Articles in Press

---

Summary:
This study aims to explore the opportunities, challenges, principles, and approaches in climate change education through a systematic analysis of 10 scientific articles published in the last five years in Scopus-indexed journals. The findings indicate that the main opportunities for climate change education include student engagement as agents of change, the strategic role of teachers, supportive learning environments, curriculum integration, science education, and supportive government policies. However, significant challenges remain, such as improving teacher competency, material complexity, limited curriculum tools, collaboration between stakeholders, and gaps between student knowledge and skills. In addition, six main principles of climate change education implementation were found, including improving teacher competency, curriculum adjustment, cross-sector collaboration, student environmental awareness, providing knowledge related to climate change, and connecting learning with contextual issues. Student-based learning approaches, such as inquiry-based learning, problem-based learning, and project-based learning, have proven effective in delivering complex and contextual materials.

---

Summary:
Approximately one-third of the food produced for human consumption is wasted each year, which is a major problem worldwide. An estimated 23–48 million tons of food is wasted annually in Indonesia, impacting the economy and the environment. In this regard, education is crucial to raise awareness of the effects of food waste among the younger generation. The purpose of this study was to identify trends in the use of interactive media, such as educational games and digital applications, and evaluate how effective they are in raising students' awareness and understanding of the waste problem in academic settings. This study also systematically reviewed the literature and assessed the impact of interactive media on students' behavior. The results of the analysis indicate that interactive media can help students learn about food waste. This study provides suggestions for better educational practices and suggests the integration of interactive media into formal curricula to create sustainable behavioral changes among students. However, there are still challenges in terms of developing application features and sustaining behavioral changes. This study provides recommendations for better educational practices and proposes the integration of interactive media into formal curricula to create sustainable behavioral changes among students.

---

Summary:
Drought is a complex natural phenomenon resulting from prolonged periods of below-average precipitation. Its gradual development over large areas makes it challenging to determine its onset, duration, and overall impact accurately. In this study, an artificial neural network (ANN) method-based model was developed to predict the standard precipitation index (SPI), an index commonly used to determine drought severity. SPI12 which reflects a meteorological drought indicator to monitor precipitation anomalies over 12-month accumulation periods were estimated based on artificial neural network (ANN) method using monthly precipitation data recorded in the 1980-2015 period for Kayseri. The North Atlantic Oscillation Index (NAOI), Mediterranean Oscillation Index (MOI), and Arctic Oscillation Index (AOI), which represent large-scale global cycles, were used as input variables in the models. A multilayer perceptron-type ANN model with a single hidden layer was chosen. The model training used 70% of the data and a scaled conjugate gradient backpropagation algorithm. The remaining 30% of the data were used for model testing and control. The activation functions of the ANN model and the number of neurons in the hidden layer were determined using the trial-and-error method. The performances of the models were evaluated using the mean Nash-Sutcliffe coefficient of efficiency (NSE), root square error (RMSE), and coefficient of determination (R2) of agreement between the estimated and observed SPI12 values. This study demonstrated that drought conditions can be successfully predicted at 3, 6, and 12 months in advance using indices that reflect large-scale global climate anomalies.

---

Summary:
Biogas processes play an important role in the disposal of organic waste. However, these processes are difficult to control because they are highly sensitive and variable. A lot of work has been done to date in order to eliminate this problem. With the development of technology and artificial intelligence, the spread of “Autonomous” systems has become widespread in the control of anaerobic processes as in many other fields. The Anaerobic Digestion Model No. 1 (ADM1) developed by the International Water Association (IWA) has been adopted as the standard model for the AD process since 2002. With the development of this model, Simple Regression Tree (SRT), Probabilistic Neural Networks (PNN), Artificial Neural Networks (ANN), Gradient Boosted Tree (GBT), Linear Regression (LR), Tree Ensemble Regression (TER), Random Forest Regression (RFR), Polynomial Regression (PR), Fuzzy Logic (FL), Adaptive Network-Based Fuzzy İnference System (ANFIS), Different ML algorithms such as Support Vector Machine (SVM), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) Developing Data-Driven Models (DDDV), Deep neural network (DNN) have been used in various studies and tried to perform process optimization, real-time monitoring, disturbance detection and parameter estimation. In this study, with the help of bibliometric analysis, the development of ML models in biogas processes is examined and solutions are presented.

---

Summary:
. Flow and thrust calculations at supersonic speeds require intensive formulas and general assumptions, thus prolonging the preliminary design process. Today, the use of computer programs for aerodynamic design and analysis is inevitable in the development of aircraft. However, in this process, traditional calculation methods are mostly used. By performing the relevant calculations with a source code, time-consuming problems such as data extraction from tables, interpolation or calculation with formulas can be avoided. In this study, a computational tool was created in Python using the formulas contained in compressible flow theory. For the calculation, ISA (International Standard Atmosphere) and altitude values are first obtained from the user to determine the atmospheric conditions. These conditions are known to directly affect static conditions. Then, the data input of one of the selected parameters is made and the remaining parameters according to these input values are presented on the result screen together with the other outputs. These outputs were compared with NASA data and their accuracy was analysed. Two different configurations were created to examine the dependence of compressible flow calculations on atmospheric conditions. In the first one, constant ISA and different altitude values were analysed, while in the other one, constant altitude and different temperature deviations were evaluated. These evaluations revealed the sensitivity of the calculation results to atmospheric variables. The findings provide critical data on how to design and analyse aircraft under different operational conditions. This study, for the first time, provides calculations based on atmospheric variables, enabling them to efficiently obtain the values of parameters that depend on these data. This approach is an innovative contribution to the existing literature, expanding the body of knowledge on the analysis of compressible flows.

---

Summary:
Biogas and biomethane are renewable gases that should be strongly considered to accelerate decarbonization and reduce greenhouse gas emissions in many sectors. In addition, biomethane is important to provide renewable and more economical energy to consumers using the existing gas infrastructure. Moreover, biomethane can be easily stored and can be used as a balancer for intermittent renewable energy sources such as solar and wind. The EU considers bio-CNG (compressed), bio-LNG (liquefied) fuels to be an effective method in reducing emissions. Therefore, Europe leads the world in biogas and biomethane production. In this study, evaluations and general views were made about the definition of biogas and biomethane, production amounts in the world and purification methods (treatment) of biogas. The main purpose of the current study is to emphasize that biogas provides an important solution for decarbonization and that its usage areas can be expanded by purifying it as biomethane.