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Poly(ethylene terephthalate) (PET) waste from soft drink bottles was incorporated into palm olein alkyd to produce new polyol for use in polyurethane resins as surface protection on metal surfaces.

Alkyd was prepared from palm olein, glycerol and phthalic anhydride. PET underwent simultaneous glycolysis and transesterification reactions with the alkyd. Varying the amount of PET has led to polyols with different viscosities. Polyurethane resins were produced by reacting the polyols with toluene diisocyanate. The resins were coated on mild steel panels and cured. Performances of the cured films were tested.

The polyurethanes (PU) resin cured to a harder film with better thermal stability. Films showed excellent adhesion properties, while higher content of PET exhibited higher pencil hardness, better water, salt, acid and alkali resistance.

Other vegetable oils could also be used. The alkyd structure could be changed by formulation to have different functionality and the ability to incorporate higher amount of PET waste. Rate of glycolysis of PET could be increased by higher amount of ethylene glycol.

This method has managed to use waste PET in producing new polyol and PU resins. The cured films exhibit good mechanical and chemical properties, as well as excellent adhesion and thermal stability.

The non-biodegradable PET has created environmental pollution problems connected to littering and illegal landfilling. It has become necessary to pay greater attention to recycling PET bottles for obtaining valuable products.

This approach is different from the earlier reports, where PET was recycled to recover the raw materials.

This study aims to assess the household food insecurity in Malaysia during the initial phase of the movement control order (MCO) to provide insights into the prevalence and predictors of food insecurity in this context.

The research used an online cross-sectional survey between March 28 and April 28, 2020. The study collected data from the Radimer/Cornell Hunger Scale and a food insecurity instrument. Analytical tools included chi-square and logistic regression models.

Of the 411 participating households, 54.3% were food-secure, while 45.7% experienced varying food insecurity. Among these, 29.9% reported mild hunger-associated food insecurity, 8.5% experienced individual food insecurity and 7.3% reported child hunger. The study identified predictors for food insecurity, including household income, as those with total income of < RM 2,300 had 13 times greater odds (odds ratio [OR] 13.8; confidence interval [CI] 5.9–32.1; p < 0.001) than those with income of RM 5,600, marital status as divorced (OR 4.4; 95% CI 1.0–19.9; p-value = 0.05) or married (OR 1.04; 95% CI 0.52–2.1) compared to those who are single. Self-employed respondents had three times greater odds of living in a household experiencing food insecurity (OR 3.58; 95% CI 1.6–7.7; p-value = 0.001) than those in the private sector (OR 1.48; 95% CI 0.85–2.61) or experiencing job loss (OR 1.39; 95% CI 0.62–3.1) compared with those who reported being in full-time government employment.

This study acknowledged limitations, such as not considering various dimensions of food insecurity, such as coping strategies, nutritional support, diet quality and well-being, due to the complexity of the issue.

The study underscores the importance of targeted support for vulnerable groups and fostering collaborative efforts to address household food insecurity during crises like the MCOs.

The research offers insights into how to address household food insecurity and its impact on society.

It identifies predictors, quantifies increased odds and emphasizes the necessity of targeted policies and collaborative approaches for fostering resilient recovery and promoting well-being in vulnerable populations.

Institutions, including higher education institutions (HEIs), may use crises as an opportunity to develop, to transform and to improve their institutional resilience. Indeed, the Covid-19 pandemic proves that a vast majority of HEIs around the world effectively adapted to the circumstances of the pandemic and successfully embarked on remote learning. The analysis of HEIs proves as well that the nearly overnight switch to remote learning was but one aspect of the quiet transformation that HEIs worldwide were subdued to. In this context, this chapter identifies the administrative practices, including talent management, operations management, and above all, the organizational culture. The notion of changed expectations on the part of the faculty and the students is highlighted. The key point that this chapter makes is that the faculty and the art of education, rather than simply teaching, need to be placed first if HEIs are to retain their resilience.

The study aims to examine the association between the sustainable development triangle and real earnings management (REM) and the moderating role of business innovation.

The study was based on the quadruple bottom line approach to measuring corporate sustainable development. For the REM, Roychowdhury model is used to identify the practices. The study used panel data using 740 firm-year observations from non-financial listed companies in the Nigerian market from 2011 to 2020, collected from the Nigeria Stock Exchange.

The study finds a negative influence on the association of economic, environmental, social and governance (EESG) on REM in related party transactions. Thus, by regressing the three different components of REM separately, then EESG will have strongest impact as well. The study suggests a bidirectional association between EESG and REM. Furthermore, the study finds that business innovation strengthens the negative association between EESG and REM. The study concludes that sustainable companies in the Nigerian public market are less liable to practice REM.

The study examines only non-financial listed companies quoted on the Nigeria Stock Exchange, which restricts the generalization of the findings.

The findings of the study should be of immense value to the investors who need comprehensive appraisal of earnings quality to enhance sustainable development strategies for sustainable business innovation among Nigeria firms. Thus, sustainability and innovation can serve as the principles for supporting developing countries impacted by the COVID-19 pandemic and supporting a sustainable development.

The study will be of immense value to policymakers, regulators and standard setters who demand for facts insightful of business practices and reporting behaviors for sustainable development.

Existing studies have mainly focused on triple bottom line. This study adds to the existing body of literature on the Quadruple bottom line in an African market. More so, the study investigates the impact of business innovation on the relationship between economic, environmental, social and governance and real earnings management, which was rarely investigated in the prior literature.

Motivated by recent rapid exchange rate depreciations, shrank economic growth, high inflation, and persistent trade deficits, this study examines the trade balance (TB) in the face of the recent dynamics of the stated macroeconomic factors, which are also important determinants of the TB. The symmetric test of the J-curve phenomenon for the selected Sub-Saharan African (SSA) countries is revisited in this regard. The study uses panel data from 1970 to 2020 for ten of these countries for the longitudinal panel analysis with the TB as the dependent variable and the real exchange rate, foreign and domestic national incomes, and trade openness as the set of independent variables.

Because the underlying data set involves a heterogeneous panel of relatively short N and long T, the pooled mean group (PMG) and mean group (MG) heterogeneous panel models are employed based on the Hausman test for parameter consistency in heterogeneous panels.

The findings largely support the domestic income growth– TB worsening and the foreign income growth– TB improvement hypotheses. Trade openness is found to mostly augment the TB performance of the countries. The results also validated the J-curve effect for only 3/10 and 2/10 countries in the PMG and MG models, respectively. The divergence for most of the countries is attributed to possible import compression and institutional structure of SSA countries.

Given the favorable effects of trade openness on the TB performance of SSA countries, it is recommended that SSA countries place much emphasis on import-substitution industrialization and value addition to their natural resources as well as investment-driven growth policies to improve the competitiveness of their exports and reverse the chronic deficits in their TBs.

This paper is unique for invoking heterogeneous panel models to analyze the TB in light of recent dynamics of its determinants, as well as providing an update on the symmetric test of the J-curve phenomenon for the selected SSA countries.

In developing countries, adoption of building information modelling (BIM) concept within the architecture, engineering and construction (AEC) curricula in universities is a relatively new effort, and subsequently, studies on the status of BIM implementation in universities are rare. This study, therefore, becomes imperative with a view to identifying and examining the barriers to the incorporation of BIM into quantity surveying (QS) undergraduate curriculum in Nigerian universities.

The study adopted a questionnaire survey, which was targeted at the academia and students from two selected universities offering QS honours degree programme. Data collected were analysed using mean score, Mann–Whitney test and factor analysis.

The study identified 30 barriers, and the analysis of the ranking revealed that 17 (out of 30) identified barriers were considered as the most serious barriers. The study, through factor analysis, grouped the 30 identified barriers into six major factors.

The findings provide greater insights and empirical evidence on the major barriers to implementation of BIM education in developing countries.

The identified barriers are relevant not only to QS education but also to other related disciplines within the AEC context. These findings would be of great value to academic staff and university management board to develop strategies for incorporating BIM into AEC disciplines curricula in developing countries at large.

Extensive research towards identifying the attributable cost overrun factors globally has been conducted predominantly from a survey-oriented perspective, which disregard the contextual basis on which these triggers manifest. This study aims to explore the driving factors of cost overrun in highway projects, specific to the Nigerian context.

The research used a context-based approach to seek project stakeholders’ perspectives on the key drivers of cost overrun in highway projects in Nigerian. Semi-structured interviews were conducted with client, contractor and consultant organisations involved in the provision of highway infrastructure projects in Nigeria. The collected data was analysed using a developed coding framework grounded on a case study approach, principles of inductive thematic analysis and saliency analysis to identify the key drivers.

Findings from the analysis identified triggers from macroeconomic, societal, leadership and project management perspectives with synergistic relationships with each other based on prevalence and significance. Among the key triggers is a delay in work progress, political instability, adverse weather, social issues, delay in progress payment to contractors and modification of project scope. In conclusion, the triggers of cost overrun in highway projects are contextually driven by the complex nature of the project management, societal, macroeconomic and leadership triggers specific to the Nigerian context.

The research was limited to only highway infrastructure projects in Nigeria. Furthermore, the findings are based on a small sample size, and thus, caution must be taken before applying the outcome of this study in a generalised way to other contexts.

Practically, the stakeholders i.e. client, contractors and consultants should acknowledge the contextual circumstances in which each of the triggers takes place, which will aid in developing pragmatic measures and make the right decisions towards addressing these triggers during any highway construction project in Nigeria and enhance the chances of project success.

The context-based approach applied in this study is expected to provide a new insight in understanding the triggers of cost overruns, especially in highway projects in Nigeria and indeed other developing countries with similar governance characteristics

To investigate the mechanical properties of geopolymer concrete at elevated temperatures.

The investigation involved studying the influence of partially replacing fly ash with ground granulated blast furnace slag (GGBS) at different proportions (5%, 10%, 15%, 20% and 25%) on the composition of the geopolymer. This approach aimed to examine how the addition of GGBS impacts the properties of the geopolymer material. The chemical NaOH was purchased from the local supplier of Jamshedpur. The alkali solution was prepared with a concentration of 12 M NaOH to produce the concrete. After several trials, the alkaline-to-binder ratio was determined to be 0.43.

The compressive strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 35.42 MPa, 41.26 MPa, 44.79 MPa, 50.51 MPa and 46.33 MPa, respectively. The flexural strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 5.31 MPa, 5.64 MPa, 6.12 MPa, 7.15 MPa and 6.48 MPa, respectively. The split tensile strength values at 28 days for specimens FG1, FG2, FG3, FG4 and FG5 are 2.82 MPa, 2.95 MPa, 3.14 MPa, 3.52 MPa and 3.31 MPa, respectively.

This approach allows for the examination of how the addition of GGBS affects the properties of the geopolymer material. Four different temperature levels were chosen for analysis: 100 °C, 300 °C, 500 °C and 700 °C. By subjecting the geopolymer samples to these elevated temperatures, the study aimed to observe any changes in their mechanical.

This study aims to explore the stagnation flow over a shrinking surface in a hybrid nanofluid consists of Al₂O₃ and Cu nanoparticles. Here, the flow is subjected to the magnetohydrodynamic (MHD) and the melting phenomenon effects.

The similarity variables are used to gain the similarity equations. These equations are solved via the bvp4c solver. The effects of several physical parameters on the flow and the thermal characteristics of the hybrid nanofluid are analysed and discussed. Later, the temporal stability analysis is used to determine the stability of the dual solutions obtained as time evolves.

Results show that two solutions are found for the limited range of the stretching/shrinking parameter λ, and then these solutions are terminated at λ=λc. The rise of the melting parameter Me from 0 to 2 contributes to enhance 109.63% of the local Nusselt number Rex-1/2Nux and 3.30% of the skin friction coefficient Rex1/2Cf. Contrarily, the values of Rex-1/2Nux and Rex1/2Cf decline by 25.04% and 5.58%, respectively, as the magnetic parameter Mg increases from 0 to 0.3. Additionally, Al₂O₃-Cu/water has the highest values of Rex1/2Cf and the lowest values of Rex-1/2Nux. Lastly, it is found that the first solution is physically stable as time evolves.

This paper considers the MHD stagnation point flow of a hybrid nanofluid over a shrinking surface with the melting phenomenon effects. Most importantly, it is shown that there exist dual solutions within a specific range of the physical parameters. Besides, the temporal stability of the solutions is also reported in this study. The finding can contribute to foresee the flow and thermal behaviours in industrial applications. Also, the suitable values of parameters can be determined to avoid misjudgement in flow and heat transfer analysis.

The purpose of this study is to compare the prediction models for half-cell potential (HCP) of RCC slabs cathodically protected using pure magnesium anodes and subjected to chloride ingress.The models for HCP using 1,134 data set values based on experimentation are developed and compared using ANFIS, artificial neural network (ANN) and integrated ANN-GA algorithms.

In this study, RCC slabs, 1000 mm × 1000 mm × 100 mm were cast. Five slabs were cast with 3.5% NaCl by weight of cement, and five more were cast without NaCl. The distance of the point under consideration from the anode in the x- and y-axes, temperature, relative humidity and age of the slab in days were the input parameters, while the HCP values with reference to the Standard Calomel Electrode were the output. Experimental values consisting of 80 HCP values per slab per day were collected for 270 days and were averaged for both cases to generate the prediction model.

In this study, the premise and consequent parameters are trained, validated and tested using ANFIS, ANN and by using ANN as fitness function of GA. The MAPE, RMSE and MAE of the ANFIS model were 24.57, 1702.601 and 871.762, respectively. Amongst the ANN algorithms, Levenberg−Marquardt (LM) algorithm outperforms the other methods, with an overall R-value of 0.983. GA with ANN as the objective function proves to be the best means for the development of prediction model.

Based on the original experimental values, the performance of ANFIS, ANN and GA with ANN as objective function provides excellent results.