Browsing by Author "Sandeep Singh"

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A compounded probability model for decreasing hazard and its inferential properties
(Gnedenko Forum, 2021) Brijesh P. Singh; Utpal Dhar Das; Sandeep Singh
Early failures are generally observed due to latent defects within a product caused by faulty components, faulty assembly, transportation damage and installation damage. Also early life (infant mortality) failures tend to exhibit a decreasing failure rate over time. Such type of problems can be modelled either by a complex distribution having more than one parameter or by finite mixture of some distribution. In this article a single parameter continuous compounded distribution is proposed to model such type of problems. Some important properties of the proposed distribution such as distribution function, survival function, hazard function and cumulative hazard function, entropies, stochastic ordering are derived. The maximum likelihood estimate of the parameter is obtained which is not in closed form, thus iteration procedure is used to obtain the estimate of parameter. The moments of the proposed distribution does not exist. Some real data sets are used to see the performance of proposed distribution with comparison of some other competent distributions of decreasing hazard using Likelihood, AIC, AICc, BIC and KS statistics. © 2021 PROUniversitaria Publishing House. All rights reserved.
A general class of new continuous mixture distribution and application
(SCIK Publishing Corporation, 2021) Brijesh P. Singh; Sandeep Singh; Utpal Dhar Das
A generalization of a distribution increases the flexibility particularly in studying of a phenomenon and its properties. Many generalizations of continuous univariate distributions are available in literature. In this study, an investigation is conducted on a distribution and its generalization. Several available generalizations of the distribution are reviewed and recent trends in the construction of generalized classes with a generalized mixing parameter are discussed. To check the suitability and comparability, real data set have been used. © 2021 the author(s).
Effect of circuit training and yogasanas on cardiovascular endurance, inspiratory capacity and forced vital capacity among sports person with special reference to prakriti
(Informatics Publishing Limited, 2019) Sandeep Singh; Sangeeta Gehlot
Background: Circuit training and Yogasana are good for the development of physical and physiological fitness of an individual. These training methods are useful to develop the individual’s fitness component like strength, speed, cardiovascular endurance, flexibility and agility as well as physiological components like Forced Vital Capacity (FVC), Inspiratory Capacity (IC) and Expiratory Capacity (EC). Thus, this study was planned to find out the variation of cardiovascular endurance, inspiratory capacity and forced vital capacity among sport persons through circuit training and Yogasana practice in different Prakriti individuals. Materials and Methods: 60 young and healthy male of age group 18-28 years, inter university level sport players were selected and divided into three groups, two experimental group (Yogasana and circuit training group) and one control group. Prakriti of each player was determined by the standard proforma. Harvard step test and PFT was done before and after completion of intervention. Result: After intervention significant changes were found in cardiovascular endurance, forced vital capacity and inspiratory capacity. Pair wise comparison of groups resulted in significant difference between circuit training group v/s control group and Yogasana group v/s control group in FVC and IC, circuit training group v/s Yogasana groups in IC. On Prakriti wise analysis significant changes were observed in all the three parameters of all Prakriti players of circuit training group while, Yogasana group showed significant difference in different parameters. No change was found in control group. Conclusion: Circuit training and Yogasana practices produced almost similar response on all studied parameters. © 2019, Informatics Publishing Limited, All rights reserved.
Estimation of the source parameters of the Nepal earthquake from strong motion data
(Springer Netherlands, 2016) A. Joshi; Monu Tomer; Sohan Lal; Sumer Chopra; Sandeep Singh; Sanjay Prajapati; M.L. Sharma; Sandeep
Kathmandu and its surrounding region were rocked recently by a devastating earthquake on April 25, 2015. This is the largest earthquake that has occurred in this region since the past eight decades. This earthquake was recorded on strong motion stations located about 470–522 km away from its epicenter. Records of accelerographs from these stations have been used to determine the location of this earthquake using hypo71 algorithm given by Lee and Lehr (HYPO71, a computer program for determining hypocenter, magnitude and first motion pattern of local earthquakes. US Geological Survey Open file report, 100, 1975). The recorded accelerograms have been corrected for site effects using site amplification curve obtained from ambient seismic noise recorded at each station. Site effect has been computed using H/V ratio method given by Nakamura (Q Rep RTRI 30(1):25–33, 1989) using ambient noise data. The corrected record is further used to obtain source displacement spectra. The source spectrum obtained from strong motion data is compared with theoretical source spectrum obtained from Brune’s (J Geophys Res 75:4997–5009, 1970) model for the horizontal components. The long-term flat level and corner frequency from source displacement spectra are used to calculate stress drop, source radius and seismic moment of this earthquake. The present study indicates that the Nepal earthquake originated 12.0 km below the epicenter located at 27.93°N, 84.70°E. The source radius, stress drop and seismic moment of this earthquake estimated from source displacement spectra are 44.13 ± 3.85 km, 18.68 ± 5.93 bars and 3.53 ± 0.28 × 1027 dyne cm, respectively. © 2016, Springer Science+Business Media Dordrecht.
Explaining Ovarian Cancer Data with Increasing Hazard Model
(Natural Sciences Publishing, 2021) Brijesh P. Singh; Utpal Dhar Das; Sandeep Singh; Mansour Lotayif
A single parameter model is developed in this study and used to understand ovarian cancer data. Its several mathematical and statistical properties such as the hazard rate function, moments, moment generating function, mean residual life function, renyi entropy, Bonferroni and Lorenz curve along with order statistics are derived. Maximum likelihood method is used to estimate the parameter. Also the importance of proposed model is checked for engineering data. Analysis reveals that the proposed model has potential to provide a better explanation than several existing lifetime models © 2021 NSP Natural Sciences Publishing Cor.
Gene Therapy, OMICS Approaches, and Translational Neurodegenerative Models: Recent Advancements and Future Perspectives
(CRC Press, 2024) Aakriti Sharma; Shashank Shekhar Mishra; Sandeep Singh
Gene therapy, OMICS approaches, and translational neurodegenerative models collectively represent a cutting-edge triumvirate at the forefront of addressing neurodegenerative diseases. Gene therapy, through gene replacement, silencing, and editing, aims to correct genetic defects at their source, offering hope for conditions like Alzheimer’s and Parkinson’s. OMICS technologies-including genomics, transcriptomics, proteomics, and metabolomics-provide a comprehensive view of the molecular intricacies of these diseases, identifying genetic variants, gene expression changes, and protein profiles critical for understanding and developing targeted interventions. Translational neurodegenerative models bridge the gap between bench research and clinical applications, utilising in vitro cell cultures, induced pluripotent stem cells, and organoids to replicate disease complexities observed in humans. These models enhance the reliability and relevance of patient-specific studies, paving the way for personalised treatments. Understanding the molecular basis of neurodegeneration is imperative for advancing therapeutic interventions, offering insights into genetic mutations, abnormal protein aggregations, and disrupted signaling pathways. This knowledge facilitates the development of precise diagnostics, biomarkers, and targeted therapies, potentially halting or reversing disease progression. Gene therapy’s evolution, marked by key milestones such as the first clinical trial for Parkinson’s disease and the FDA approval for spinal muscular atrophy treatment, underscores its transformative potential. Techniques like CRISPR-Cas9 have further revolutionised the field, enabling precise genetic modifications. This integrated approach, combining gene therapy, OMICS, and translational models, holds promise for innovative and personalised medical interventions, aiming to improve outcomes and quality of life for individuals with neurodegenerative diseases. © 2025 selection and editorial matter, Sachchida Nand Rai, Sandeep Singh, Santosh Kumar Singh.
Health risk assessment from exposure to dissolved trace element concentration in drinking groundwater resources of Central Ganga Alluvial Plain: a case study of Lucknow region
(Taylor and Francis Ltd., 2022) Praveen Kumar Kannojiya; Ashwani Raju; Anjali Singh; Nupur Srivastava; Sandeep Singh; Munendra Singh
This study explores ‘Indicator Kriging’ approach for assessment of health risk from exposure to trace elements concentration (Formula presented.) in drinking water resources of the Central Ganga Alluvial Plain (CGAP), northern India. The estimates for (Formula presented.) were generated using analysis of groundwater samples (n = 100) collected from the Lucknow monitoring area to map the predicted area of health risk. The predicted probability maps have reclassified into a unified scale to generate Trace Element Risk Index (TERI), which has further integrated with human population count data to generate Health Risk Index of Lucknow. The results indicate that the risk is potentially alarming in urban areas as relatively high (Formula presented.) there are referring to the local (point) sources of contamination. Approximately 23.15% human population residing in about 69.77% of the total area is at moderate-to-high health risk probability. The findings of this study could help planning substantial remediation measures on long-term basis. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Mapping human health risk by geostatistical method: a case study of mercury in drinking groundwater resource of the central ganga alluvial plain, northern India
(Springer International Publishing, 2019) Ashwani Raju; Anjali Singh; Nupur Srivastava; Sandeep Singh; Dharmendra Kumar Jigyasu; Munendra Singh
Human health is “at risk” from exposure to sub-lethal elemental occurrences at a local and or regional scale. This is of global concern as good-quality drinking water is a basic need for our wellbeing. In the present study, the “probability kriging,” a geostatistical method that has been used to predict the risk magnitude of the areas where the probability of dissolved mercury concentration (dHg) is higher than the World Health Organization (WHO) permissible limit. The method was applied to geochemical data of dHg concentration in 100 drinking groundwater samples of Lucknow monitoring area (1222 km2) located within the Ganga Alluvial Plain, India. Threefold (high to extreme risk) and twofold (moderate risk) higher dHg concentration values than the WHO permissible limit were observed in all of the groundwater samples. The generated prediction map using the probability kriging method shows that the probability of exceedance of dHg is the highest in the northwestern part of the Lucknow monitoring area due to anthropogenic interferences. The hotspots with high to very high probability are potentially alarming in the urban sector where 32.4% of the total population is residing in 6.8% of the total area. Interpolation of local estimates results in an easily readable and communicable human health risk map. It may help to consider substantial remediation measures for managing drinking water resources of the Ganga Alluvial Plain, which is among the anthropogenic mercury emission–dominated regions of the world. © 2019, Springer Nature Switzerland AG.
Modeling of rupture using strong motion generation area: a case study of Hualien earthquake (M w 6.1) occurred on April 18, 2019
(Springer Science and Business Media Deutschland GmbH, 2023) Saurabh Sharma; Anand Joshi; Sandeep; Che-Min Lin; Chun-Hsiang Kuo; Kuo-Liang Wen; Sandeep Singh; Mukat Lal Sharma; Mohit Pandey; Jyoti Singh
The strong Hualien earthquake (Mw 6.1) occurred along the suture zone of the Eurasian Plate and the Philippine Sea Plate, which struck the Hualien city in eastern Taiwan on April 18, 2019. The focal mechanism of this earthquake shows that it is caused by a rupture within a thrust. In the present study, the rupture plane responsible for this earthquake has been modeled using the modified semi-empirical technique (MSET). The whole rupture plane is assumed to be composed of strong motion generation areas (SMGAs) along which the slip occurs with large velocities. The spatiotemporal distribution of aftershocks of this earthquake within identified rupture plane suggests that there are two SMGAs within the rupture plane. The source displacement spectra (SDS) obtained from the observed records have been used to compute the source parameters of these two SMGAs. The MSET efficiently simulates strong ground motion (SGM) at the rock site. The shallow subsurface shear wave velocity profile at various stations has been used as an input to SHAKE91 algorithm for converting records at the surface to that at the rock site. The simulated records are compared with the observed records based on root-mean-square error (RMSE) in peak ground acceleration (PGA) of horizontal components. Various parameters of the rupture plane have been selected using an iterative forward modeling scheme. The accelerograms have been simulated for all the stations that lie within an epicentral distance ranging from 5 to 100 km using the final rupture plane parameters. The comparison of observed and synthetic records validates the effectiveness of the simulation technique and suggests that the Hualien earthquake consists of two SMGAs responsible for high-frequency SGM. © 2022, The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.
Mother’s education and mortality under age three: An investigation in presence of some socio-demographic correlates
(Radiance Research Academy, 2021) Brijesh P. Singh; J.V. Madhusudan; Sandeep Singh
Introduction: Premature death or death during the beginning part of life is the major cause of concern for the research. As far as living and socioeconomic conditions of a country or society are concerned, infant and child mortality is considered a sensitive indicator. Also, child mortality continues to be a major public health issue particularly in developing countries where it is mostly concentrated and keeps occurring in large numbers. In India, the burden of children dying under five years of age is dispropor-tionately carried by socially disadvantaged groups. Mortality under age three has special importance because the child in this developing world is vulnerable to infectious diseases. Objective: The present study is an attempt to examine the factors that affect on mortality of children under age three in the most populous state of India. Methods: In this study, we have utilized the data from the fourth round of the National Family Health Survey (NFHS), conducted in 2015-2016 for Uttar Pradesh. Bivariate analysis of data and unadjusted/adjusted logistic regression has been used in the present study to know the likelihood of the various factors. Results: Logistic regression suggests that, among the socio-demographic variables, women’s education emerges as a strong predictor for explaining mortality under age three. As expected, the child of the illiterate mothers has experienced higher mortality as compared with literate mothers. Children of households with poor wealth index and sorter preceding birth interval are more likely to die than their counterparts. Mother’s age at childbirth and birth order also plays a significant association in underage three mortality. Male children have almost the same risk of dying as female children. Conclusion: The study indicates mother’s age at birth, education, birth order, birth interval and basic immunization emerges as an important factor to influence child mortality under age three, therefore there is an earnest need to intervene in these issues in the society. © IJCRR.
Neurodegenerative Diseases: Translational Models, Mechanisms, and Therapeutics
(CRC Press, 2024) Sachchida Nand Rai; Sandeep Singh; Santosh Kumar Singh
This reference book provides a comprehensive overview of models and therapeutic approaches against neurodegenerative diseases, including Parkinson’s disease, Alzheimer’s disease, Huntington’s disease, and amyotrophic lateral sclerosis. It explores models based on the chemical, induced, cellular, genetic, transgenic, and 3D organoid approaches in neurodegenerative diseases. The book also reviews advantages and limitations of these models in designing the treatment strategies. Additionally, the book covers the emerging field of bioinformatics and its application in modeling various neurodegenerative diseases. Towards the end, the book highlights the role of holistic management, precision medicine, OMICS, and gene therapy against neurodegenerative disorders. It examines the implications and significance of stem cells therapy in translational models of neurodegenerative diseases. This book is an invaluable resource for researchers, neuroscientists, and neurosurgeons for getting in-depth information on the neurodegenerative models and therapeutic approaches. © 2025 selection and editorial matter, Sachchida Nand Rai, Sandeep Singh, Santosh Kumar Singh.
Preface
(CRC Press, 2024) Sachchida Nand Rai; Sandeep Singh; Santosh Kumar Singh
[No abstract available]