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Ranked set sampling (RSS) is known to increase the efficiency of the estimators while comparing it with simple random sampling. The problem of missingness creates a gap in the information that needs to be addressed before proceeding for estimation. Negligible amount of work has been carried out to deal with missingness utilizing RSS. This paper proposes some logarithmic type methods of imputation for the estimation of population mean under RSS using auxiliary information. The properties of the suggested imputation procedures are examined. A simulation study is accomplished to show that the proposed imputation procedures exhibit better results in comparison to some of the existing imputation procedures. Few real applications of the proposed imputation procedures is also provided to generalize the simulation study. [ABSTRACT FROM AUTHOR]

In survey research, the issue of measurement errors (ME) has been sorted out by various authors, but the issue of correlated measurement errors (CME) has only been studied by Shalabh and Tsai (2017) till date. This article provides a modest acquaintance to evaluate the performance of few novel logarithmic estimators of population mean in the existence of CME under simple random sampling (SRS). The mean square error of the proposed estimators has been obtained. It has been exhibited theoretically under certain conditions that the proposed class of estimators dominates their conventional counterparts. Furthermore, the theoretical findings have been assessed with a Monte Carlo simulation using a hypothetically gendered population and proper suggestions have been forwarded to the survey professionals. [ABSTRACT FROM AUTHOR]

The data we encounter in real life often contain missing values. In sampling methods, missing value imputation is done with different methods. This article proposes novel logarithmic type imputation methods for estimating the population mean in the presence of missing data under ranked set sampling (RSS). According to the determined theoretical results, the proposed imputation methods are found to be the most efficient in comparison to popularly known imputation methods like mean imputation, Al-Omari and Bouza (2014) imputation methods, Sohail et al. (2018) imputation methods, and Bhushan and Pandey (2016) type imputation methods utilizing RSS. Apart from this, a simulation study has been accomplished utilizing artificially drawn symmetric and asymmetric populations. The outcomes are encountered to be rather satisfactory, showing improvement over all existing imputation methods. [ABSTRACT FROM AUTHOR]

New forms of interaction made possible by developments in special educational technologies can now help students with dyscalculia. Artificial intelligence (AI) has emerged as a promising tool in recent decades, particularly between 2001 and 2010, offering avenues to enhance the quality of education for individuals with dyscalculia. Therefore, the implementation of AI becomes crucial in addressing the needs of students with dyscalculia. Content analysis techniques were used to examine the literature covering the influence of AI on dyscalculia and its potential to assist instructors in promoting education for individuals with dyscalculia. The study sought to create a foundation for a more inclusive dyscalculia education in the future through in-depth studies. AI integration has had a big impact on educational institutions as well as people who struggle with dyscalculia. This paper highlights the importance of AI in improving the educational outcomes of students affected by dyscalculia. [ABSTRACT FROM AUTHOR]

AbstractVery little attention has been paid by the authors for providing improved imputation methods under correlated measurement errors (CMEs) using various sampling designs. This article addresses several power ratio imputation methods and the resulting estimators under ranked set sampling (RSS) when CMEs are present. The mean square error (MSE) is developed to assess how well the suggested estimators work under CMEs. The effectiveness of the proposed imputation methods and corresponding resultant estimators is assessed by a comprehensive simulation utilizing an artificially generated population. Further, an application of the proposed imputation methods is also provided using real data from Sweden’s municipalities consisting of the total number of seats in 1982 in municipal council taken as study variable and the number of conservative seats in 1982 in municipal council taken as auxiliary variable. The CMEs might arise due to common surveyor biases if the same surveyor collects information on both the “total number of seats in municipal council” and “the number of conservative seats in that municipal council”. The simulation and real data results show that the proposed power ratio imputation methods outperform the mean, conventional ratio, and product imputation methods. [ABSTRACT FROM AUTHOR]

In surveys, successive sampling is generally considered to study the same characteristic from one occasion to another so that the change in characteristics over time can be further studied. This paper presents a class of estimators using a novel approach to estimate population mean on two occasions under successive sampling. We have carried out numerical study and simulation study to validate the significance of the proposed class and its members. We have used an optimum unmatched proportion of each class or estimator to compute their respective mean square error during simulation, while other studies considered some fixed value for unmatched units. For large population, the suggested estimation technique is always better for survey practitioners than others. [ABSTRACT FROM AUTHOR]

Abstract.This article suggested some sampling strategies allied with Searls (1964) for mean estimation on current occasions under an optimal random non response framework using auxiliary information. The characteristics of each class or estimator under their respective strategy have been studied under the optimum replacement policy. We have gauged losses, which are carried out to show the dominance over complete response classes like Singh and Vishwakarma (2007, 2009). Appropriate recommendations have been made to the survey researchers for their real-life practical applications. [ABSTRACT FROM AUTHOR]

In real life, situations may arise when the available data are insufficient 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 effort 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 first order approximation. The efficiency conditions are determined and a thorough simulation study is carried out using artificially generated data sets. An application is included with real data that further supports this study. [ABSTRACT FROM AUTHOR]

In 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 first order approximation. The efficiency 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 artificially drawn populations. Some appropriate suggestions are also provided to the surveyors. [ABSTRACT FROM AUTHOR]

Missing data is an obligatory phenomenon in most of the sample surveys and when it is not handled cautiously at beginning of the study, outcomes may result to substantial biases in the survey estimates. Retaining such evidences into cognizance, this paper proffers few possible improved imputation methods to figure out the problem of missing data at the starting of the study and proffers computation procedure of the population mean using simple random sampling. The characteristics of the proffered imputation methods are ascertained till first order approximation pursued by a computational study carried out using several existent and hypothetical data sets. The findings are turned out rather promising showing dominance over the existing imputation methods. Further, apposite advices have been forwarded to the survey professionals for practical applications. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we intend to utilize the multi auxiliary information available under RSS for the imputation of missing data. The mean imputation, regression imputation methods, and power transformation imputation method are identified as special cases of the proposed imputation methods. These methods are dominated by the proposed imputation methods. The theoretical comparison provides the dominance conditions of the proposed imputation methods over their conventional counterparts. In support of the theoretical findings, a simulation study is considered over a hypothetically generated population. Furthermore, some real data examples are also provided to generalize the simulation results. [ABSTRACT FROM AUTHOR]

In survey sampling, several estimation procedures have been proffered by various prominent authors to compute the impact of measurement errors (ME) but the impact of correlated measurement errors (CME) has been computed only by Shalabh and Tsai [Ratio and product methods of estimation of population mean in the presence of correlated measurement errors. Commun Stat Simul Comput. 2016;46(7):5566–5593]. This study provides a novel approach to compute the impact of CME through some logarithmic-type estimators using simple random sampling (SRS). The properties of the proffered estimators have been studied and compared with the properties of the conventional estimators. A numerical study and a broad spectrum simulation study are accomplished over real and artificially generated populations to support the theoretical results. [ABSTRACT FROM AUTHOR]

This research article addresses an efficient separate and combined class of estimators for the population mean estimation based on stratified random sampling (StRS). The first order approximated expressions of bias and mean square error of the proposed separate and combined class of estimators are obtained. A comparative study is conducted to determine the efficiency conditions in which the suggested class of estimators outperforms the contemporary estimators. These efficiency conditions are examined through an extensive simulation study by employing a hypothetically drawn symmetrical and asymmetrical populations. The simulation results have shown that the suggested class of estimators is more effective than the other available estimators. In addition, an application of the proposed methods is also presented by examining a real data set. [ABSTRACT FROM AUTHOR]

It is well known that ranked set sampling (RSS) is more efficient than simple random sampling (SRS). Furthermore, the presence of missing data vitiates the conventional results. Only a minuscule amount of work has been conducted under RSS with missing data. This paper makes a modest attempt to provide some efficient difference- and ratio-type imputation methods in the presence of missing values under RSS. The envisaged imputation methods are demonstrated to provide better results than the existing imputation methods. The theoretical results are enhanced by a computational analysis using real and hypothetically generated symmetric (Normal) and asymmetric (Gamma and Weibull) populations. The computational results show that the proposed imputation method outperforms the existing imputation methods in terms of its higher percent relative efficiency. Additionally, the impact of skewness and kurtosis on the efficiency of the suggested imputation methods has also been calculated. [ABSTRACT FROM AUTHOR]

Ranked set sampling (RSS) has been proven an efficient alternative to simple random sampling (SRS). The use of auxiliary information also helps to improve the efficiency of the estimation procedures. Therefore, to accomplish higher efficiency and discuss the optimality issues, we proffer some optimal classes of estimators under RSS by employing multi-auxiliary information. It is seen that the ordinary mean estimator, traditional regression, and ratio estimators are the subsets of the proffered estimators. The expressions of the bias and mean square error are reported. An analytical comparison under some optimality conditions points out the ascendancy of the proffered classes of estimators over all reviewed works. The theoretical results have been furnished with computational study by employing some artificial and natural populations. The computational results show that the proffered estimators outperform the conventional estimators reviewed in this study. Furthermore, apposite advices are suggested to the survey persons. [ABSTRACT FROM AUTHOR]

This article examines the issue of population mean estimation utilizing past and present data in the form of an exponentially weighted moving average (EWMA) statistic under simple random sampling (SRS). We suggest memory-type logarithmic estimators and derive their properties, such as mean-square error (MSE) and bias up to a first-order approximation. Using the EWMA statistic, the conventional and novel memory-type estimators are compared. Real and artificial populations are used as examples to illustrate the theoretical findings. According to the empirical findings, memory-type logarithmic estimators are superior to the conventional mean estimator, ratio estimator, product estimator, logarithmic-type estimator, and memory-type ratio and product estimators. [ABSTRACT FROM AUTHOR]

In the model plant Arabidopsis thaliana, parental age is known to affect somatic mutation rates in their immediate progeny and here we show that this age dependent effect persists across successive generations. Using a set of detector lines carrying the mutated uidA gene, we examined if a particular parental age maintained across five consecutive generations affected the rates of base substitution (BSR), intrachromosomal recombination (ICR), frameshift mutation (FS), and transposition. The frequency of functional GUS reversions were assessed in seedlings as a function of identical/different parental ages across generations. In the context of a fixed parental age, BSR/ICR rates were unaffected in the first three generations, then dropped significantly in the 4th and increased in most instances in the 5th generation (e.g. BSR (F1 38 = 0.9, F2 38 = 1.14, F3 38 = 1.02, F4 38 = 0.5, F5 38 = 0.76)). On the other hand, with advancing parental ages, BSR/ICR rates remained high in the first two/three generations, with a striking resemblance in the pattern of mutation rates (BSR (F1 38 = 0.9, F1 43 = 0.53, F1 48 = 0.79, F1 53 = 0.83 and F2 38 = 1.14, F2 43 = 0.57, F2 48 = 0.64, F2 53 = 0.94). We adopted a novel approach of identifying and tagging flowers pollinated on a particular day, thereby avoiding biases due to potential emasculation induced stress responses. Our results suggest a time component in counting the number of generations a plant has passed through self-fertilization at a particular age in determining the somatic mutation rates. [ABSTRACT FROM AUTHOR]

The essence of this paper is to propose some efficient combined and separate classes of estimators for estimating population mean Y ¯ under stratified simple random sampling. The bias and mean square error of the proposed classes of estimators are obtained. The proposed estimators are theoretically justified over the conventional mean estimator, classical ratio and regression estimators, Kadilar and Cingi estimators, Shabbir and Gupta estimators, Singh and Vishwakarma estimators, Koyuncu and Kadilar estimators, Singh and Solanki estimator, Yadav et al. estimator, Solanki and Singh estimator and Shahzad et al. estimator. The theoretical findings are extended with a simulation study accomplished over some artificially generated symmetric and asymmetric populations. [ABSTRACT FROM AUTHOR]

In survey research, various types of estimators have been suggested that consider only the current sample information to compute the unknown population parameters. Therefore, we utilize the past sample information along with the current sample information in the form of hybrid exponentially weighted moving averages to suggest the memory type logarithmic estimators for time-based surveys. The expression of the mean square error of the suggested estimators is determined to the first order of approximation. A relative comparison of the suggested estimators with the existing estimators is performed and efficiency conditions are obtained. Further, a simulation study is accomplished using a hypothetically rendered population and a real data illustration to improve the theoretical results. The results of the simulation study and the real data application exhibit that the consideration of past and current sample information meliorates the efficiency of the suggested estimators. [ABSTRACT FROM AUTHOR]

The present article discusses the issue of population mean estimation in the ranked set sampling framework. A modified class of estimators is proffered and compared in the aspect of its efficacious performance with all salient conventional estimators existing to date. Some well-known existing estimators under R S S are recognized as the members of the proffered estimators for appropriately chosen characterizing scalars. The ascendancy of the proposed class of estimators regarding the conventional estimators has been shown through an extensive computational study utilizing some natural and artificially generated populations. [ABSTRACT FROM AUTHOR]

In this manuscript, we propose the combined and separate difference and ratio type estimators of population mean using stratified ranked set sampling. Additionally, several well-known estimators are identified as the sub-class of the suggested estimators. The characteristics of the suggested estimators have been analyzed and their effective performances are compared with the prominent estimators existing till date. Moreover, to prove the credibility of the theoretical findings, an extensive empirical study is administered over some real and hypothetically yielded symmetric and asymmetric populations. [ABSTRACT FROM AUTHOR]

Infectious and contagious diseases exist in humanity for many centuries which causes a curb in the growth of the population. Immunization plays a vital role to prevent mortality and morbidity against infectious diseases. COVID-19 pandemic continues to rage the urgency of developing a vaccine that should ensure the safety, efficacy, swift and fair deployment, implementation, and monitoring of vaccines across the globe. In the present context, the vaccine production to immunization campaign is a critical challenge. Therefore, an effective vaccine supply chain mechanism is required to address issues such as counterfeit vaccines, reduce vaccine wastages, and vaccine record fraud. In this paper, a blockchain-enabled vaccine supply chain is proposed to ensure the correctness, transparency, trust, and immutable log and improve the efficiency of vaccine distribution in the cold chain. The uniqueness of the proposed system is to provide distributed system to verify the reliability and efficacy of the vaccine from production to end beneficiaries' feedback about the vaccine. Our proposed system gives a clear view to the users as well as to the healthcare provider about the vaccination and ensures the anticounterfeit vaccine. The proposed system minimizes counterfeit vaccines and records, provides transparent communication between stakeholders in the supply chain, and improves the security of the vaccine supply chain and immutable feedback system about the vaccine. [ABSTRACT FROM AUTHOR]

This manuscript considers some improved combined and separate classes of estimators of population mean using bivariate auxiliary information under stratified simple random sampling. The expressions of bias and mean square error of the proposed classes of estimators are determined to the first order of approximation. It is exhibited that under some particular conditions, the proposed classes of estimators dominate the existing prominent estimators. The theoretical findings are supported by a simulation study performed over a hypothetically generated population. [ABSTRACT FROM AUTHOR]

This paper proposes some optimal classes of estimators under ranked set sampling. We have acquainted some modifications of the difference and ratio type estimators under ranked set sampling, considered by various authors like Hansen et al., Srivastava, and Walsh in simple random sampling. We have demonstrated that the efficiency of the proposed optimal classes of estimators are always better than the other existing estimators. The theoretical results have been supported by a simulation study carried out over an artificially generated population. [ABSTRACT FROM AUTHOR]

This study introduces some modified classes of estimators of population variance in simple random sampling utilizing information on auxiliary attribute which cover traditional mean, ratio and regression estimators and Kadilar and Cingi (2004) type estimators adapted by Singh and Malik (2014) for particular values of characterizing scalars. The expressions of bias and mean square error of the proposed classes of estimators are tabulated up to the first order of approximation. The proposed classes of estimators are theoretically compared with the contemporary estimators existing till date and the efficiency conditions are obtained. Subsequently, the theoretical results are numerically enhanced by using a real data set. [ABSTRACT FROM AUTHOR]

In this article, we propose additive shared gamma frailty model and additive shared inverse Gaussian frailty model with Lindley as baseline distribution to analyze the infectious disease data set of McGilchrist and Aisbett. The Bayesian approach of Markov Chain Monte Carlo technique was employed to estimate the parameters involved in the models. A simulation study was also carried out to compare the true values and estimated values of the parameters. Comparison of proposed models and the existing models was also done by using Bayesian information criteria such as BIC, WBIC and Bayes factor. A better model was also recommended for infectious disease data. [ABSTRACT FROM AUTHOR]

This paper introduces some new ratio- and difference-type estimators of the population variance in the presence of random non-response based on Searls (The utilization of a known coefficient of variation in the estimation procedure. J Am Stat Asso. 1964;59:1225–1226) philosophy. The proposed ratio- and difference-type estimators remain better than the estimators obtained by Ahmeda et al. (Estimation of finite population variance in presence of random non-response using auxiliary variables. Infr Mang Sci. 2005;16(2):73–82) in the presence of random non-response using auxiliary variables. The properties (bias and mean square error) of the proposed estimators presented were derived up to the first-order approximation using the Taylor series approach. Conditions for which the new estimators more efficient than other estimators considered in the study were also established. Numerical examples were conducted, and the results revealed that the proposed class of estimators is more efficient than existing estimators. [ABSTRACT FROM AUTHOR]

This article deals with some new imputation methods by extending the work of Bhushan and Pandey using multi-auxiliary information. The popularly used imputation like mean imputation, ratio method of imputation, regression method of imputation and power transformation method are special cases of the proposed methods apart from being less efficient than the proposed methods. The proposed imputation methods can be considered as an efficient extension to the work of Singh and Deo (Stat Pap 44:555–579, 2003), Singh (Stat A J Theor Appl Stat 43(5):499–511, 2009), Ahmed et al. (Stat Transit 7(6):1247–1264, 2006), Diana and Perri (Commun Stat Theory Methods 39:3245–3251, 2010) and Bhushan and Pandey (J Stat Manag Syst 19(6):755–769, 2016, Commun Stat Theory Methods 47(11):2576–2589, 2018). The theoretical results are derived and comparative study is conducted using real and simulated data and the results are found to be quite encouraging providing the improvement over the all discuss work. [ABSTRACT FROM AUTHOR]

The present study is an attempt to equip a strategy with a cost-effective computational approach when non response is present under two occasion sampling. We have applied our computational cost strategy over Choudhary et al. (2004)'s non response setup for fixed precision and evaluated cost. In addition, we have also computed variance for some fixed cost. We have discussed the aforementioned procedure for three cases as when there is non response present on both occasions, first occasion and second occasion. A numerical illustration is demonstrated for validation of improved cost methodology where we also work out with optimum unmatched or matched fraction while Choudhary et al. (2004) do not provide the direct optimal result. [ABSTRACT FROM AUTHOR]

This paper introduces some improved methods of imputation using higher order moment of an auxiliary variable while imputing missing values. The performance of the proposed imputation methods are investigated relative to the methods proposed by Mohamed, Sedory, and Singh (2016) and Bhushan and Pandey (2016, 2018). A comparative study has been carried out and it has been shown that the proposed methods perform better in comparision to methods proposed by Mohamed, Sedory, and Singh (2016) and Bhushan and Pandey (2016, 2018). The theoretical findings are supported by numerical study on two real populations and a simulation study using hypothetical population. [ABSTRACT FROM AUTHOR]

Protein synthesis in all the living cells is mediated by a large protein-RNA complex called the ribosome. These macromolecular complexes can range from 2.5 (prokaryotes) to 4.2 MDa. (eukaryotes) in size and undergo various conformational transitions during protein synthesis to translate the genetic code into the nascent polypeptide chains. Recent advances in cryo-electron microscopy (cryo-EM) and image processing methods have provided numerous detailed structures of ribosomes from diverse sources and in different conformational states resolved to near-atomic resolutions. These structures have not only helped in better understanding of the translational mechanism but also revealed species-specific variations or adaptations in the ribosome structures. Structural investigations of the ribosomes from Mycobacterium smegmatis (Msm) and its closely related pathogenic Mycobacterium tuberculosis (Mtb) lead to the identification of two additional ribosomal proteins named as bS22 and bL37 and several unique extensions in ribosomal-protein and ribosomal-RNA. Hibernation Promoting Factor (HPF) bound structure of Msm ribosome, termed as the hibernating ribosome, possibly indicates a new mechanism of ribosome protection during dormancy. These studies enabled the identification of the mycobacteria-specific ribosomal features and provides an opportunity to understand their function and target them for further drug-discovery purposes. Here we review the unique structural features identified in Msm ribosome and their possible implications in comparison to a well-studied Escherichia coli (Ec) ribosome. [ABSTRACT FROM AUTHOR]

In 2011, France and Germany banned pioglitazone due to a concomitant risk for bladder cancer. There has been continued debate about this topic. Therefore, we present a detailed analysis of data from individual case safety reports of pioglitazone use (PG-ICSRs) associated with bladder cancer reported worldwide and in India. Data from PG-ICSRs reported by the National Coordination Centre's Pharmacovigilance Programme of India, as well as over 131 World Health Organization member countries in the Uppsala Monitoring Centre's VigiLyze pharmacovigilance database system, from January 1, 1967, to March 4, 2018, were collected. Comparisons between data from global and Indian PG-ICSRs were made by applying filters such as country, bladder cancer, age group, gender, time period, information component, and data mining. Among the adverse drug reactions (ADRs) reported with pioglitazone use worldwide, bladder cancer and related terms were the most highly reported (43%). The most frequently co-reported concurrently used drug was metformin, which was included in 25% and 40% of overall and bladder cancer–specific PG-ICSRs, respectively. Suspected bladder cancer–specific pioglitazone-related reactions were reported in 27 countries, with 8548 serious and 1858 fatal cases and an information components value of 9.15. The Americas had the highest relative percentage of suspected bladder cancer in PG-ICSRs (53%), while the prevalence was much lower in India (2%). In both cohorts, men over the age of 45 years constituted the most highly reported population. India has a very low prevalence of reported overall and bladder cancer–specific pioglitazone-related ADRs compared to Europe and the Americas. Possible explanations for the difference in reporting rates include variance in genetic makeup, low BC risk factor, pioglitazone prescription at a lower therapeutic dose, greater use of chemopreventive spices in the diet, higher frequency of metformin as a concurrent drug, and under-reporting of ADRs. [ABSTRACT FROM AUTHOR]

In this article, we have considered three different shared frailty models under the assumption of generalized Pareto Distribution as baseline distribution. Frailty models have been used in the survival analysis to account for the unobserved heterogeneity in an individual risks to disease and death. These three frailty models are with gamma frailty, inverse Gaussian frailty and positive stable frailty. Then we introduce the Bayesian estimation procedure using Markov chain Monte Carlo (MCMC) technique to estimate the parameters. We applied these three models to a kidney infection data and find the best fitted model for kidney infection data. We present a simulation study to compare true value of the parameters with the estimated values. Model comparison is made using Bayesian model selection criterion and a well-fitted model is suggested for the kidney infection data. [ABSTRACT FROM AUTHOR]

It is an established fact that the existence of measurement errors (M E) vitiates the conventional properties of the estimators. The impact of correlated measurement errors (C M E) was first assessed by Shalabh and Tsai (2017) using classical ratio and product estimators. This article makes a modest attempt to suggest some classes of robust estimators of population mean in the presence of C M E. The bias and mean square error of the suggested estimators are reported with the first-order approximation and the efficiency conditions are derived. The theoretical results are extended with the help of a simulation study executed over a hypothetically rendered population. Apart from this, the effect of M E on the suggested estimators is also studied both theoretically and empirically. • To examine robustness of the proposed estimators under correlated measurement errors. • To provide a comparative study. • To provide an empirical study using real and artificially generated populations. [ABSTRACT FROM AUTHOR]

Due to the global population growth and economic development, energy demand has increased worldwide. Countries take steps to improve their alternative and renewable energy sources. Algae is one of the alternative energy sources and can be used to produce renewable biofuel. In this study, nondestructive, practical, and rapid image processing techniques were applied to determine the algal growth kinetics and biomass potential of four algal strains, including C. minutum, Chlorella sorokiniana, C. vulgaris, and S. obliquus. Laboratory experiments were conducted to determine different aspects of biomass and chlorophyll production of those algal strains. Suitable non-linear growth models, including Logistic, modified Logistic, Gompertz, and modified Gompertz models, were employed to determine the growth pattern of algae. Moreover, the methane potential of harvested biomass was calculated. The algal strains were incubated for 18 days, and the growth kinetics were determined. After the incubation, the biomass was harvested and assessed for its chemical oxygen demand content and biomethane potential. Among the tested strains, C. sorokiniana was the best in biomass productivity (111.97 ± 0.9 mg L−1d−1). The calculated vegetation indices, namely; colorimetric difference, color index vegetation, vegetative, excess green, excess green minus excess red, combination, and brown index values showed a significant correlation with biomass and chlorophyll content. Among the tested growth models, the modified Gompertz shows the best growth pattern. Further, the estimated theoretical CH 4 yield was highest for C. minutum (0.98 mL g−1) compared to other tested strains. The present findings suggest that image analysis can be used as an alternative method to study the growth kinetics and biomass production potential of different algae during cultivation in wastewater. [Display omitted] • Growth of C. sorokiniana , C. vulgaris , C. minutum , and S. obliquus were compared. • C. sorokiniana outperformed in terms of biomass production in municipal wastewater. • Pioneering attempts on algal growth kinetics using image analysis. • Among the tested growth models, modified Gompertz shows the best fit. • Optimal theoretical CH 4 for C. minutum was 0.98 mL g−1 [ABSTRACT FROM AUTHOR]

This article proposes various Searls-type ratio imputation methods (STRIM) on the lines of Ahmed et al. (2006). It is a well-known fact that the optimal ratio type estimator attains the MSE of regression estimator (or optimal difference estimator) but while using Searls-type transformation (STT) (Searls (1964)) this may not always happen. These STRIM are shown to perform better than the imputation procedures of Ahmed et al. (2006). The STRIM may even outperform the Searls type difference imputation methods (STDIM) proposed by us in our earlier work, Bhushan and Pandey (2016). This study is concluded with the numerical study along with the theoretical comparison. [ABSTRACT FROM AUTHOR]

Background: The fishes of family Gobiidae are one of the least studied fishes, especially for otolith structure. The otoliths were possess species specific features. Hence, traits of sagittal otolith of gobid species studied. Methods: Five gobid species Odontamblyopus roseus (Valenciennes, 1837), Trypauchen vagina (Bloch and Schneider, 1801), Glossogobius giuris (Hamilton, 1822), Parachaeturichthys polynema (Bleeker, 1853) and Boleophthalmus dussumieri (Valenciennes, 1837) were investigated by three methods including morphological, shape indices and step wise discriminant function analysis (SDFA). Result: Interrelationship between shape indices investigated, at 95% level of confidence (P<0.05), revealed that perimeter of P. polynema and area of T. vagina have isometric growth with their length (b=3.0071, 2.90, respectively) and otolith area of B. dussumieri have positive allometric growth (b=4.23077). SDFA, based on otolith morphometry, discriminated species up with 97.18% accuracy. Hence, the results of present investigation can be used for discrimination of the species and as a tool in predicting fish size from the otoliths and in calculating the biomass of these less studied fish species. [ABSTRACT FROM AUTHOR]

A mathematical model is developed to analyze electro-kinetic effects on unsteady peristaltic transport of blood in cylindrical vessels of finite length. The Newtonian viscous model is adopted. The analysis is restricted under Debye-Hückel linearization (i.e., wall zeta potential 25mV) is sufficiently small). The transformed, nondimensional conservation equations are derived via lubrication theory and long wavelength and the resulting linearized boundary value problem is solved exactly. The case of a thin electric double layer (i.e., where only slip electro-osmotic velocity considered) is retrieved as a particular case of the present model. The response in pumping characteristics (axial velocity, pressure gradient or difference, volumetric flow rate, local wall shear stress) to the influence of electro-osmotic effect (inverse Debye length) and Helmholtz-Smoluchowski velocity is elaborated in detail. Visualization of trapping phenomenon is also included and the bolus dynamics evolution with electro-kinetic effects examined. A comparative study of train wave propagation and single wave propagation is presented under the effects of thickness of EDL and external electric field. The study is relevant to electrophoresis in haemotology, electrohydrodynamic therapy and biomimetic electro-osmotic pumps. [ABSTRACT FROM AUTHOR]

The influence of transverse magnetic field on time-dependent peristaltic transport of electrically-conducting fluids through a microchannel under an applied external electric field with induced electric field effect is considered, based on lubrication theory approximations. The electrohydrodynamic (EHD) problem is also simplified under the Debye linearization. Closed-form solutions for the linearized dimensionless boundary value problem are derived. With increasing Hartmann number, the formation of bolus in the regime (associated with trapping) is inhibited up to a critical value of magnetic field. Flow rate, axial velocity and local wall shear stress are strongly decreased with greater Hartmann number whereas pressure difference is enhanced with higher Hartmann number at low time values but reduced with greater elapse in time. With greater electro-osmotic parameter (i.e. smaller Debye length), maximum time-averaged flow rate is enhanced, whereas the axial velocity is reduced. An increase in electrical field parameter (i.e. maximum electro-osmotic velocity) causes an increase in maximum time-averaged flow rate. The simulations find applications in electromagnetic peristaltic micro-pumps in medical engineering and also “smart” fluid pumping systems in nuclear and aerospace industries. [ABSTRACT FROM AUTHOR]

Lupus nephritis and renal polyarteritis nodosa (PAN) are two distinct disorders that rarely overlap. Herein, we describe a patient who was initially diagnosed with lupus nephritis based on her clinical presentation, proteinuria, hematuria, positive anti-nuclear antibody, and a kidney biopsy. A month later, the patient presented with left flank pain and weakness. A CT scan of the abdomen and pelvis showed a perinephric hematoma and the renal arteriogram revealed numerous microaneurysms within the kidney consistent with renal PAN. This case elucidates the diagnostic and management dilemmas that confront physicians taking care of patients with overlapping features of lupus nephritis and renal PAN and also points to the possible role of lupus nephritis in pathogenesis of renal PAN. [ABSTRACT FROM PUBLISHER]

Shikonins are commercially important secondary compounds, known for array of biological activities such as antimicrobial, insecticidal, antitumor, antioxidants, etc. These compounds are usually colored and therefore have application in food, textiles and cosmetics. Shikonin and its derivatives, which are commercially most important of the naphthoquinone pigments, are distributed among members of the family Boraginaceae. These include different species of Lithospermum, Arnebia, Alkanna, Anchusa, Echium and Onosma. The growing demand for plant-based natural products has made this group of compounds one of the enthralling targets for their in vitro production. The aim of this review is to highlight the recent progress in production of shikonins by various biotechnological means. Different methods of increasing the levels of shikonins in plant cells such as selection of cell lines, optimization of culture conditions, elicitation, in situ product removal, genetic transformation and metabolic engineering are discussed. The experience of different researchers working worldwide on this aspect is also considered. Further, to meet market demand, the needs for continuous and reliable production systems, as well as future prospects, are included. [ABSTRACT FROM AUTHOR]

AP9-cd, a novel lignan composition from Cedrus deodara has significant anticancer potential, and to further enhance its activity, it was lucratively encumbered into solid lipid nanoparticles (SLNs). These nanoparticles were formulated by micro-emulsion technique with 70% drug trap competence. AP9-cd-SLNs were regular, solid, globular particles in the range of 100–200 nm, which were confirmed by electron microscopic studies. Moreover, AP9-cd-SLNs were found to be stable for up to six months in terms of color, particle size, zeta potential, drug content and entrapment. AP9-cd-SLNs have 30–50% higher cytotoxic and apoptotic potential than the AP9-cd alone. The augmented anticancer potential of AP9-cd-SLNs was observed in cytotoxic IC 50 value, apoptosis signaling cascade and in Ehrlich ascites tumor (EAT) model. AP9-cd-SLNs induce apoptosis in Molt-4 cells via both intrinsic and extrinsic pathway. Moreover, the dummy nanoparticles (SLNs without AP9-cd) did not have any cytotoxic effect in cancer as well as in normal cells. Consequently, SLNs of AP9-cd significantly augment the apoptotic and antitumor potential of AP9-cd. The present study provides a podium for ornamental the remedial latent via novel delivery systems like solid lipid nanoparticles. [ABSTRACT FROM AUTHOR]

In this article, we introduce the predictive estimation approach for estimating the population mean using modified difference and ratio type predictive estimators in ranked set sampling. The expressions of bias and mean square error of the proffered predictive estimators are reported to the first order of approximation. A comparative study of the proffered predictive estimators with the conventional predictive estimators under simple random sampling and ranked set sampling is considered. The theoretical findings have been supported by a broad spectrum computational study carried out using various real and simulated data sets. Further, the appropriate suggestions are forwarded to the survey professionals. [ABSTRACT FROM AUTHOR]

Chromium (Cr) is considered as the most common ubiquitous pollutant for aquatic animals including fish. An experiment was conducted to determine the acute and chronic toxicity of Cr, pH and high temperature in Anabas testudineus. Lethal concentration (LC 50) of Cr alone was determined as 55.02 mg L−1, Cr and low pH 48.19 mg L−1 and Cr, low pH and high temperature 47.16 mg L−1. The chronic toxicity of low dose of Cr, pH and high temperature (1/10th and 1/20th of LC 50) was designed to execute the experiment for 72 days. The stress enzymes and biomarkers were determined viz. superoxide dismutase, catalase, glutathione peroxidase, glutathione-s-transferase, lipid peroxide, acetylcholine esterase, cortisol, HSP-70, blood glucose, aspartate amino transferase, alanine amino transferase and malate dehydrogenase, lactate dehydrogenase, ATPase and genotoxicity in this study. We had also studied the integrated biomarker response (IBR), which revealed that Cr toxicity enhanced with concurrent exposure to pH and high temperature. All the biochemical attributes were significantly altered with exposure to Cr alone and with low pH and high temperature except gill SOD. Further, thermal tolerance was also determined, and results revealed that thermal tolerance was significantly reduced with exposure to Cr alone and Cr and low pH exposure in A. testudineus. The present study concluded that, the chronic toxicity of Cr is enhanced with low pH and high temperature and it has led to understanding the multi-approach of Cr toxicity which affect, stress biomarkers, cellular metabolic stress and thermal tolerance of A. testudineus. [Display omitted] • LC 50 of Cr, Cr and pH, Cr, pH and temperature in Anabas was 55.02, 48.19, 47.61 mg L−1. • Low dose (1/10th and 1/20th) of Cr, pH and temperature causes oxidative stress, LPO in A. testudineus. • Exposure to Cr alone and with low pH and high temperature induce genotoxicity. • Pre-reared under Cr alone and with low pH reduced thermal tolerance of Anabas. • Pre-reared under Cr, pH and temperature enhanced CTmax and LTmax in Anabas. [ABSTRACT FROM AUTHOR]

Engineered nanoparticles (ENPs) are being increasingly produced as a result of the rapid development in nanotechnology. They are used to generate innovative and versatile goods in a wide range of industrial, medical and public sectors including healthcare, biomedicine, cosmetics, agriculture, transport, energy, materials, and information and communication technologies. Nanomaterials have very unique chemical and physical properties that do suggest potential health hazards, but a limited health and safety information exists for engineered nanomaterials. In vivo and in vitro experimental studies have shown that several types of ENPs (metallic nanoparticles, quantum dots, carbon nanotubes, Zinc oxide, Iron oxide) can have various types of biological effects, some detrimental on the various organs, both acutely and in the long term, resulting in cytotoxicity and/or genotoxicity. This review focus on the possible biological impact of engineered NPs, serving as a reminder that nanomaterials can become a double-edged sword if not handled properly and thus, the current efforts should include research to generate data for safety and nanotoxicological evaluation of potential or putative hazards to the human health in particular and the environment at large. [ABSTRACT FROM AUTHOR]

Background: Cystathionine γ-lyase (CSE) produces H2S via enzymatic conversion of L-cysteine and plays a critical role in cardiovascular homeostasis. We investigated the effects of genetic modulation of CSE and exogenous H2S therapy in the setting of pressure overload-induced heart failure.Methods and Results: Transverse aortic constriction was performed in wild-type, CSE knockout, and cardiac-specific CSE transgenic mice. In addition, C57BL/6J or CSE knockout mice received a novel H2S donor (SG-1002). Mice were followed up for 12 weeks with echocardiography. We observed a >60% reduction in myocardial and circulating H2S levels after transverse aortic constriction. CSE knockout mice exhibited significantly greater cardiac dilatation and dysfunction than wild-type mice after transverse aortic constriction, and cardiac-specific CSE transgenic mice maintained cardiac structure and function after transverse aortic constriction. H2S therapy with SG-1002 resulted in cardioprotection during transverse aortic constriction via upregulation of the vascular endothelial growth factor-Akt-endothelial nitric oxide synthase-nitric oxide-cGMP pathway with preserved mitochondrial function, attenuated oxidative stress, and increased myocardial vascular density.Conclusions: Our results demonstrate that H2S levels are decreased in mice in the setting of heart failure. Moreover, CSE plays a critical role in the preservation of cardiac function in heart failure, and oral H2S therapy prevents the transition from compensated to decompensated heart failure in part via upregulation of endothelial nitric oxide synthase and increased nitric oxide bioavailability. [ABSTRACT FROM AUTHOR]

The article discusses the study on the H2S as a protection against pressure overload-induced heart failure by upregulation of endothelial nitric oxide synthase. It says that the transverse aortic constriction was performed in wild-type, cystathionine and cardiac-specific ϒ-lase (CSE) transgenic mice. Result show that H2S levels are decreased in mice in the setting of heart failure and CSE plays critical role in the preservation of cardiac function in heart failure. INSET: CLINICAL PERSPECTWE.

Abstract: The present study describes anticancer effect of gallic acid based indanone derivative (1). Indanone 1 exhibited in vivo anticancer activity against Erhlich ascites carcinoma in Swiss albino mice by inhibiting tumor growth by 54.3% at 50mg/kg b.wt. It showed antitubulin effect by inhibiting tubulin polymerase enzyme. In cell cycle analysis, it inhibited G2/M phase and induced apoptosis. It significantly suppressed VEGF-R1, VEGF-R2 and HIF-α in human breast cancer MCF-7 cells, thus exhibiting antiangiogenic activity. In acute oral toxicity, indanone 1 was well tolerated and was found to be non-toxic up to 1000mg/kg b.wt. in Swiss albino mice. Pharmacokinetic studies in rabbits revealed rate of absorption, half life, volume of distribution with high plasma and blood clearance after i.v. administration. Indanone 1, is a safe and moderately active anticancer agent. [Copyright &y& Elsevier]