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To evaluate the performance of a reactive diluent, nonylphenyl methacrylate (NPM) for toughness improvement of bisphenol‐a‐glycidyl dimethacrylate (BisGMA) and to optimise the results of such a modification.

To achieve desirable rheological and physico‐mechanical properties of BisGMA/NPM network, various compositions were made by incorporating different concentrations of NPM. The effect of concentration on the impact and the adhesive strengths of the unmodified and modified BisGMA networks were characterised.

The modification of BisGMA resin using NPM showed significant enhancement of the impact and the adhesive strengths over the unmodified one. The modification caused a chemical linkage between NPM and BisGMA resin, which led not only to a phase separation but also to establishing the intrinsically strong chemical bonds across the NPM phase/resin matrix interphase, which was responsible for the improvement of the impact and adhesive strength. The optimum results were obtained at 10/h (parts per 100 parts of BisGMA resin) of modifier.

The reactive diluent, used in the present context was synthesised from nonyl phenol, methacrylic acid and benzoyl chloride in methyl ethyl ketone using triethylamine as base.

The method of modification developed provides a simple and practical solution for improving the rheological and physico‐mechanical properties of BisGMA network.

The method developed is a novel one for enhancing the rheological and physico‐mechanical properties of BisGMA network diluted with NPM resin and may find numerous applications in surface coating and adhesive.

This paper aims to study the temporal and spatial variation of vegetation and the influence of climate change on vegetation coverage in the Yellow River basin, China. The current study aimed to evaluate the role of a series of government-led environmental control projects in restoring the ecological environment of the Yellow River basin.

This paper uses unary linear regression, Mann–Kendall and wavelet analyses to study the spatial–temporal variations of vegetation and the response to climate changes in the Yellow River, China.

The results showed that for the past 17 years, not only the mean annual increase rate of the Normalized Difference Vegetation Index (NDVI) was 0.0059/a, but the spatial heterogeneity also yields significant results. The vegetation growth in the southeastern region was significantly better than that in the northwestern region. The variation period of the NDVI in the study area significantly shortened, and the most obvious oscillation period was half a year, with two peaks in one year. In addition, there are positive and negative effects of human activities on the change of vegetation cover of the Loess Plateau. The project of transforming cultivated land to forest and grassland promotes the increase of vegetation cover of the Loess plateau. Unfortunately, the regional urbanization and industrialization proliferated, and the overloading of grazing, deforestation, over-reclamation, and the exploitation and development of the energy area in the grassland region led to the reduction of the NDVI. Fortunately, the positive effects outweigh the negative ones.

This paper provides a comprehensive insight to analysis of the vegetation change and the responses of vegetation to climate change, with special reference to make the planning policy of ecological restoration. This paper argues that ecological restoration should be strengthened in areas with annual precipitation less than 450 mm.

Recently, fractional differential equations have been used to model various physical and engineering problems. One may need a reliable and efficient numerical technique for the solution of these types of differential equations, as sometimes it is not easy to get the analytical solution. However, in general, in the existing investigations, involved parameters and variables are defined exactly, whereas in actual practice it may contain uncertainty because of error in observations, maintenance induced error, etc. Therefore, the purpose of this paper is to find the dynamic response of fractionally damped beam approximately under fuzzy and interval uncertainty.

Here, a semi analytical approach, variational iteration method (VIM), has been considered for the solution. A newly developed form of fuzzy numbers known as double parametric form has been applied to model the uncertainty involved in the system parameters and variables.

VIM has been successfully implemented along with double parametric form of fuzzy number to find the uncertain dynamic responses of the fractionally damped beam. The advantage of this approach is that the solution can be written in power series or compact form. Also, this method converges rapidly to have the accurate solution. The uncertain responses subject to impulse and step loads have also been computed and the behaviours of the responses are analysed. Applying the double parametric form, it reduces the computational cost without separating the fuzzy equation into coupled differential equations as done in traditional approaches.

Uncertain dynamic responses of fuzzy fractionally damped beam using the newly developed double parametric form of fuzzy numbers subject to unit step and impulse loads have been obtained. Gaussian fuzzy numbers are used to model the uncertainties. In the methodology using the alpha cut form, corresponding beam equation is first converted to an interval-based fuzzy equation. Next, it has been transformed to crisp form by applying double parametric form of fuzzy numbers. Finally, VIM has been applied to solve the same for the general fuzzy responses. Various numerical examples have been taken in to consideration.

With the development of research toward damage detection in structural elements, the use of artificial intelligent methods for crack detection plays a vital role in solving the crack-related problems. The purpose of this paper is to establish a methodology that can detect and analyze crack development in a beam structure subjected to transverse free vibration.

Hybrid intelligent systems have acquired their own distinction as a potential problem-solving methodology adopted by researchers and scientists. It can be applied in many areas like science, technology, business and commerce. There have been the efforts by researchers in the recent past to combine the individual artificial intelligent techniques in parallel to generate optimal solutions for the problems. So it is an innovative effort to develop a strong computationally intelligent hybrid system based on different combinations of available artificial intelligence (AI) techniques.

In the present research, an integration of different AI techniques has been tested for accuracy. Theoretical, numerical and experimental investigations have been carried out using a fix-hinge aluminum beam of specified dimension in the presence and absence of cracks. The paper also gives an insight into the comparison of relative crack locations and crack depths obtained from numerical and experimental results with that of the results of the hybrid intelligent model and found to be in good agreement.

The paper covers the work to verify the accuracy of hybrid controllers in a fix-hinge beam which is very rare to find in the available literature. To overcome the limitations of standalone AI techniques, a hybrid methodology has been adopted. The output results for crack location and crack depth have been compared with experimental results, and the deviation of results is found to be within the satisfactory limit.

Because of the 2008 global financial crisis aftermaths, economic downturn and prolonged recession, several OECD countries have adopted an austerity compound by significantly reducing public health expenditure (PHE) for dealing with their fiscal pressure and sovereign-debt challenges. Against this backdrop, this study aims to examine the responsiveness of PHE to macro-fiscal determinants, demography, as well to private health insurance (PHI) financing.

The authors gather annual panel data from four international organizations databases for the total of OECD countries from a period lasting from 2000 to 2017. The authors apply static and dynamic econometric methodology to deal with panel data and assess the impact of several parameters on PHE.

The authors’ findings indicate that gross domestic product, fiscal capacity, tax revenues and population aging have a positive effect on PHE. Further, the authors find that both unemployment rate and voluntary private health insurance financing present a negative statistically significant impact on our estimated outcome variable. Different specifications and sample periods applied in the regression models reveal how inseparably associated are PHE and OECD's economies compliance on macro-fiscal policies for offsetting public finances derailment.

Providing more evidence on the responsiveness of PHE to several macro-fiscal drivers, it can be a helpful tool for governments to reconsider their persistence on fiscal adjustments measures and rank public health financing to the top of their political agenda. Health systems policies for meeting Universal Health Coverage (UHC) objectives, they should also take into consideration the voluntary PHI institution, especially for economies with insufficient fiscal capacity to raise public health financing.

To the best of knowledge, the impact of unemployment and voluntary PHI funding on public health financing, apart from other macro-fiscal and demographical parameters effect, remains unnoticed in the existing published studies on the topic.

This study aims to document the participation of intra-household decision-making activities by older adults in India.

This study has used a nationally representative sample of 21,662 older adults (aged 60 and above) from the Longitudinal Ageing Study of India data of 2017–2018. Intra-household decision-making participation is measured based on decision-making activities that includes marriage of daughter/son, buying and selling of property, giving a gift to the family, education of family member and arrangement of social/religious events. This paper used bivariate analysis and binary logistic regression model to examine the factors associated with the participation of older adults in the intra-household decision-making activities.

The result has shown that older persons’ participation declined with increased age. This study has also found a difference in the participation of intra-households decision-making activities between male and female, rural and urban older adults, poor and rich older adults. Older adults with good health status who maintain social engagement and a good lifestyle are more likely to participate in the household’s decision-making activities.

Older adults with better economic and social status are more likely to participate in intra-household decision-making activities that make their life happier than the counterpart. Therefore, emphasis should be given to those vulnerable older adults who do not have any social and economic security in the society.

There are limited studies available on intra-household decision-making participation by older adults. This paper documents the intra-household decision-making participation by older adults in India with a nationally representative large sample.

Vibration of large membranes has great utility in engineering application such as in important parts of drums, pumps, microphones, telephones and other devices. So, to obtain a numerical solution of this type of problems is necessary and important. In general, in existing approaches, involved parameters and variables are defined exactly. Whereas in actual practice, it may contain uncertainty owing to error in observations, maintenance-induced error, etc. So, the main purpose of this paper is to solve this important problem numerically under fuzzy and interval uncertainty to have an uncertain solution and to study its behaviour.

In this study, the authors have considered a new approach is known as double parametric form of fuzzy number to model uncertain parameters. Along with this a semianalytical approach, i.e. variational iteration method, has been used to obtain uncertain bounds of the solution.

The variational iteration method has been successfully implemented along with the double parametric form of fuzzy number to find the uncertain solution of the vibration equation of a large membrane. The advantage of this approach is that the solution can be written in a power series or a compact form. Also, this method converges rapidly to obtain an accurate solution. Various cases depending on the functional value involved in the initial conditions have been studied and the behaviour has been analysed. Applying the double parametric form reduces the computational cost without separating the fuzzy equation into coupled differential equations as done in traditional approaches.

The vibration equation of large membranes has been solved under fuzzy and interval uncertainty. Uncertainties have been considered in the initial conditions. New approaches, i.e. variational iteration method along with the double parametric form, have been applied to solve the vibration equation of large membranes.

The purpose of this paper is to find the solution of classical nonlinear shallow-water wave (SWW) equations in particular to the tsunami wave propagation in crisp and interval environment.

Homotopy perturbation method (HPM) has been used for handling crisp and uncertain differential equations governing SWW equations.

The wave height and depth-averaged velocity of a tsunami wave in crisp and interval cases have been obtained.

Present results by HPM are compared with the existing solution (in crisp case), and they are found to be in good agreement. Also, the residual error of the solutions is found for the convergence conformation and reliability of the present results.

To evaluate the efficiency of modifying epoxy resin using phenol‐nonyl phenol based polymer (PNPF) for toughness improvement and optimise the results of such a modification.

For effective toughening, various compositions were made by incorporating PNPF at different concentrations. The impact and adhesive strengths of the unmodified and modified epoxy networks were characterised.

The modification of epoxy resin using PNPF showed significant enhancement of impact and adhesive strengths over the unmodified one. The modification caused the formation of a chemical linkage between PNPF and resin which led not only to a phase separation, but also to formation of intrinsically strong chemical bonds across the PNPF phase/resin matrix interphase, which was the main cause of the improved impact and adhesive strengths. The optimum results were obtained at 10 phr (parts per 100 parts of epoxy resin) of modifier.

The modifier, PNPF, used in the present context was synthesised from phenol, nonyl phenol and formalin using oxalic acid as catalyst.

The developed method provided a simple and practical solution to improving the toughness of a cured epoxy.

The method for enhancing toughness of a cured epoxy was novel and could find numerous applications in the surface coating and adhesive.

Social networking platforms are increasingly using the Follower Link Prediction tool in an effort to expand the number of their users. It facilitates the discovery of previously unidentified individuals and can be employed to determine the relationships among the nodes in a social network. On the other hand, social site firms use follower–followee link prediction (FFLP) to increase their user base. FFLP can help identify unfamiliar people and determine node-to-node links in a social network. Choosing the appropriate person to follow becomes crucial as the number of users increases. A hybrid model employing the Ensemble Learning algorithm for FFLP (HMELA) is proposed to advise the formation of new follower links in large networks.

HMELA includes fundamental classification techniques for treating link prediction as a binary classification problem. The data sets are represented using a variety of machine-learning-friendly hybrid graph features. The HMELA is evaluated using six real-world social network data sets.

The first set of experiments used exploratory data analysis on a di-graph to produce a balanced matrix. The second set of experiments compared the benchmark and hybrid features on data sets. This was followed by using benchmark classifiers and ensemble learning methods. The experiments show that the proposed (HMELA) method predicts missing links better than other methods.

A hybrid suggested model for link prediction is proposed in this paper. The suggested HMELA model makes use of AUC scores to predict new future links. The proposed approach facilitates comprehension and insight into the domain of link prediction. This work is almost entirely aimed at academics, practitioners, and those involved in the field of social networks, etc. Also, the model is quite effective in the field of product recommendation and in recommending a new friend and user on social networks.

The outcome on six benchmark data sets revealed that when the HMELA strategy had been applied to all of the selected data sets, the area under the curve (AUC) scores were greater than when individual techniques were applied to the same data sets. Using the HMELA technique, the maximum AUC score in the Facebook data set has been increased by 10.3 per cent from 0.8449 to 0.9479. There has also been an 8.53 per cent increase in the accuracy of the Net Science, Karate Club and USAir databases. As a result, the HMELA strategy outperforms every other strategy tested in the study.