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The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

Prior studies mostly tested the association between carbon emissions and firm value in certain contexts. This study aims to advance the existing literature by concentrating on three indicators of greening in corporations namely resource use, emissions and eco-innovation, and examining their value relevance in the stock market at the global level. Furthermore, we deepen the investigation by exploring the moderating role of eco-innovation and the CSR committee between greening in corporations and market value.

The data for the study were retrieved from the Thomson Reuters Eikon database for the years between 2002 and 2019 and contain 17,961 firm-year observations which are analyzed through fixed-effects regression.

The results reveal that while resource usage is viewed as value-relevant by the market, the emissions and eco-innovation are not. However, despite eco-innovation per se not being value-relevant, its interaction with resource usage and emissions is value-relevant. Furthermore, CSR committees undertake a very critical role in translating greening practices into market value.

While the results for emissions support the cost-concerned school, the findings for resource usage confirm the value creation school. Furthermore, the interaction effect of eco-innovation and CSR committee confirms the resource-based theory and stakeholder theory, respectively.

Investors regard eco-innovation-induced pro-environmental behaviors as value-relevant. These results propose firms replace eco-innovation at the focal point in developing environmental strategies and connecting other greening efforts to it. Moreover, CSR committees are critical to corporations in translating greening practices into firm value by developing and implementing disclosure and communication strategies.

The study’s originality stems from investigating the synergetic effect that eco-innovation and CSR committees generate in translating greening practices to greater market value at a global scale.

The aim of our study is to explore the nexus between the gender composition of board and firm financial performance. We use the data of 114 listed banks from 10 Asian emerging economies. Data were extracted from the DataStream for the year 2012–2021. We apply fixed effect model to analyze the data. In addition, we use generalized method of moments (GMM) to verify our main findings. We find that both proxies of board gender composition which are the proportion of female board members and the percentage of female executives on the board have a significant impact on banks' financial performance. Findings suggest that female representation on board provides more insights of monitoring and optimal advisory capabilities and, therefore, gender-diversified board enhances firm performance. Females are more active in business matters and take more interests to fulfill their responsibilities. The results of our study provide useful signals for corporate and regulatory policymakers. Board gender disparities between enterprises should be better understood by all stakeholders to have the optimal combination of board members that ultimately lead to better performance of the firm.

This paper aims to solve the problems molybdenum disulfide (MoS₂) nanosheets suffer from inadequate dispersion stability and form a weak lubricating film on the friction surface, which severely limits their application as lubricant additives.

MoS₂/C₆₀ nanocomposites were prepared by synthesizing molybdenum disulfide (MoS₂) nanosheets on the surface of hydrochloric acid-activated fullerenes (C₆₀) by in situ hydrothermal method. The composition, structure and morphology of MoS₂/C₆₀ nanocomposites were characterized. Through the high-frequency reciprocating tribology test, its potential as a lubricant additive was evaluated.

MoS₂/C₆₀ nanocomposites that were prepared showed good dispersion in dioctyl sebacate (DOS). When 0.5 Wt.% MoS₂/C₆₀ was added, the friction reduction performance and wear resistance improved by 54.5% and 62.7%, respectively.

MoS₂/C₆₀ composite nanoparticles were prepared by in-situ formation of MoS₂ nanosheets on the surface of C₆₀ activated by HCl through hydrothermal method and were used as potential lubricating oil additives.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2023-0321/

Cotton fibre lots are graded and selected for yarn spinning based on their quality value which is a function of certain fibre properties. Cotton grading and selection has created a domain of emerging interest among the researchers. Several researchers have addressed the said issue using a few exponents of multi-criteria decision-making (MCDM) technique. The purpose of this study is to demonstrate a cotton selection problem using a recently developed measurement of alternatives and ranking according to compromise solution (MARCOS) method which can handle almost any decision problem involving a finite number of alternatives and multiple conflicting decision criteria.

The MARCOS method of the MCDM technique was deployed in this study to rank 17 cotton fibre lots based on their quality values. Six apposite fibre properties, namely, fibre bundle strength, elongation, fineness, upper half mean length, uniformity index and short fibre content are considered as the six decision criteria assigning weights previously determined by an earlier researcher using analytic hierarchy process.

Among the 17 alternatives, C9 secured rank 1 (the best lot) with the highest utility function (0.704) and C7 occupied rank 17 (the worst lot) with the lowest utility function (0.596). Ranking given by MARCOS method showed high degree of congruence with the earlier approaches, as evidenced by high rank correlation coefficients (Rs > 0.814). During sensitivity analyses, no occurrence of rank reversal is observed. The correlations between the quality value-based ranking and the yarn tenacity-based rankings are better than many of the traditional methods. The results can be improved further by adopting other efficient method of weighting the criteria.

The properties of raw cotton have significant impact on the quality of final yarn. Compared to the traditional methods, MCDM is reported as the most viable solution in which fibre parameters are given their due importance while formulating a single index known as quality value. The present study demonstrates the application of a recently developed exponent of MCDM in the name of MARCOS for the first time to address a cotton fibre selection problem for textile spinning mills. The same approach can also be extended to solve other decision problems of the textile industry, in general.

Novelty of the present study lies in the fact that the MARCOS is a very recently developed MCDM method, and this is a maiden application of the MARCOS method in the domain of textile, in general, and cotton industry, in particular. The approach is very simple, highly effective and quite flexible in terms of number of alternatives and decision criteria, although highly robust and stable.

The “chiralisation” of Euclidean polygonal tessellations is a novel, recent method which has been used to design new auxetic metamaterials with complex topologies and improved geometric versatility over traditional chiral honeycombs. This paper aims to design and manufacture chiral honeycombs representative of four distinct classes of 2D Euclidean tessellations with hexagonal rotational symmetry using fused-deposition additive manufacturing and experimentally analysed the mechanical properties and failure modes of these metamaterials.

Finite Element simulations were also used to study the high-strain compressive performance of these systems under both periodic boundary conditions and realistic, finite conditions. Experimental uniaxial compressive loading tests were applied to additively manufactured prototypes and digital image correlation was used to measure the Poisson’s ratio and analyse the deformation behaviour of these systems.

The results obtained demonstrate that these systems have the ability to exhibit a wide range of Poisson’s ratios (positive, quasi-zero and negative values) and stiffnesses as well as unusual failure modes characterised by a sequential layer-by-layer collapse of specific, non-adjacent ligaments. These findings provide useful insights on the mechanical properties and deformation behaviours of this new class of metamaterials and indicate that these chiral honeycombs could potentially possess anomalous characteristics which are not commonly found in traditional chiral metamaterials based on regular monohedral tilings.

To the best of the authors’ knowledge, the authors have analysed for the first time the high strain behaviour and failure modes of chiral metamaterials based on Euclidean multi-polygonal tessellations.

This paper analyzes the direct effect of financial development and the mediating impact of financial development through foreign direct investment (FDI), foreign aid and trade on economic growth for all Asian countries.

A fixed-effect model with Driscoll–Kraay panel corrected estimators was employed to find the direct and mediating impact of financial developments on growth for all 47 Asian economies from 1980 to 2020. The bootstrapped panel-quantile regression (BPQR) model is used to check how this effect varies for different income groups of countries.

The results demonstrated that financial development positively impacts countries' economic growth. The interaction effect of financial development with FDI, foreign aid and foreign trade negatively impacts economic growth. The BPQR results showed that FDI and foreign aid help in the growth of lower quantile economies; however, the impact is negative for middle- and upper-income countries. Trade impacts growth positively for all the quantiles of economies.

The results suggest that the Asian economies must continue to provide thrust on the financial development of their own countries to achieve better growth. It also implied that the dependence on external finance is good for low-income countries and not advisable for middle- and upper-income countries.

To the best of the authors’ knowledge, the current study is the first to provide empirical evidence on analyzing both the direct and interaction effect of financial development on economic growth by considering all the Asian economies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0587

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This paper aims to investigate the corrosion resistance of two types of coatings – one is ceria sol coating and the other is ceria sol coating modified by ZnO nanoparticles on 7075 aluminum alloy in 3.5% NaCl solution.

Aluminum alloys were dipped into ceria sol and ceria sol modified by ZnO nanoparticles separately and removed after 10 min from the solutions and dried at 110°C for 30 min and heated at 500 °C for 30 min to form the coatings. The coatings have been characterized by using field emission scanning electron microscopy (FE-SEM), electrochemical impedance spectroscopy (EIS), X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS). The EIS tests were performed in a corrosive solution of 3.5% NaCl.

The results showed that the coating of ceria sol modified by ZnO nanoparticles has higher corrosion resistance than the ceria sol coating and the bare sample. Also, the best efficiency is related to aluminum sample immersion after 1 h in NaCl corrosive solution for coating modified by ZnO nanoparticles.

In this research, the modification of ceria sol coating by ZnO nanoparticles had an effect on improving the corrosion behavior of aluminum alloy. It is also understood that modification of coatings is an effective parameter on corrosion resistance.

This paper aims to map the research on management accounting (MA), clarifying its current role and identifying gaps and opportunities for future research.

In this paper, 784 papers were reviewed for the 1958–2019 period, published in 220 scientific journals indexed on Clarivate Analytics’ Web of Science (Science Citation Index Expanded [SCI-EXPANDED] and Social Sciences Citation Index [SSCI]). In the process, content analysis, regression analysis and bibliometric analysis were used.

The most relevant journals, authors and topics in MA, along with trends and patterns in the literature, were identified. Seven clusters that represent the overall thematic research structure of the MA field were also identified. This study shows that MA is becoming a multidimensional management decision-support instrument covering all organizational dimensions. As such, the research on MA is following the recent concerns with the sustainable development and digitalization of business processes.

Based on the findings of this research study, theoretical and practical implications for MA researchers were provided. These findings could also be useful to industry practitioners to improve their knowledge of emerging trends in MA practices, strategies and concepts.

Based on bibliometric and content analysis, a framework that shows an organizational, market and social context for the evolution of MA over the past 60 years was provided. It highlights the dynamics of MA alignment with organizational and external environment changes. Future research opportunities and implications for researchers and practitioners were also identified.