Browsing by Author "Kumar, A"
Now showing 1 - 20 of 33
Results Per Page
Sort Options
Item 2-Deoxy-D-Glucose: A Novel Pharmacological Agent for Killing Hypoxic Tumor Cells, Oxygen Dependence-Lowering in Covid-19, and Other Pharmacological Activities(2023-03) Singh, R; Gupta, V; Kumar, A; Singh, KTe nonmetabolizable glucose analog 2-deoxy-D-glucose (2-DG) has shown promising pharmacological activities, including inhibition of cancerous cell growth and N-glycosylation. It has been used as a glycolysis inhibitor and as a potential energy restriction mimetic agent, inhibiting pathogen-associated molecular patterns. Radioisotope derivatives of 2-DG have applications as tracers. Recently, 2-DG has been used as an anti-COVID-19 drug to lower the need for supplemental oxygen. In the present review, various pharmaceutical properties of 2-DG are discussed.Item Curcumin ameliorates oxidative stress in red blood cells during ageing(2023-03) Kumar, A; Maurya, PAn essential dietary flavonoid known as curcumin has positive health effects and inhibits the synthesis of reactive oxygen species (ROS). The aim of this study is to look at signs of oxidative stress in red blood cells (RBCs) treated with curcumin as a function of age. A total of 116 healthy volunteers ranging in age from 20 to 81 years provided clinically pertinent blood samples for the investigation. Three groups of subjects were created: young (20 to 35 years), middle (36 to 60 years), and old (>60 years). Oxidative stress was induced in vitro by incubating RBCs with 10-5M tert-butyl hydroperoxide (t-BHP). Malondialdehyde and reduced glutathione were detected by co-incubating RBCs with curcumin (10-8 M to 10-5 M final concentration) and t-BHP to assess the effect of curcumin. After being incubated with t-BHP, the results revealed higher MDA levels (P <0.001) in comparison to their respective controls and the GSH level significantly (P <0.001) decreased during ageing. By raising GSH and lowering MDA levels, curcumin treatment in vitro considerably (P <0.01) mitigated the harmful effect of oxidative stress in RBCs from all age groups. The results of this study showed the potential role of curcumin in the ageing process and it will facilitate the quick screening of novel chemical compounds that may protect RBCs from oxidative stress.Item Curcumin ameliorates oxidative stress in red blood cells during ageing(2023-02) Kumar, A; Maurya, PKAn essential dietary flavonoid known as curcumin has positive health effects and inhibits the synthesis of reactive oxygen species (ROS). The aim of this study is to look at signs of oxidative stress in red blood cells (RBCs) treated with curcumin as a function of age. A total of 116 healthy volunteers ranging in age from 20 to 81 years provided clinically pertinent blood samples for the investigation. Three groups of subjects were created: young (20 to 35 years), middle (36 to 60 years), and old (>60 years). Oxidative stress was induced in vitro by incubating RBCs with 10-5M tert-butyl hydroperoxide (t-BHP). Malondialdehyde and reduced glutathione were detected by co-incubating RBCs with curcumin (10-8 M to 10-5 M final concentration) and t-BHP to assess the effect of curcumin. After being incubated with t-BHP, the results revealed higher MDA levels (P <0.001) in comparison to their respective controls and the GSH level significantly (P <0.001) decreased during ageing. By raising GSH and lowering MDA levels, curcumin treatment in vitro considerably (P <0.01) mitigated the harmful effect of oxidative stress in RBCs from all age groups. The results of this study showed the potential role of curcumin in the ageing process and it will facilitate the quick screening of novel chemical compounds that may protect RBCs from oxidative stress.Item Current scenario and challenges in recycling of human urine generated at source in rail coaches as resource(2023-07) Dubey, KK; Rajput, D; Baldia, A; Kumar, A; Kumar, V; Yadav, AThe current scenario of human urine being directly discharged into the environment without recycling, despite being an economical source of fertilizer. Train coaches are the major source of large-scale urine waste generation. Adopting a cir cular economy creates significant synergies toward usages of water generated after nutrient recovery from urine. Some advanced decentralized treatment systems, such as electro chemical, bioelectrical, or reverse osmosis, would be useful to treat and recover nutrients from urine waste/wastewater. The laborious and costly affair of removing nutrients like N, P, and K from human urine needed a sustainable solution. These recovered nutrients can be reused as fertilizers in irrigation and, indirectly, in large-scale biodiesel production by being used in microalgae cultivation. However, the potential of reusing human urine waste is yet to be explored commercially. Additionally, artificial intelligence may be explored with sus tainable approaches for urine separation and recycling soon.Item Current scenario and challenges in recycling of human urine generated at source in rail coaches as resource(2023-07) Dubey, K; Rajput, D; Baldia, A; Kumar, AThe current scenario of human urine being directly discharged into the environment without recycling, despite being an economical source of fertilizer. Train coaches are the major source of large-scale urine waste generation. Adopting a cir cular economy creates significant synergies toward usages of water generated after nutrient recovery from urine. Some advanced decentralized treatment systems, such as electro chemical, bioelectrical, or reverse osmosis, would be useful to treat and recover nutrients from urine waste/wastewater. The laborious and costly affair of removing nutrients like N, P, and K from human urine needed a sustainable solution. These recovered nutrients can be reused as fertilizers in irrigation and, indirectly, in large-scale biodiesel production by being used in microalgae cultivation. However, the potential of reusing human urine waste is yet to be explored commercially. Additionally, artificial intelligence may be explored with sus tainable approaches for urine separation and recycling soon.Item Design based synthetic imputation methods for domain mean(2024) Bhushan, S; Kumar, A; Pokhrel, RIn real life, situations may arise when the available data are insufcient to provide accurate estimates for the domain, the small area estimation (SAE) technique has been used to get accurate estimates for the variable under study. The problem of missing data is a serious problem that has an impact on sample surveys, but small area estimates are especially prone to it. This paper is a basic efort that suggests design based synthetic imputation methods for the domain mean estimation using simple random sampling in order to address the issue of missing data under SAE. The expression of the mean square error for the proposed imputation methods are obtained up to frst order approximation. The efciency conditions are determined and a thorough simulation study is carried out using artifcially generated data sets. An application is included with real data that further supports this study.Item Design based synthetic imputation methods for domain mean(2024) Bhushan, S; Kumar, A; Phokhrel, R; Bakr, M; Mekiso, GIn real life, situations may arise when the available data are insufcient to provide accurate estimates for the domain, the small area estimation (SAE) technique has been used to get accurate estimates for the variable under study. The problem of missing data is a serious problem that has an impact on sample surveys, but small area estimates are especially prone to it. This paper is a basic efort that suggests design based synthetic imputation methods for the domain mean estimation using simple random sampling in order to address the issue of missing data under SAE. The expression of the mean square error for the proposed imputation methods are obtained up to frst order approximation. The efciency conditions are determined and a thorough simulation study is carried out using artifcially generated data sets. An application is included with real data that further supports this study.Item Effect of selective fermentation on nutritional parameters and techno-functional characteristics of fermented millet-based probiotic dairy product(2024-05) Samtiya, M; Badgujar, P; Chandratre, G; Aluko, R; Kumar, A; Bhushan, B; Dhewa, TThe primary goal of this study was to assess the effect of selective fermentation on the nutritional and techno functional characteristics of fermented millet-skim milk-based product. The product was made with HHB-311 biofortified pearl millet (PM) flour, skim milk powder, and isolated cultures (either alone or in combination) of Limosilactobacillus fermentum MS005 (LF) and Lactobacillus rhamnosus GG 347 (LGG). To optimize fermentation time, time intervals 8, 16, and 24 h were explored, while the temperature was kept 37 ◦C. Results of protein digestibility showed that LF (16 h) and LGG (24 h) fermented samples had significantly higher (P < 0.05) protein digestibility of 90.75 ± 1.6% and 93.76 ± 3.4%, respectively, than that of control (62.60 ± 2.6%). Further, 16 h fermentation with LF showed enhanced iron (39%) and zinc (14%) bioavailability. The results suggested that LF with 16 h fermentation is most suitable for making millet-based fermented products with superior techno functional attributes and micronutrient bioavailability.Item Efficient imputation methods in case of measurement errors(2024-02) Kumar, A; Bhushan, S; Shukla, S; Bakr, MThis manuscript develops few efficient difference and ratio kinds of imputations to handle the situation of missing observations given that these observations are polluted by the measurement errors (ME). The mean square errors of the developed imputations are studied to the primary degree approximation by adopting Taylor series expansion. The proposed imputations are equated with the latest existing imputations presented in the literature. The execution of the proposed imputations is assessed by utilizing a broad empirical study utilizing some real and hypothetically created populations. Appropriate remarks are made for sampling respondents regarding practical applicationsItem An Efficient Method to Decide the Malicious Traffic: A Voting-Based Efficient Method(2023) Kumar, A; Singh, J; Kumar, VTo address the high rate of false alarms, this article proposed a voting-based method to efficiently predict intrusions in real time. To carry out this study, an intrusion detection dataset from UNSW was downloaded and preprocessed before being used. Given the number of features at hand and the large size of the dataset, performance was poor while accuracy was low. This low prediction accuracy led to the generation of false alerts, consequently, legitimate alerts used to pass without an action assuming them as false. To deal with large size and false alarms, the proposed voting-based feature reduction approach proved to be highly beneficial in reducing the dataset size by selecting only the features secured majority votes. Outcome collected prior to and following the application of the proposed model were compared. The findings reveal that the proposed approach required less time to predict, at the same time predicted accuracy was higher. The proposed approach will be extremely effective at detecting intrusions in real-time environments and mitigating the cyber-attacks.Item Enhanced direct and synthetic estimators for domain mean with simulation and applications(2024-07) Kumar, A; Bhushan, S; Pokhrel, R; Emam, W; Tashkandy, Y; Khan, MThis article considers the issue of domain mean estimation utilizing bivariate auxiliary information based enhanced direct and synthetic logarithmic type estimators under simple random sampling (SRS). The expressions of mean square error (MSE) of the proposed estimators are provided to the 1𝑠𝑡 order approximation. The efficiency criteria are derived to exhibit the dominance of the proposed estimators. To exemplify the theoretical results, a simulation study is conducted on a hypothetically drawn trivariate normal population from 𝑅 programming language. Some applications of the suggested methods are also provided by analyzing the actual data from the municipalities of Sweden and acreage of paddy crop in the Mohanlal Ganj tehsil of the Indian state of Uttar Pradesh. The findings of the simulation and real data application exhibit that the proposed direct and synthetic logarithmic estimators dominate the conventional direct and synthetic mean, ratio, and logarithmic estimators in terms of least MSE and highest percent relative efficiency.Item Evidence of a Large Refrigerant Capacity in Nb-Modified La1.4Sr1.6Mn2−xNbxO7 (0.0 ≤ x ≤ 0.15) Layered Perovskites(2024-03) Kumar, A; Sharma, M; Vij, A; Kumari, KIn this work, evidence of isothermal magnetic entropy change (∆SM) over a broad tempera ture region is presented in a series of La1.4Sr1.6Mn2−xNbxO7 Ruddlesden–Popper compounds with niobium modification (Nb) (0.0 ≤ x ≤ 0.15) at the manganese (Mn) site. The ceramic samples were ob tained through a solid-state sintering method in optimized conditions. All compounds predominantly possessed Ruddlesden–Popper phase while a few additional reflections were resolved in Nb-doped compounds which indicates the separation of structural phases. These peaks are assigned to a sepa rate layered perovskite and single perovskite with tetragonal symmetry and hexagonal symmetry, respectively. The microstructure of the pure sample reveals uniform grain morphology but in Nb doped specimens chiefly three types of grains were found. It was assumed that the inter-connected large particles were of R-P phase which is dominant in both parent and x = 0.05 compounds, while the hexagonal and polygonal morphology of grains in higher concentrations of dopants directly corroborates with the symmetry of single perovskite and additional layered perovskite phases, re spectively. The parent compound exhibits a single ∆SM curve, whereas all Nb-substituted samples display bifurcated ∆SM curves. This indicated two transition regions with multiple magnetic com ponents, attributed to distinct structural phases. The highest ∆SM values obtained for components corresponding to the R-P phase are 2.32 Jkg−1k −1 , 0.75 Jkg−1k −1 , 0.58 Jkg−1k −1 and 0.43 Jkg−1k −1 and for the second component located around room temperature are 0.0 Jkg−1k −1 , 0.2 Jkg−1k −1 , 0.28 Jkg−1k −1 and 0.35 Jkg−1k −1 for x = 0.0, 0.05, 0.10 and 0.15 compositions, respectively, at 2.5 T. Due to the collective participation of both components the ∆SM was expanded through a broad temperature range upon Nb doping.Item Genome sequencing of SARS-CoV-2 omicron variants in Delhi reveals alterations in immunogenic regions in spike glycoprotein(2023-10) Shikha, S; Jogi, M; Jha, R; Kumar, R; Sah, T; Kumar, AThe SARS-CoV-2 omicron variants keep accumulating a large number of mutations in the spike (S) protein, which contributes to greater transmissibility and a rapid rise to dominance within populations. The identification of mutations and their affinity to the cellular angiotensin-converting enzyme-2 (ACE-2) receptor and immune evasion in the Delhi NCR region was under acknowledged. The study identifies some mutations (Y505 reversion, G339H, and R346T/N) in genomes from Delhi, India, and their probable implications for altering the immune response and binding affinity for ACE-2. The spike mutations have influenced the neutralizing activity of antibodies against the omicron variant, which shows partial immune escape. However, researchers are currently exploring various mitigation strategies to tackle the potential decline in efficacy or effectiveness against existing and future variants of SARS-CoV-2. These strategies include modifying vaccines to target specific variants, such as the omicron variant, developing multivalent vaccine formulations, and exploring alternative delivery methods. To address this, it is also necessary to understand the impact of these mutations from a different perspective, especially in terms of alterations in antigenic determinants. In this study, we have done whole genome sequencing (WGS) of SARS-CoV-2 in COVID-19 samples from Delhi, NCR, and analyzed the spike’s mutation with an emphasis on antigenic alterations. The impact of mutation in terms of epitope formation, loss/gain of efficiency, and interaction of epitopes with antibodies has been studied. Some of the mutations or variant genomes seem to be the progenitors of the upcoming variants in India. Our analyses suggested that weakening interactions with antibodies may lead to immune resistance in the circulating genomes.Item Hybrid Approach of Cotton Disease Detection for Enhanced Crop Health and Yield(2024-07) Kumar, R; Kumar, A; Bhatia, K; Nisar, K; Chouhan, S; Maratha, P; Tiwari, AThe well-being of cotton crops is of utmost importance for maintaining agricultural productivity, and the early detection of diseases plays a critical role in achieving this objective. This study introduces a comprehensive approach for creating a machine learning-based system capable of identifying diseases in cotton plants through the analysis of leaf images. The research encompasses stages such as acquiring the dataset, pre-processing the data, training the model, developing an ensemble model, evaluating the models, and analyzing the results. Several machine-learning models are trained and evaluated to determine how well they can classify cotton leaves as "Healthy" or "Diseased." These models include Random Forest, Support Vector Machine (SVM), Multi-Class SVM, and an Ensemble model. This investigation yields a practical and visually informative system for disease detection, which can contribute to disease prevention, thereby enhancing both crop yield and quality. This work underscores the significance of continuous improvement by periodically updating the models and explores the potential of advanced techniques such as deep learning.Item In silico investigation of antioxidant interaction and effect of probiotic fermentation on antioxidant profiling of pearl millet-based rabadi beverage(2021-12) Yadav, P; Shukla, A; Dhewa, T; Kumar, APearl millet-based food products can be used for weight control and minimize the possibility of chronic diseases. They have protein, minerals, fat, phenolic compounds, and a diminutive glycemic index. Moreover, Probiotic fermentation can bring specific additional benefits in addition to nutritional improvements. In silico analysis of the chemical-protein interaction of tannic acid and ascorbic acid of pearl millet was undertaken. Further, the role of fortification of rabadi beverage by probiotic culture was also assessed in this study at different temperatures (35, 42, and 45°C) of fermentation. In silico study has predicted the association of both tannic acid and ascorbic acid with the various human proteins responsible for the growth and development of the human immune system. In all used probiotic (Lactobacillus rhamnosus, Lactobacillus sp. and Streptococcus faecalis), L. rhamnosus fortified rabadi beverage at continuous increasing temperature (35, 42, 45 °C) of non-autoclaved batch showed high content of TAC (36.83 ± 5.41 µg mL-1), TPC (46.1 ± 8.28 µg mL-1) and TFC (29.91 ± 7.73 µg mL-1); while decrease in tannins content (14.84 ± 4.64 µg mL-1) as compared to control [TAC (29.32 ± 3.17 µg mL-1), TPC (25.53 ± 5.75 µg mL-1), TFC (21.91 ± 5.95 µg mL-1), and Tannins (20.74 ± 3.43 µg mL-1)]. L. rhamnosus fortified rabadi beverage of non-autoclaved batch showed better results than Lactobacillus sp. and S. faecalis fortified rabadi beverage of both batches (autoclaved and non-autoclaved); which in turn expressed the enhanced therapeutic activity of probiotic fortified rabadi beverage.Item Inverse unit exponential probability distribution: Classical and Bayesian inference with applications(2024-05) Alsadat, N; Tanis, C; Sapkota, L; Kumar, A; Marzouk, W; Gemeay, AThis article examines the new inverse unit exponential distribution, utilizing both classical and Bayesian methodologies; it begins by present ing the general properties of the proposed model, highlighting characteristic features, such as the presence of a reverse-J or increasing and inverted bathtub-shaped hazard rate function. Furthermore, it explores various statistical properties of the suggested distribution. It employs 12 methods to estimate the associated parameters. A Monte Carlo simulation is conducted to evaluate the accuracy of the estimation pro cedure. Even for small samples, the results indicate that biases and mean square errors decrease as the sample size increases, demonstrating the robustness of the estimation method. The application of the suggested distribution to real datasets is then discussed. Empirical evidence, using model selection criteria and goodness-of-fit test statistics, supports the assertion that the suggested model outperforms several existing models considered in the study. This article extends its analysis to the Bayesian framework. Using the Hamiltonian Monte Carlo with the no U-turn sampling algorithm, 8000 real samples are generated. The convergence assessment reveals that the chains are convergent and the sam ples are independent. Subsequently, using the posterior samples, the parameters of the proposed model are estimated, and credible intervals and highest posterior density intervals are computed to quantify uncertainty. The applicability of the suggested model to real data under both classical and Bayesian methodologies provides insights into its statistical properties and performance compared to existing models.Item Logarithmic Type Direct and Synthetic Estimators for Domain Mean Using Simple Random Sampling(2024-01) Bhushan, S; Kumar, A; Pokhrel, RIn this article, we propose logarithmic type direct and synthetic estima tors for the estimation of domain mean under simple random sampling. The properties such as bias and mean square error of the proposed direct and synthetic estimators are obtained up to rst order approximation. The e - ciency conditions are obtained under which the proposed direct and synthetic estimators outperform their conventional counterparts. The performance of the proposed direct and synthetic estimators is examined with the help of comprehensive computational study using real and arti cially drawn popu lations. Some appropriate suggestions are also provided to the surveyors.Item Lomax tangent generalized family of distributions: Characteristics, simulations, and applications on hydrological-strength data(2024-05) Zaidi, S; Mahmood, Z; Atchadé, M; Tashkandy, Y; Bakr, M; Almetwally, E; Hussam, E; Gemeay, A; Kumar, AThis article proposes and discusses a novel approach for generating trigonometric G-families using hybrid generalizers of distributions. The proposed generalizer is constructed by utilizing the tangent trigonometric function and distribution function of base model 𝐺(𝑥). The newly proposed family of uni-variate continuous distributions is named the “Lomax Tangent Generalized Family of Distributions (LT-G)” and structural-mathematical-statistical properties are derived. Some special and sub-models of the proposed family are also presented. A Weibull-based model, ‘The Lomax Tangent Weibull (LT-W) Distribution,” is discussed and the plots of density (pdf) and hazard (hrf) functions are also explained. Model parameter estimates are estimated by employing the maximum likelihood estimation (MLE) procedure. The accuracy of the MLEs is evaluated through Monte Carlo simulation. Last but not least, to demonstrate the flexibility and potential of the proposed distribution, two actual hydrological and strength data sets are analyzed. The obtained results are compared with well-known, competitive, and related existing distributions.Item Mean estimation using an efficient class of estimators based on simple random sampling: Simulation and applications(2024-02) Kumar, A; Siddiqui, A; Mustafa, M; Hussam, E; Aljohani, H; Almulhim, FIn this article, we offer simple random sampling (SRS) based efficient class of estimators of population mean 𝑌̄ utilizing additional information. The expression of the mean square error of the proposed class of estimators is deduced up to first degree approximation. The efficiency conditions are established which are enhanced numerically utilizing a simulation study consummated over symmetrical and asymmetrical populations. Real data sets are also utilized to exemplify the suggested estimators. The numerical findings are appeared rather acceptable demonstrating better advancement over the ordinary estimators.Item A new sine-arisen probabilistic model and artificial neural network methods for statistical modeling of the music engineering and reliability data(2024-05) Zhu, J; Mohie El-Din, M; Kumar, AProbability-arisen models play a considerable role in preparing a crucial stage for decision-making concerning reliability, engineering, and more closely related scenarios. Bearing in mind the consequential roles of probability-arisen models, we introduce and implement a new probabilistic model that has arisen by using the sine function, namely, the sine very flexible Weibull (SVF-Weibull) distribution. The proposed SVF-Weibull distribution is a result of a combination of the very flexible Weibull distribution with the sine-based strategy. For the SVF-Weibull distribution, point estimates are obtained. The assessment of the point estimates of the SVF-Weibull distribution is done via a simulation study. Finally, the consequential role of the SVF-Weibull distribution, illustrated by considering reliability and music engineering data sets. Furthermore, we implement some machine learning tools for predicting the reliability and music engineering data sets. The performances of the machine learning tools are assessed across many hidden variables. Our findings suggest that the artificial neural network method is more optimal than other methods for predicting the reliability and music engineering data sets.