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3,106 results on '"SATPAL"'

102. Management of retinal detachment in block related globe perforation with pneumatic retinopexy

Author

Karandeep Rishi, Pradeep Venkatesh, and Satpal P Garg

Subjects
Humphrey field analyzer, isopropyl unoprostone, microperimetry, retinitis pigmentosa, Color vision, farnsworth-munsell 100 hue test, multiple sclerosis, pattern visual evoked potentials, Amniotic membrane, astigmatism, autografting, fibrin tissue adhesive, pterygium, sutures, Insulin-like growth factor 1, octreotide, platelet derivated growth factor, proliferative vitreoretinopathy, transforming growth factor ß, Intraocular pressure rise, phacoemulsification, risk factors, Bayes′s theorem, initiating treatment, glaucoma, monocular trial, Geleophysic dysplasia, mitomycin C, trabeculectomy, Angle closure glaucoma, iridociliary cyst, laser cyclophotocoagulation, Fibrin glue, secondary IOL implantation, vertical fixation, Glaucoma, intraocular pressure, tonopen, Block-related perforation, pneumatic retinopexy, retinal detachment, Ophthalmology, RE1-994
Abstract

Retinal detachment after ocular perforation related to local anesthesia is a common complication, which is usually associated with a poor prognosis despite complex vitreoretinal surgical procedures. We report a case of 62-year-old male with cataract surgery done 4 weeks back with nasal retinal detachment with a posterior break. Pneumatic retinopexy was performed and laser barrage of the breaks was done the next day when the retina got attached. A vision of 20/30 was achieved at the end of 2 months. To the best of our knowledge, this is a first case report in literature where pneumatic retinopexy was used to manage a retinal detachment caused by block-related perforation.

Published
2013
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107. A Comparison of Security Analysis Methods for Smart Contracts Built on the Ethereum Blockchain

Author

Kushwaha, Satpal Singh, Joshi, Sandeep, 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, Roy, Satyabrata, editor, Sinwar, Deepak, editor, Dey, Nilanjan, editor, Perumal, Thinagaran, editor, and Tavares, João Manuel R. S., editor

Published
2023
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108. Automated Estimation of Left Ventricular Diastolic Chamber Stiffness: Application to Patients with Heart Failure and Aortic Regurgitation

Author

Hasaballa, Abdallah I., Zhao, Debbie, Wang, Vicky Y., Gamage, Thiranja P. Babarenda, Creamer, Stephen A., Quill, Gina M., Ruygrok, Peter N., Arri, Satpal S., Doughty, Robert N., Legget, Malcolm E., Young, Alistair A., Nash, Martyn P., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bernard, Olivier, editor, Clarysse, Patrick, editor, Duchateau, Nicolas, editor, Ohayon, Jacques, editor, and Viallon, Magalie, editor

Published
2023
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109. Global Scenario of Temperate Nuts

Author

Kumar, Amit, Sharma, Nirmal, Sharma, Shivali, Nyorak, Gepu, Satpal, Jaryal, Sonika, Mir, Mohammad Maqbool, Iqbal, Umar, Sindouri, Amarjeet S., Bhat, Khalid M., Mir, Mohammad Maqbool, editor, Rehman, Munib Ur, editor, Iqbal, Umar, editor, and Mir, Shabir Ahmad, editor

Published
2023
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110. Feasibility and acceptability of the use of flash glucose monitoring encountered by Indigenous Australians with type 2 diabetes mellitus: initial experiences from a pilot study

Author

Eer, Audrey Sing Yi, Ho, Rebecca Chia Yee, Hearn, Tracey, Hachem, Mariam, Freund, Megan, Burchill, Luke James, Atkinson-Briggs, Sharon, Singh, Satpal, Eades, Sandra, O’Brien, Richard Charles, Furler, John Stuart, O’Neal, David Norman, Story, David Andrew, Zajac, Jeffrey David, Braat, Sabine, Brown, Alex, Clarke, Phillip, Sinha, Ashim Kumar, McLean, Anna Gerardina, Twigg, Stephen Morris, and Ekinci, Elif Ilhan

Published
2023
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115. Investigating the mechanistic features of ParABS-mediated Vibrio cholerae chromosome 2 segregation

Author

Chodha, Satpal and Hoiczyk, Egbert

Abstract

In all cell types, stable generational viability is dependent on the faithful inheritance of genomic material in daughter cells. This entails replicated DNA being segregated to opposing sides of the cell prior to cell division at mid-cell. In bacteria, a minimal ParABS (partitioning) system is used to correctly localise DNA cargos and is found on the chromosomes of up to 70% of species. A centromere-like site, parS, is bound by the CTP-binding protein, ParB. An ATPase with DNA-binding activity, ParA, acts as a motor protein to drive segregation of the ParB-parS complex, along with the attached DNA cargo. The underlying mechanism has been derived mostly from studies on plasmid Par systems. However, despite recent progress for Par-mediated chromosome segregation, the exact mechanism(s) of their action have yet to be deciphered. Vibrio cholerae, the causative agent of cholera, has two chromosomes, with one using a Par system closely related to those found on plasmids, making it an ideal chromosomal Par model to study. The goal of this thesis was to biochemically characterise the ParABS system of V. cholerae chromosome 2. First, each step in the ATPase cycle of ParA2 was examined and it was shown that there are key differences to plasmid ParA proteins, with an overall faster ATPase cycle likely responsible for driving translocation of a much bigger DNA cargo. Secondly, the formation of the ParA2-ParB2-parS2 complex was investigated, and dynamic self-assembly was seen in the presence of ATP and CXP. Throughout the study, findings were compared with known plasmidal and chromosomal Par systems in order to contribute to a greater understanding of the mechanism(s) of bacterial chromosome segregation.

Published
2020

116. Analysis of longitudinal jaw growth data to study sex differences in timing and intensity of the adolescent growth spurt for normal growth and skeletal discrepancies

Author

Sandhu, Satpal S., Leckie, George, Tilling, Kate, and Hughes, Rachael

Subjects
617.6, Growth Curve Model, Longitudinal data, Jaw growth
Abstract

The upper jaw (maxilla) and the lower jaw (mandible) grow in a downward and forward direction resulting in normal skeletal jaw relationship (Class I) with normal anteroposterior (upper and lower jaw length) and vertical (total face height) growth changes. An excessive or deficient growth in either jaw or both jaws result in skeletal malocclusions (Class II and Class III) characterized by anteroposterior and vertical skeletal discrepancies. Studying timing and intensity of the adolescent growth spurt is essential for the successful correction of skeletal malocclusions. A natural approach to estimation of timing (age at peak growth velocity, APGV) and intensity (peak growth velocity, PGV) involves fitting growth curve models (GCMs) and estimating derivatives. Different linear mixed effects (LME) and nonlinear mixed effects (NLME) GCMs have been successfully applied to height data for estimating timing and intensity of the adolescent growth spurt. However, a systematic review of the literature (database searched until December 31, 2016) showed that studies applying GCMs to longitudinal jaw growth data focused exclusively on conventional polynomial based linear GCM. Furthermore, none of the previous studies simultaneously compared anteroposterior and vertical growth changes between normal skeletal jaw relationship and skeletal malocclusions. In this thesis, I explored the potential of three LME and two NLME GCMs for studying jaw growth data available from the American Association of Orthodontists Foundation (AAOF) Craniofacial Growth Legacy Collection. Data comprised of repeated growth measurements of upper and lower jaw length and total face height on 128 males (mean age 11.67 years, standard deviation 2.92) and 139 females (mean age 11.60 years, standard deviation 2.88) between seven and 18 years of age. The LME models included were the conventional polynomial (CP), fractional polynomial (FP), and restricted cubic spline (RCS). The NLME models studied were the super imposition by translation and rotation (SITAR) and Preece-Baines (PB). The research goal was to first evaluate and compare the fit of LME and NLME GCMs and then apply the best fitting linear or nonlinear GCM to the jaw growth data for studying class differences in the timing and the intensity of adolescent growth spurt between normal skeletal jaw relationship and skeletal malocclusions (i.e., Class I vs Class II, Class I vs Class III, and Class II vs Class III) for males and females. In the first of the three research studies which make up this thesis, a simulation study was conducted to evaluate and compare the performance of popular information criteria (Akaike information criterion, AIC; Bayesian information criterion, BIC) and prediction criteria (measure of variance explained, R2; concordance correlation coefficient, CCC) for selecting the optimal functional form for GCMs. I restricted attention to CP GCM in this study. Balanced and unbalanced data were simulated and analysed for different sample sizes and varying model complexity. Different versions of the restricted maximum likelihood (REML) based AIC and BIC were calculated to study the effect of different penalty adjustments on their performance. The AIC and BIC which included the total number of model parameters in their penalty terms performed at least as well and often better than their counterparts which included only the number of variance-covariance parameters. Both AIC and BIC performed consistently better than the prediction criteria in selecting the true model. Amongst the two information criteria, AIC performed better than BIC especially when sample size was small, and the model involved a complex variance covariance structure. In the second research study, the AIC was then used to compare the fit of covariate adjusted CP, FP, RCS, SITAR and PB GCMs fitted to the upper jaw length, lower jaw length and total face height measurements (hereafter referred as outcomes). Data were analysed separately for males and females. Each GCM was fitted by including all possible individual-specific random effects. In addition to fit to the data, I also compared GCMs in terms of their ability to estimate covariate adjusted growth trajectories (distance, velocity and acceleration) and adolescent growth spurt parameters (APGV and PGV). The PB model failed to converge for any of the three outcomes for both sexes. Results showed that unlike RCS and the SITAR GCMs, both CP and FP GCMs estimate biologically implausible growth trajectories (negative growth velocity). The RCS GCM fitted best to the data (as measured by the AIC) and therefore was selected for answering the clinical research questions in the final research study. In the final research study, the RCS GCM was then used to estimate class differences in growth trajectories and the adolescent growth spurt parameters for males and females. Results showed sex differences in the timing and the intensity of adolescent growth spurt for normal growth and skeletal malocclusions. Females, on average, experience a less intense adolescent growth spurt which occurs almost one and half year earlier than males. Results indicated that an early but less intense growth spurt in the upper jaw length and the lower jaw length is mainly responsible for the development of anteroposterior (upper and lower jaw length) and vertical (total face height) skeletal discrepancies for Class II and Class III skeletal malocclusions. The clinical implications of the research findings are discussed.

Published
2020

124. Cancer Biology

Author

Jain, Aakanchha, primary, Prajapati, Shiv Kumar Prajapati, additional, Jain, Dolly, additional, Jain, Richa, additional, Panda, Amrita Kumari, additional, Bisht, Satpal Singh, additional, and Behera, Santosh Kumar, additional

Published
2023
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125. Blockchain and Smart Grid

Author

Kushwaha, Satpal Singh, primary, Joshi, Sandeep, additional, Bairwa, Amit Kumar, additional, and Chaurasia, Sandeep, additional

Published
2023
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130. List of contributors

Author

Abbas, Saira, primary, Acharya, Padmini Sateesha, additional, Ahmad, Sharjeel, additional, Ahmed, Iftikhar, additional, Aishwarya, Madhavankutty, additional, Ali, Ahmad, additional, Bhardwaj, Snigdha, additional, Bhatia, Sonam, additional, Bisht, Satpal Singh, additional, De Mandal, Surajit, additional, Dewali, Seeta, additional, Divyaa, Nandhakumar, additional, Gajendran, Babu, additional, Govindarajulu, Sathya Narayanan, additional, Ibrahim, Kalibulla Syed, additional, Jayamurali, Dheepthi, additional, Kannan, Ramasamy Palanisamy Bharathi, additional, Karthika, Rangasamy, additional, Kumar, Ankit, additional, Kumar, Kulbhushan, additional, Mandal, Narayan Chandra, additional, Mandal, Sucheta, additional, Manoharan, Nivedita, additional, Miglani, Rashi, additional, Mishra, Rojita, additional, Moniusha, Jayasekar, additional, Mughal, Amina, additional, Mumtaz, Amer, additional, Panda, Amrita Kumari, additional, Parasuraman, Rajeshwari, additional, Parveen, Nagma, additional, Praveen, Rajkumar, additional, Rana, Mahendra, additional, Rawat, Gaurav, additional, Saminathan, Gowsalya, additional, and Varier, Krishnapriya M., additional

Published
2023
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131. List of contributors

Author

Abukhader, Rose, primary, Agrawal, R.S., additional, Ahmad, Iqrar, additional, Ali, Iftikhar, additional, Al-Tawaha, Abdel Razzaq, additional, Anand, Kumar Hegde Biliyaru, additional, Andhare, Prasad, additional, Anjaly Shanker, M., additional, Anshuman, Kena Premshankar, additional, Babu, Karthik Sajith, additional, Baitharu, Iswar, additional, Banerjee, Satarupa, additional, Bansal, Kuldeep, additional, Baranwal, Jaya, additional, Barooah, Mridula Saikia, additional, Barse, Brajesh, additional, Bayan, Mohammad F., additional, Behera, Prakash Chandra, additional, Bhattacharya, Vijeta, additional, Bhorge, Yeshwant R., additional, Bhuyan, Deepjyoti, additional, Bisht, Satpal Singh, additional, Bloch, Khalida, additional, Chandrasekaran, Balakumar, additional, Chatterjee, Prarthana, additional, Chaudhary, Rupali R., additional, Das, Kajari, additional, Dave, Sushma, additional, Dehury, Budheswar, additional, Desai, Urja, additional, Dey, Abhijit, additional, Dhanalakshmi, M., additional, Di Petrillo, Amalia, additional, Dubey, Navneet Kumar, additional, Dubey, Subodh Kumar, additional, Fais, Antonella, additional, Floris, Sonia, additional, Gadnayak, Ayushman, additional, Gaur, Arti, additional, Ghosh, Sougata, additional, Giri, Namrata A., additional, Gupta, Suchetana, additional, Gupta, Surya Prakash, additional, Gupta Soni, Anshita, additional, Hegde, Namita, additional, Isaq, Mona, additional, Iyer, Mayuri, additional, Jagatap, Vilas, additional, Jain, Sandhya, additional, Jayabaskaran, C., additional, Jobby, Renitta, additional, Juvale, Kapil, additional, Kader, S. Abdul, additional, Kaikini, Aakruti, additional, Kamble, Rahul B., additional, Kaur, Paranjeet, additional, Kellomäki, Minna, additional, Khanashyam, Anandu Chandra, additional, Khatun, Rousan, additional, Khera, Simran, additional, Kumar, Amit, additional, Kumar Singh, Pankaj, additional, Kumaravel, Mohanya, additional, Latambale, Ganesh, additional, Luo, Shun-Yuan, additional, Mahajan, Srushti, additional, Mahanty, Arabinda, additional, Mahender, Thatikayala, additional, Meher, Rajesh Kumar, additional, Minaxi, Maru, additional, Mir, Showkat Ahmad, additional, Mishra, Monika, additional, Mishra, Namrata, additional, Mishra, Rojita, additional, Mohanty, Ipsita, additional, Muhammad, Auwal, additional, Murugan, Vaishnavi, additional, Naik, Pradeep Kumar, additional, Nair, Sneha P., additional, Nayak, Binata, additional, Nirmal, Nilesh Prakash, additional, Padhiary, Archana, additional, Pal, Kavita, additional, Panda, Amrita Kumari, additional, Pandya, Medha, additional, Panhekar, Deepa Y., additional, Parihar, Vijay Singh, additional, Parthasarathy, Ramalingam, additional, Patel, Harun, additional, Patel, Viral, additional, Pati, Ashwariya, additional, Pati, Siddhartha, additional, Patil, Mayuri A., additional, Pattnaik, Subhaswaraj, additional, Poojari, Chandrappa Chinna, additional, Prasad Das, Alok, additional, Puri, Sachin, additional, Qaisi, Ali, additional, Quadri, Amreen S., additional, Rai, Padmalatha S., additional, Rajput, Mithun Singh, additional, Ramachandra, Yarappa Lakshmikant, additional, Ranveer, R.C., additional, Rathod, N.B., additional, Raval, Manan, additional, Ravi, Pooja, additional, Rawal, Rakesh, additional, Sahu, Sanjeev Kumar, additional, Saiyed, Hiram, additional, Sakhale, Bhagwan K., additional, Sarkar, Purnima Dey, additional, Sarkate, Aniket P., additional, Sawant, Ratnnadeep C., additional, Sawant, Siddhi, additional, Senapati, Manas Ranjan, additional, Shabbirahmed, Asma Musfira, additional, Sharma, Radha, additional, Shatnawi, Mohamad, additional, Shilali, K., additional, Shinde, Sonali S., additional, Singh, Harvinder, additional, Singh, Iqubal, additional, Singh, Sikha, additional, Somkuwar, Subhash R., additional, Somu, Prathap, additional, Sruthi, D., additional, Tawaha, Abdel Rahman Al, additional, Tete, Sheary Somam, additional, Thomas, Pinchu Elizabath, additional, Thongmee, Sirikanjana, additional, Thorakkattu, Priyamvada, additional, Tiwari, Mansi, additional, Tungare, Kanchanlata, additional, Upadhyay, Dhwani, additional, Upadhye, Vijay, additional, Vairagar, Pravin R., additional, Wadhwa, Pankaj, additional, and Yashavantha Rao, H.C., additional

Published
2023
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135. Converting Braille Symbol and Words to Voice

Author

Bhattacharya, Ritwick, Sharma, Harish, Chaurasia, Sandeep, Kushwaha, Satpal Singh, 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, Tripathi, Anshuman, editor, Soni, Amit, editor, Shrivastava, Ashish, editor, Swarnkar, Anil, editor, and Sahariya, Jagrati, editor

Published
2022
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139. Extremophilic Diversity and Climate Change

Author

Panda, Amrita Kumari, primary, Mishra, Rojita, additional, Miglani, Rashi, additional, Dewali, Seeta, additional, Kumar, Ankit, additional, Bora, Shikha, additional, and Bisht, Satpal Singh, additional

Published
2022
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150. A higher order stable numerical approximation for time‐fractional non‐linear Kuramoto–Sivashinsky equation based on quintic B‐‐spline.

Author

Choudhary, Renu, Singh, Satpal, Das, Pratibhamoy, and Kumar, Devendra

Subjects
*NUMERICAL analysis, *EQUATIONS, *QUINTIC equations
Abstract

This article deals with designing and analyzing a higher order stable numerical analysis for the time‐fractional Kuramoto–Sivashinsky (K‐S) equation, which is a fourth‐order non‐linear equation. The fractional derivative of order γ∈(0,1)$$ \upgamma \in \left(0,1\right) $$ present in the considered problem is taken into Caputo sense and approximated using the L1−2$$ L1-2 $$ scheme. In space direction, the discretization process uses quintic B$$ \mathfrak{B} $$‐spline functions to approximate the derivatives and the solution of the problem. The present approach is unconditionally stable and is convergent with rate of accuracy O(h2+k2)$$ \mathcal{O}\left({h}^2+{k}^2\right) $$, where h$$ h $$ and k$$ k $$ denote the space and time step sizes, respectively. We have also noted that the linearized version of the K‐S equation leads the rate of accuracy to O(h2+k3−γ)$$ \mathcal{O}\left({h}^2+{k}^{3-\upgamma}\right) $$. The present approach is also highly effective for the time‐fractional Burgers' equation. We have shown that the present approach provides better accuracy than the L1$$ L1 $$ scheme with the same computational cost for several linear/non‐linear problems, with classical as well as fractional time derivatives. [ABSTRACT FROM AUTHOR]

Published
2024
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