A corncob-derived magnetic solid acid catalyst was synthesized through the sulfonation method and an impregnation process, respectively. In the sulfonation process, the concentrated H2SO4 was utilized as an activation agent to obtain acidic properties. The solution of ferric sulphate-ferrous sulphate was utilized for impregnation to generate the magnetic behaviour of the material. The prepared magnetic acid solid catalyst had a high saturation magnetisation value of 16.48 emu/g and a total acidity of 1.43 mmol/g. The performance of the catalyst was evaluated in the esterification reaction of waste cooking oil. The best result presented 86.12% FFA conversion under reaction conditions of 5% catalyst loading and a 1:15 oil-to-methanol molar ratio at 60oC for 4 h. The catalyst was separated magnetically from the reaction solution and exhibited a good reusability with 61% remaining active after 5 consecutive cycles of reaction. This study resulted in a promising method to obtain magnetic-sulfonated carbon-based catalyst from corncob residue, and it is economical potentially and environmentally friendly for the esterification of low-quality feedstock for biodiesel production.

The peach tree is a very water-demanding species that is affected by water stress, which is worsening due to global warming. The soil environment is also influenced by tillage and cropping methods, which affect the water content, temperature, aeration, and organic matter of the soil. Weed control is one of the most crucial cultural practices in arboriculture since weeds can compete with fruit trees for resources. This paper aims to measure the impact of water stress combined with different soil maintenance methods on vegetative growth and peach tree production. Different evapotranspiration conditions (ETc) were used. Two irrigation doses R1 (80% of ETc) and R2 (100% of ETc) were combined with three soil maintenance modes T1 (Sapping), T2 (Sickle tillage), and T3 (Chemical maintenance). The findings highlighted water stress reduces the growth and development of the peach tree but did not have a significant impact on yield when the irrigation dose was reduced by 20%. The sapping and sickle maintenance modes recorded the best results for most of the parameters, while the chemical maintenance mode had a positive effect on the total number of fruits and yield under the 100% of ETc water regime.

This research aims to improve problem-solving abilities regarding the greenhouse effect using project-based learning methods supported by Science, Technology, Engineering, and Mathematics (STEM)-Education for Sustainable Development (ESD)-based teaching materials. The study was conducted in multiple phases: (i) utilizing a pretest to gauge students' prior knowledge, (ii) employing the project-based learning approach to teach the greenhouse effect, and (iii) assessing students' final knowledge (with a posttest). The research was completed with the observation of temperature variations in a greenhouse prototype. Students monitored and recorded temperature changes over time. Students' problem-solving abilities increased significantly after being treated using project learning assisted by STEM-ESD teaching materials, imparting more information through the media by stimulating students' curiosity and interest in science subjects.

A significant difference test is used to evaluate certain treatments on the sample in two different observation periods. One of the commonly used software is SPSS which is used to analyze data which helps researchers in calculating data so that it can be completed quickly. However, there are still many students and researchers who are not experts in calculating data using SPSS software, especially significant difference tests. This article aims to provide a step-by-step guide in calculating data using SPSS for statistical requirements and significant difference tests. To understand the calculations well using SPSS, we demonstrate the requirements tests (i.e., normality and homogeneity tests), parametric significant difference tests (i.e., One Sample t-test, Paired sample t-test, and Independent Sample t-test), and non-parametric (i.e., Wilcoxon test and Mann-Whitney test). We also added and demonstrated the steps for calculating data in the field of education with the variables analyzed being differences in student learning outcomes. We used the data when delivering the steam engine concept to students, showing how statistical calculation can understand students' comprehension. Bibliometric analysis regarding statistics was also added. This paper can be used as a guide in carrying out statistical tests using SPSS software.

HC-SR04 ultrasonic sensor is one of the famous low-cost sensors. It is measured distance from 2 to 400 cm. It depends on ultrasonic sound waves that are sent by an electronic device to determine the distance of the object, and the reflected sound is converted into an electronic signal. This paper proposed a flowchart of the modern optimization method Pelican Optimization Algorithm (POA) to enhance the distance measurement of ultrasonic sensor kind HC-SR04. In addition, the experimental system designed and interfacing between MATLAB with Ardunio is implemented to easily save the measured and desired distances and enter these distances into the POA as pelicans. The error comparison between two methods implemented, one method called the classical method, and another method is proposed named POA. The results show the minimum distance error between ultrasonic and object in POA is less than the error without POA. The best-measured distance results were achieved and approximately equal to the desired distances. The proposed method of POA for ultrasonic distance sensor enhanced by 99.97%. This sensor accurately detects objects from 2 to 400 cm which can be used in a robotic application.

Spatial ability, an essential skill in modern education, is on par with language and computing abilities. However, the definition and categorization of spatial ability are still unclear, requiring further development in assessment practices and research. The factors influencing spatial ability are still being explored, and assessments across different cultures and backgrounds need refinement. Results show a significant correlation between spatial visualization ability, gender, and major, with males and STEM majors scoring higher. Other factors, like students' prior spatial experience, did not show a significant correlation. These findings help identify and evaluate students' spatial visualization ability levels, guiding the design of spatial thinking courses and supporting differentiated teaching. The assessment also serves as a measure to track changes in students' spatial visualization ability before and after the course.

The advantages of reusability, lower cost, and environmentally friendly operation have made the heterogeneous catalyzed methylic process a preferable alternative to the homogeneously catalyzed protocol. The optimal production yield of palm kernel shell oil (PKSO) methyl ester (PKSOME) was modeled using Response Surface Methodology (RSM). The cost of PKSOME was determined, and the synthesized PKSOME was blended with diesel fuel with various volume ratios. Several analyses were done, including thermophysical properties using ASTM test methods, density and viscosity, fire point and flash point, aniline point, and acid value. Emission characteristics such as exhaust smoke, carbon monoxide, and carbon dioxide were measured using an IC engine. The use of waste eggshells for heterogeneously catalyzed biodiesel from underutilized PKSO for green diesel can reduce production costs even further. The green biodiesel model and TP correlations have applications in the biodiesel and aviation industries.

This research examines the viability of incorporating a second-life lithium-ion battery energy storage system with a solar photovoltaic power source to facilitate energy acquisition in two irrigation scenarios at a durian farm located in Thailand. The first option entails selecting the battery with suitable dimensions to effectively harness solar energy following morning irrigation, while the second option involves sizing the battery specifically for storing solar energy solely for the purpose of powering the motor pump. This study conducts an analysis on the degradation of the battery, focusing on the influence of specific environmental conditions and its specification. The degradation analysis employs polynomial functions as an alternative to exponential semi-empirical stress models for fitting stress models. This approach demonstrates a robust fit, as evidenced by a high R-squared value of approximately 1. The economic analysis considers various factors, including solar irradiance derating factors, battery deterioration rate, and photovoltaic power ratings for all scenarios. The sensitivity analysis evaluates the variations in irradiance and costs associated with the battery. When solar radiation levels surpass 500 W/m2 and the cost of the battery remains below $100/kWh, the estimated payback period is approximately 5 years over the duration of the 10-year project lifespan.

The research problem centered around the need to enhance students' computational thinking (CT) ability, which is crucial for their success in the present and future. This study aims to examine the efficacy of Augmented Reality (AR) in improving the CT abilities of seventh-grade junior high school students. The study utilized a quasi-experimental design with a control group and an experimental group to meet the research aims. The control group was provided with conventional mathematical instruction through established teaching methods, while the experimental group was exposed to mathematics learning enhanced by AR media. The study involved 160 students from four junior high schools located in one of the cities in Indonesia. A five-question CT ability test was employed as the research instrument. The mean difference test was used to analyze the data and compare the performance of the control and experimental groups. The research findings indicated that the effective application of AR media significantly enhanced the CT skills of seventh-grade adolescents in middle school. The results aid in creating new teaching approaches and emphasize the possibilities of AR technology in math education.