The performance of bituminous materials is mainly affected by the prevailing maximum and minimum temperatures, and their mechanical properties can vary significantly with the magnitude of the temperature changes. The given effect can be observed from changes occurring in the bitumen or asphalt mixture stiffness and the materials’ serviceable life. Furthermore, when asphalt pavement layer are used, the temperature changes can be credited to climatic factors such as air temperature, solar radiation and wind. Thus in relevance to the discussed issue, the contents of this paper displays a comprehensive review of the collected existing 38 prediction models and broadly classifies them into their corresponding numerical, analytical and statistical models. These models further present different formulas based on the climate, environment, and methods of data collection and analyses. Corresponding to which, most models provide reasonable predictions for both minimum and maximum pavement temperatures. Some models can even predict the temperature of asphalt pavement layers on an hourly or daily basis using the provided statistical method. The analytical models can provide straight-forward solutions, but assumptions on boundary conditions should be simplified. Critical climatic and pavement factors influencing the accuracy of predicting temperature were examined. This paper recommends future studies involving coupled heat transfer model for the pavement and the environment, particularly consider to be made on the impact of surface water and temperature of pavements in urban areas.

Pro-environmental behavior in addressing climate change is influenced by multi-dimensional factors—knowledge, values, intention and sociodemographic background. Correlational studies between environmental values and environmental behaviors have not been able to determine values or behaviors that need to be given priority in future interventions. Therefore, this study firstly determined the environmental values and pro-environmental behavior that are easy or difficult to embrace by 152 respondents with low socioeconomic background. Secondly, we identified the extent pro-environmental behavior is triggered by environmental values. This survey study employs the Rasch analysis model. The respondents had difficulty in associating themselves with biospheric values however readily demonstrated consideration toward altruistic values, especially related to concerns for future generations. In terms of environmental conservation behavior, the respondents were not willing to relinquish comfort easily, such as giving up self-driving and taking public transportation or reducing usage of electricity. In addition, adults of low socioeconomic background find it difficult to endorse statements such as getting involved in campaigns related to environmental conservation. Thus, younger family members must be educated about conservation behaviors such as environmental campaigns commonly offered at schools, and these youngsters can be encouraged to extend their role by educating their parents.

This paper reports the use of a numerical solution of nanofluid flow. The boundary layer flow over a stretching sheet in combination of two nanofluids models is studied. The partial differential equation that governs this model was transformed into a nonlinear ordinary differential equation by using similarity variables, and the numerical results were obtained by applying the shooting technique. Copper (Cu) nanoparticles (water-based fluid) were used in this study. This paper presents and discusses all numerical results, including those for the local Sherwood number and the local Nusselt number. Additionally, the effects of the nanoparticle volume fraction, Brownian motion Nb, and thermophoresis Nt on the performance of heat transfer are discussed. The results show that the stretching sheet has a unique solution: as the nanoparticle volume fraction φ (φ = 0), Nt (Nt = 0.1), and Nb decrease, the rate of heat transfer increases. Furthermore, as φ (φ = 0) and Nb decrease, the rate of mass transfer increases. The data of the Nusselt and Sherwood numbers were tested using different statistical distributions, and it is found that both datasets fit the Weibull distribution for different values of Nt and rotating φ.

Examination is one of the important elements in measuring the student achievement and to determine whether the course learning outcome is achieved or not. The best exam paper is the paper that can evaluate the students’ achievement and thus satisfy the course learning outcome. The purpose of this study is to compare the examination papers and identify whether the course learning outcome is achieved or not based on the performance of students in the examinations. The sample is stratified according to year 1 until 4 and according to the program. The students are selected from three academic years 2015/2016, 2016/2017 and 2017/2018. The data is obtained from the marks of their mid-semester and final exams. Difficulty and discrimination indices is evaluated for each item in the exam paper. The research findings found that the ideal question for the mid-semester exam is from the session 2017/2018 with difficulty and discrimination indices range from 0.4 to 0.8. While the ideal question for final semester exam is from session 2016/2017 with difficulty index in range 0.4-0.6 and higher discrimination index as compared to other sessions. As a result, the student performance for 2017/2018 session has increased significantly in the overall assessment with 13.0% obtained grade A compared to 11.1% in 2016/2017 and only 4.9% in 2015/2016. The failure rate has also reduced at only 11.4% in 2017/2018 compared to 32.1% in 2015/2016 and 11.9% in 2016/2017.

Understanding the mechanical properties of materials is essential in science and engineering to enhance product durability, safety, and performance, and to prevent structural failures. This study applies fractal analysis to investigate vibration signals recorded by piezo film sensors during impact testing on four square-shaped materials: brass, copper, mild steel, and stainless steel. Using an impact hammer, each material was subjected to impact forces ranging from 300N to 800N. Vibration data was captured and analyzed in MATLAB using a box-counting algorithm to calculate fractal dimensions. The findings revealed a notable correlation between the calculated fractal dimensions and two critical mechanical properties, Poisson’s ratio and Young’s modulus. The fractal dimension is inversely ordered relative to the Poisson’s ratio values of the materials, while the order of the fractal dimension aligns with the order of Young’s modulus values. This suggests that materials with higher Young’s modulus values also display higher fractal dimensions, whereas materials with higher Poissons ratios exhibit lower fractal dimensions. These insights indicate that fractal analysis of vibration signals provides a reliable,efficient, and cost-effective alternative to conventional methods for evaluating material properties. This approach holds significant potential for non-destructive testing applications, especially in fields requiring rapid and economical material assessments, such as aerospace, automotive, and construction.