), EoS parameter , Om(z), stability of the obtained models through the square speed of the sound, wde wde' plane, statefinder parameter planes (r, s) and (q, r) and presented via graphical representation. By the end of the discussion, VRDE model was found to be compatible with the present accelerated expansion of the Universe., Comment: 32 pages, 18 figures

Published
2023

28. Divergent Phenotypes with Same CHRNE Mutation in Two Siblings with Congenital Myasthenic Syndrome

Author

Ankith Naveen, Madhu S Pujar, Ranjitha Revankar, and Shreya Rotti

Subjects
genetics, neuromuscular weakness, pediatric, respiratory insufficiency, Pediatrics, RJ1-570
Abstract

Background: Congenital myasthenic syndrome is a rare inherited neuromuscular disorder resulting in abnormal weakness and fatigue on exertion with onset at or shortly after birth or in early childhood. Clinical Description: A 2-year-old boy presented to us with respiratory failure, having a history of recurrent respiratory tract infections and underlying isolated motor delay. His 7-year-old elder sister had undiagnosed generalized weakness. Management and Outcome: While the index case was being stabilized with mechanical ventilation, his elder sibling was evaluated. Ptosis was noted in her, which improved with neostigmine. Examination and laboratory investigations ruled out other differentials. Clinical exome sequencing was sent which showed homozygous CHRNE ENST00000649488.2.c.1367_1369del. (p.Asn456del) resulting in acetylcholine receptor deficiency. Both siblings were started on oral pyridostigmine and salbutamol, resulting in improvement in muscle weakness over 3 months and 4 months in younger and older sibling, respectively. Conclusion: Recurrent respiratory insufficiency when associated with motor delay may be suggestive of a neuromuscular disorder. Even siblings with the same mutation may have different levels of severity of clinical manifestation.

Published
2024
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30. On the Automated Unruptured Intracranial Aneurysm Segmentation From TOF-MRA Using Deep Learning Techniques

Author

V. A. Anima and Madhu S. Nair

Subjects
Aneurysm, computer-aided detection, time of flight-magnetic resonance angiography, unruptured intracranial aneurysm, dice similarity coefficient, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Aneurysms pose a life-threatening risk due to weakened vessel walls, causing bulging or ballooning in arterial blood vessels. The growth of an aneurysm increases the risk of rupture and consequent bleeding in the brain, leading to a hemorrhagic stroke. Therefore, accurate detection and segmentation of intracranial aneurysms are crucial for treatment planning in patients. Recently, the use of Time of Flight Magnetic Resonance Angiography (TOF-MRA) for automated segmentation of intracranial aneurysms has gained significant importance. This study comprehensively evaluates different automated segmentation methods for unruptured intracranial aneurysms, using the publicly available Aneurysm Detection and Segmentation (ADAM) challenge dataset. The performance and method scalability of these methods is analyzed across state-of-the-art algorithms, and the experimental analysis shows that 3D U-Net architecture outperforms in the segmentation tasks.

Published
2024
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31. KSVM-Based Fast Intra Mode Prediction in HEVC Using Statistical Features and Sparse Autoencoder

Author

Preethi S. Nair and Madhu S. Nair

Subjects
HEVC, intra mode prediction, RMD, SVM, Hu moments, sparse autoencoder, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

High Efficiency Video Coding (HEVC) is designed to deliver a video communication with better quality at reduced bit rate. For intra coding, HEVC employs an effective hierarchical quad tree partitioning and an exhaustive optimal mode search which increases the time complexity. Aiming this issue, we propose a Support Vector Machine (SVM)-based method to effectively predict the intra mode. Compared to the standard HEVC encoder HM-15.0, the proposed method could reduce 57.6% of encoding time at a bit-rate penalty of 3.3% at an average PSNR decline of only around 0.09 dB.

Published
2024
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45. Tracking-by-Self Detection: A Self-supervised Framework for Multiple Animal Tracking

Author

Dev Narayan, C. B., Rahman, Fayaz, Ullah, Mohib, Cheikh, Faouzi Alaya, Imran, Ali Shariq, Coello, Christopher, Nordbø, Øyvind, Santhosh Kumar, G., Nair, Madhu S., Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Maglogiannis, Ilias, editor, Iliadis, Lazaros, editor, MacIntyre, John, editor, and Dominguez, Manuel, editor

Published
2023
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49. Exit Strategy After PCNL

Author

Sundaram, Palaniappan, Ramesh, Mukhilesh, Mishra, Dilip K., Agrawal, Madhu S., Agrawal, Madhu S., editor, Mishra, Dilip K., editor, and Somani, Bhaskar, editor

Published
2022
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