Oscillation of Second-Order Nonlinear Delay Dynamic Equations on Time Scales

In this work, we use the generalized Riccati transformation and the inequality technique to establish some new oscillation criteria for the second-order nonlinear delay dynamic equation (p(t)(xΔ(t))γ)Δ+q(t)f(x(τ(t)))=0, on a time scale , where γ is the quotient of odd positive integers and p(t) and q(t) are positive right-dense continuous (rd-continuous) functions on 𝕋. Our results improve and extend some results established by Sun et al. 2009. Also our results unify the oscillation of the second-order nonlinear delay differential equation and the second-order nonlinear delay difference equation. Finally, we give some examples to illustrate our main results

Oscillation of Second-Order Nonlinear Delay Dynamic Equations with Damping on Time Scales

We use the generalized Riccati transformation and the inequality technique to establish some new oscillation criteria for the second-order nonlinear delay dynamic equation with damping on a time scale T(r(t)g(x(t), xΔ(t)))Δ+p(t)g(x(t), xΔ(t))  + q(t)f(x(τ(t)))=0, where r(t), p(t), and q(t) are positive right dense continuous (rd-continuous) functions on T. Our results improve and extend some results established by Zhang et al., 2011. Also, our results unify the oscillation of the second-order nonlinear delay differential equation with damping and the second-order nonlinear delay difference equation with damping. Finally, we give some examples to illustrate our main results

Inferential Survival Analysis for Type II Censored Truncated Exponential Topp Leone Exponential Distribution with Application to Engineering Data

This study focuses on estimating the unknown parameters of the truncated exponential Topp-Leon distribution using a type II scheme. We estimate the unknown parameters, survival, and hazard functions using maximum likelihood estimation methods. Additionally, we derive the approximate variance covariance matrix and asymptotic confidence intervals. Furthermore, we compute Bayesian estimates of the unknown parameters under squared error and linear loss functions. To generate samples from the posterior density functions, we use the Metropolies-Hastings algorithm. We demonstrate the effectiveness of the proposed distribution by applying it to two data sets: Monte Carlo simulation and real data set. Our results show that the proposed distribution provides accurate estimates of the unknown parameters and performs well in fitting the data. Our findings also indicate that Bayesian estimation can provide more precise estimates with narrower confidence intervals compared to maximum likelihood estimation method. In summary, the study provides a comprehensive analysis of the estimation of the unknown parameters for the truncated exponential Topp-Leone distribution using a type II scheme. Also, the results demonstrate the potential of this distribution in modeling real data and the usefulness of both maximum likelihood and Bayesian estimation methods in obtaining accurate parameter estimates

Parameters and Reliability Estimation of Left Truncated Gumbel Distribution under Progressive Type II Censored with Repairable Mechanical Equipment Data

The estimation of two parameters of the left truncated Gumbel distribution using the progressive type II censoring scheme is discussed. We first derived the maximum likelihood estimators of the unknown parameters. The approximate asymptotic variance-covariance matrix and approximate confidence intervals based on the asymptotic normality of the classical estimators are calculated. Also, the survival and hazard functions are derived. Further, the delta method is used to construct approximate confidence intervals for survival and hazard functions. Using the left truncated normal prior for the location parameter and an inverted gamma prior for the scale parameter, several Bayes estimates based on squared error and general entropy loss functions are computed. Bayes estimators of the unknown parameters cannot be calculated in closed forms. Markov chain Monte Carlo method, namely Metropolis-Hastings algorithm, has been used to derive the approximate Bayes estimates. Also, the credible intervals are constructed by using Markov chain Monte Carlo samples. Finally, The Monte Carlo simulation study compares the performances among various estimates in terms of their root mean squared errors, mean absolute biased, average confidence lengths, and coverage probabilities under different sets of values of sample sizes, number of failures and censoring schemes. Moreover, a numerical example with a real data set and Markov chain Monte Carlo data sets are tackled to highlight the importance of the proposed methods. Bayes Markov chain Monte Carlo estimates have performed better than those obtained based on the likelihood function

Interval Oscillation Criteria for Forced Second-Order Nonlinear Delay Dynamic Equations with Damping and Oscillatory Potential on Time Scales

We are concerned with the interval oscillation of general type of forced second-order nonlinear dynamic equation with oscillatory potential of the form rtg1xt,xΔtΔ+p(t)g2(x(t),xΔ(t))xΔ(t)+q(t)f(x(τ(t)))=e(t), on a time scale T. We will use a unified approach on time scales and employ the Riccati technique to establish some oscillation criteria for this type of equations. Our results are more general and extend the oscillation criteria of Erbe et al. (2010). Also our results unify the oscillation of the forced second-order nonlinear delay differential equation and the forced second-order nonlinear delay difference equation. Finally, we give some examples to illustrate our results

The antiproliferative effect of mulberry (Morus alba L.) plant on hepatocarcinoma cell line HepG2

AbstractThis study aimed to investigate the antiproliferative effect of aqueous and organic extracts of mulberry leaves (Morus Alba L.) on human hepatocellular carcinoma HepG2 cell line. Mulberry leaf extracts were prepared using the solvents: water, 50% aqueous MeOH, and 100% MeOH for different time intervals, while the cells treated with dimethyl sulfoxide (DMSO) served as control. The effects of aqueous and organic extracts of M. alba L. leaves on HepG2 cell viability, nuclear factor kappa B (NF-κB) gene expression, alfa-fetoprotein (AFP), albumin (ALB), gamma-glutamyl transpeptidase (γ-GT) and alkaline phosphatase (ALP) were measured. The results of the cell viability assays showed that water, 50% aqueous MeOH, and 100% MeOH extracts exhibited a highly significant inhibitory effect on HepG2 cell proliferation which was evidenced by a reduction in viable cell count. The results were confirmed by microscopical examination of cell morphology. Furthermore, the mulberry leaf extracts suppressed the activity of NF-κB gene expression of HepG2 cells compared to the control. Also a highly significant depression occurred at the levels of AFP, γ-GT and ALP in HepG2 cells compared with that of controls in a time dependent manner. By contrast, the mulberry leaf extracts increased the secretion of ALB. Therefore, the conclusion was that the organic and aqueous extracts of mulberry leaves inhibit the growth of HepG2 cells through suppressing the activity of NF-κB gene expression and modulate the biochemical markers

A Critical Review of Renewable Hydrogen Production Methods: Factors Affecting Their Scale-Up and Its Role in Future Energy Generation

An increase in human activities and population growth have significantly increased the world’s energy demands. The major source of energy for the world today is from fossil fuels, which are polluting and degrading the environment due to the emission of greenhouse gases. Hydrogen is an identified efficient energy carrier and can be obtained through renewable and non-renewable sources. An overview of renewable sources of hydrogen production which focuses on water splitting (electrolysis, thermolysis, and photolysis) and biomass (biological and thermochemical) mechanisms is presented in this study. The limitations associated with these mechanisms are discussed. The study also looks at some critical factors that hinders the scaling up of the hydrogen economy globally. Key among these factors are issues relating to the absence of a value chain for clean hydrogen, storage and transportation of hydrogen, high cost of production, lack of international standards, and risks in investment. The study ends with some future research recommendations for researchers to help enhance the technical efficiencies of some production mechanisms, and policy direction to governments to reduce investment risks in the sector to scale the hydrogen economy up. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Acknowledgments: The authors extend their appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number “IF_2020_NBU_403”

A year of genomic surveillance reveals how the SARS-CoV-2 pandemic unfolded in Africa

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The evolving SARS-CoV-2 epidemic in Africa: insights from rapidly expanding genomic surveillance

Investment in SARS-CoV-2 sequencing in Africa over the past year has led to a major increase in the number of sequences generated, now exceeding 100,000 genomes, used to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence domestically, and highlight that local sequencing enables faster turnaround time and more regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and shed light on the distinct dispersal dynamics of Variants of Concern, particularly Alpha, Beta, Delta, and Omicron, on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve, while the continent faces many emerging and re-emerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century