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This paper aims to investigate the ability of traditional biopolymers, such as funori or the nanoscale form of cellulose nanocrystals, to consolidate fragile paper and preserve it for as long as possible.

Degraded papers dating back two centuries were separated into paper samples for consolidation processes. Funori – a marine spleen – was used as a traditional consolidation material and a mixture with ZnO NPs compared with modern materials, such as cellulose nanocrystals. The samples were aged for 25 years, examinations and analyses were performed using scanning electron microscopy and color change was assessed using the CIELAB system, X-ray diffraction and Fourier-transform infrared spectroscopy.

According to the results, using traditional materials to consolidate damage, such as funori, after aging resulted in glossiness on the surface, a color change and increased water content and oxidation. Furthermore, samples treated with a mixture of ZnO NPs and funori revealed that the mixture improved the sample properties and increased the degree of crystallization. Cellulose nanocrystals improved the surface, filled gaps, formed bridges between the fibers and acted as a protector from aging effects.

This paper highlights the ability of nanomaterials to enhance the properties of materials as additives and treat the paper manuscripts from weaknesses.

To enhance the tribological properties of nanogrease, one of the new technologies was used to synthesize a nanogrease having carbon nanotubes (CNTs) nanoparticles (NPs) with different concentrations. The microstructures of the synthesized NPs were characterized and evaluated by x-ray diffraction spectroscopy (XRD) and transmission electron microscopy (TEM). Tribological properties of the nanogrease were evaluated using a four-ball tester. The worn surface of four steel balls was investigated by scanning electron microscopy (SEM) and energy dispersive x-ray spectroscopy (EDX).

Grease was dissolved in chloroform (10 Wt.%), at 25 °C for 1 h. In parallel, functionalized CNTs with different volume concentrations (0.5, 1, 2 and 3 Wt.%) were dispersed in N, N-dimethylformamide. The mixture was stirred for 15 min and then sonicated (40 kHz, 150 W) for 30 min. After that, the mixture was added to the grease solution and magnetically stirred for 15 min and then sonicated for 2 h.

The results suggested that CNTs can enhance the antiwear and friction properties of nanogrease at 0.5 Wt.% CNTs to about 57 and 48 per cent, respectively. In addition, the weld load of the base oil containing 0.5 Wt.% CNTs was improved by 17 per cent compared with base grease.

This work describes the inexpensive and simple fabrication of nanogrease for improving the properties of lubricants, which improve power efficiency and extend lifetimes of mechanical equipment.

This work describes the fabrication of composite nanogrease based on carbon nanotubes (CNTs) as an additive at different volume concentrations 0, 0.5, 1, 2 and 3 Wt.% and investigates the correlation between CNTs and grease rheological behaviour. In addition, study the influence of shear thinning rate at various temperatures and investigates the thermal conductivity of nanogrease. The results demonstrated that grease behaves like a Newtonian viscoelastic material with a narrow linear domain. The thermal conductivity of nanogrease was enhanced by about 31.58 per cent, and the thermal and mechanical stabilities improved. Moreover, the apparent viscosity and dropping point increased by about 93 and 27 per cent, respectively.

Grease was dissolved in chloroform (10 Wt.%), at 25°C for 1 h. In parallel, functionalized CNTs with different volume concentrations (0.5, 1, 2 and 3 Wt.%) were dispersed in N,N-dimethylformamide; the dispersion was stirred for 15 min, and then sonicated (40 kHz, 150 W) for 30 min. Grease solution was then added to the CNTs. The nanofluid was magnetically stirred for 15 min and then sonicated for 2 h. This ensured uniform dispersion of nanoparticles in the base fluid.

Inexpensive and simple fabrication of nanogrease. Thermal conductivity of nanogrease was typically enhanced compared to other reported studies. Apparent viscosity and dropping point increases with the increase the volume concentration.

This work describes the inexpensive and simple fabrication of nanogrease for improving properties of lubricants, which improve power efficiency and extend lifetimes of mechanical equipment.

The study aims to assess the efficiency of nanocomposite to improve the properties of gap-filling materials for pottery artifacts.

Five different pastes were used in the laboratory studies. The pastes consist mainly of pottery powder (grog), dental plaster, microballoons and an adhesive of Primal AC33, nano-silica and nano kaolinite in various concentrations. The prepared samples were subjected to accelerated heat and light aging. Besides, some investigations were used to evaluate the efficacy of the additive nanomaterials, such as TEM, digital and scanning electron microscopy microscopes. Contact angle, color change, shrinkage degree, physical properties and compressive strength tests were also conducted.

The results indicated that using Nano-silica considerably improves the mechanical strength and decreases the shrinkage of gap-filling materials. According to the results, a mixture of grog, microballoons and Primal AC33/Nano-silica Nanocomposites is the optimal gap-filling paste for archaeological pottery. Moreover, this paste showed a higher contact angle (120°), lower color change (ΔE = 2.62), lower shrinkage (3.3%), lower water absorption (3.36%), lower porosity (5.05%) and higher compressive strength (5124 N/mm²).

This paper attains to develop an economic polymer-nanocomposite that can be used with gap-filling materials for pottery artifacts.

This paper extends the authors’ previous research work investigating resilience for municipal infrastructure from an asset management perspective. Therefore, this paper aims to formulate a pavement resilience index while incorporating asset management and the associated resilience indicators from the authors’ previous research work.

This paper introduces a set of holistic-based key indicators that reflect municipal infrastructure resiliency. Thenceforth, the indicators were integrated using the weighted sum mean method to form the proposed resilience index. Resilience indicators weights were determined using principal components analysis (PCA) via IBM SPSS®. The developed framework for the PCA was built based on an optimization model output to generate the required weights for the desired resilience index. The output optimization data were adjusted using the standardization method before performing PCA.

This paper offers a mathematical approach to generating a resilience index for municipal infrastructure. The statistical tests conducted throughout the study showed a high significance level. Therefore, using PCA was proper for the resilience indicators data. The proposed framework is beneficial for asset management experts, where introducing the proposed index will provide ease of use to decision-makers regarding pavement network maintenance planning.

The resilience indicators used need to be updated beyond what is mentioned in this paper to include asset redundancy and structural asset capacity. Using clustering as a validation tool is an excellent opportunity for other researchers to examine the resilience index for each pavement corridor individually pertaining to the resulting clusters.

This paper provides a unique example of integrating resilience and asset management concepts and serves as a vital step toward a comprehensive integration approach between the two concepts. The used PCA framework offers dynamic resilience indicators weights and, therefore, a dynamic resilience index. Resiliency is a dynamic feature for infrastructure systems. It differs during their life cycle with the change in maintenance and rehabilitation plans, systems retrofit and the occurring disruptive events throughout their life cycle. Therefore, the PCA technique was the preferred method used where it is data-based oriented and eliminates the subjectivity while driving indicators weights.

The purpose of this paper is to evaluate the influence of nanoparticles as an additive on the tribological properties of calcium grease.

The nano additives in this research are with different concentration of multi carbon nanotubes (MWCNTs) and Talc powder (1, 2, 3, 3 and 5 per cent). The ratio of MWCNTs to Talc powder is 1:1. The tribological properties of hyper MWCNTs/Talc powder to calcium grease were evaluated using a pin-on-disk wear testing. The results show that the nano additives MWCNTs/Talc to calcium grease exhibit good performance in anti-wear and friction reduction. The action mechanism was estimated through analysis of the worm surface with x-ray diffraction and transmission electron microscope.

The result indicates that boundary film mainly composed of MWCNT and Talc powder, and other organic compound was formed on the worm surface during the friction test. In addition, the wear rate and coefficient of friction of nanogreases have shown excellent improvement about 80.62 and 63.44 per cent, respectively, at 4 Wt.% of MWCNTs/Talc powder. Moreover, the thermal conductivity of nanogrease increased about 51.72 per cent.

This study describes the inexpensive and simple fabrication of nanogrease for improving properties of lubricants, which improve power efficiency and extend lifetimes of mechanical equipment.

The purpose of this paper is to investigate the rheological characteristics of graphene nanoplatelets (GNPs) and hybridized nanocomposite consisting of multi-walled carbon nanotubes (MWCNTs) and GNPs as an additive on lithium-based grease. The experiments of nanogrease are examined in different values of shear stress, apparent viscosity, temperature and shear rate using Brookfield Programmable Rheometer DV-III ULTRA and characterized by high-resolution transmission electron microscope (HRTEM) and X-ray diffraction (XRD).

First, GNPs was mixed well with lithium grease using mechanical stirring at 3,500 rpm for 15 min at room temperature to form a homogenous composite at different concentrations (0.5, 1, 1.5, 2 and 2.5 Wt.%). Afterwards, MWCNTs and GNPs are mixed and dispersed well in the lithium grease using a sonication path for 30 min and mechanical stirring at 3,500 rpm for 15 min at 28°C to form a homogenous nanocomposite.

The results indicated that 1 Wt.% of GNPs is the optimum concentration. Subsequently, the weight percentage of additives varying between MWCNTs and GNPs are tested, and the result indicate that the grease containing GNPs had a 75 per cent increase in shear stress and 93.7 per cent increase in apparent viscosity over ordinary grease.

This work describes the inexpensive and simple fabrication of nanogrease for improving properties of lubricants, which improve power efficiency and extend lifetimes of mechanical equipment.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

The purpose of this study is to provide a comprehensive analysis on the economic relationship between trade openness and economic growth and to identify current developments, potential research area and future directions. The emphasis is on the identification of annual growth of publications, country-wise distribution, publication pattern, intellectual structure and cluster analysis of scientific production in this field.

This study used evaluative techniques, text mining approach and performance analysis to identify possible patterns and correlation and to measure the impact of authors/citations/scientific production. Further, this study used the bibliometric mapping to represent the structural features of scientific production. This study emphasized on identification of the research hotspots based on occurrence of indexed keywords, productive researchers and journals during 2000–2022. Further, cluster analysis is performed using VOS viewer to analyze the current dynamics and future direction of the association between trade openness and economic growth (Eck and Waltman, 2011). Also, co-citation analysis is used in this study to identify the relations among authors or journals or documents using citation data, whereas the bibliographic coupling/mapping is intended to analyze the citing documents. Similarly, co-word analysis is used to study the article keywords that are mainly used to assess the conceptual structure of a concerning subject.

Economic growth is a function of trade openness, and it is important to analyze the relationship between trade openness and economic growth. Trade openness tends to become more liberalized over time, to contribute more to economic growth. Empirical evidence suggested that there exists a strong association between trade openness and economic growth. Further, keyword timeline analysis illustrated that the linkage between trade openness and economic growth is current area of interest among researchers. As per bibliometric analysis, China, Pakistan and Malaysia are the three most prolific countries in the terms of published articles on this theme. However, the most influential publications based on h-index and citation on trade openness–economic growth relationship is produced by Turkey. Based on cluster analysis, this study suggests that researchers are currently working on trade openness–economic growth relationship with other variables such as FDI, financial development, labor force, environment degradation and carbon emission, while in future, researchers could work on variables such as technology and sustainable development.

There are some limitations of this study. The first limitation is the authors have used Scopus database, leaving the possibility for future research to use Web of Science, Google Scholar or other similar sources. The second limitation is that the authors have used search terms “trade openness “and “economic growth,” although research could be performed using synonyms or even relevant terms in other languages.

Cluster analysis suggested that researchers are currently working on trade openness–economic growth relationship with other variables such as FDI, financial development, labor force, environment degradation and carbon emission, while in future, researchers could work on variables such as technology and sustainable development. Therefore, this study identified the potential research area in this research domain.

To confirm the originality of this study, to the best of the authors’ knowledge, this is the first study to combine bibliometric analysis and cluster analysis on trade openness–economic growth relationship. This study makes a comparison with phenomena/processes/events in contemporary economic and social reality in the field of trade openness and economic growth relationship.