The goal of this study is to generate designerly solutions for improving the culture of healthy food consumption in Tehran, Iran through cultural-historical activity theory. Even though individuals might make conscious decisions to consume healthy food, their environment might prevent them from doing so. Given the current lack of attention toward a holistic viewpoint that considers obese target users, healthy nutrition, and specifications of a target society, therapy procedures recommended by therapists as well as general healthy nutrition policies have been made useless and much less effective. The case study in this research was conducted on patients with obesity and preliminary studies show lack of success of patients, regardless of their nutrition program recommended by therapists. Observations were interpreted that unhealthy nutrition habits and obesity would not be changed just based on a calorie variable as being calculated in diets, but social, cultural and psychological factors do have an important role in generating obesity, and the disregard for considering such factors have resulted in divergence of patients between health centers, sports clubs, and monitoring groups (whether physicians or nutritionists). The hypothesis generated from such observations would signify that considering cultural-social context and generating a useful model (considering effective variables), together with treatment procedures, would help the patient reach a successful goal. Expansive design was chosen as the design approach in order to emphasize continuing the relation between users and providers of service, even after obtaining the service by a user. This viewpoint and design resulted in the dialogue between user and provider of the service or product. Based on the research, three solution scenarios were generated: considering promoting healthy nutrition culture through schools, general promotion strategies in media and society, and a collective treatment system. Based on priorities and requirements, the third scenario, designing a collective treatment center was chosen and conceptualized through tools such as system map, interaction storyboard, and consumer satisfaction diagram. The value of such a study is based on presentation and institutionalizing the theoretical infrastructures in the area of service design, while diverse solutions would be presented to specialists based on scenario-based design as well.

Due to the lack of fossil fuels, there is a significant demand to employ renewable energy systems (RES) worldwide. This paper proposes designing an optimized RES for a remote microgrid that relies solely on solar and wind sources. The proposed RES aims to provide reliable and efficient energy to the microgrid by using machine learning algorithms to forecast the power output of the solar and wind sources. This forecasting will help the system to anticipate and adjust to changes in the weather patterns that may affect the availability of solar and wind. In addition, the system advisor model (SAM) software is used to design the hybrid solar/wind system, considering factors such as the size of the microgrid and the available resources. The system comprises a 60-kW wind system of ten turbines and a 100-kW PV system spread out over the houses. The results show that random forest regression (RFR) models achieved a high level of accuracy in predicting solar power generation, as evidenced by their low mean squared error (MSE) and high R² values. Additionally, a proposed hybrid system can generate enough energy to meet the area's needs.