Digital and Sustainable Micro-Housing for Urban Youth: Developing a User-Centered Structural Model of Social, Spatial, and Technological Preferences in Istanbul

This study investigates how spatial comfort and flexibility, social integration, and digital infrastructure shape sustainable micro-housing preferences among young adults aged 18-35 in the Beşiktaş district of Istanbul. It develops and empirically tests a user-centered micro-housing model informed by participatory design principles and broader debates on safe, affordable, and inclusive urban housing.Grounded in Self-Determination Theory, the Capability Approach, and the Unified Theory of Acceptance and Use of Technology, the study employed a two-phase design. In the first phase, survey data from 410 participants were analyzed using chi-square tests, one-way analysis of variance, exploratory factor analysis, and covariance-based structural equation modeling in order to identify the spatial, social, and technological drivers of digital micro-housing preferences. In the second phase, qualitative feedback from 51 participants was thematically coded and used to further assess and refine the proposed typology. The analysis combined chi-square tests, one-way analysis of variance, Tukey’s honestly significant difference test, exploratory factor analysis, and covariance-based structural equation modeling, with mediation effects evaluated through bootstrap resampling. The final model demonstrated acceptable overall fit.The findings show that technological infrastructure and energy efficiency were the strongest predictors of willingness to live in digital micro-housing, followed by spatial comfort and flexibility, and safety and social cohesion. Together, these factors explained substantial variation in housing satisfaction and willingness to live, while housing satisfaction also played a significant mediating role.This study offers an empirically grounded, user-centered model for understanding digital micro-housing preferences among young adults in Beşiktaş, Istanbul. By integrating Self-Determination Theory, the Capability Approach, and the Unified Theory of Acceptance and Use of Technology within a single analytical framework, it contributes to a more multidimensional understanding of sustainable and participatory housing. The findings indicate that technological infrastructure, spatial flexibility, and socially secure shared environments play a central role in shaping housing satisfaction and willingness to live in digital micro-housing, highlighting their importance for youth-oriented housing design.</p

Experimental Investigation of the Effect of Cavity Joining Technique of Gas Ovens on Energy Consumption and the Environment

This article aims to show the effect of the joining technique of the sheet metal parts of a cavity on energy consumption, energy efficiency class, and environmental impact in domestic gas ovens. An oven cavity can be joined by screwing or welding the metal parts. Experiments were carried out on two identical prototypes, which only differed in the joining method used to assemble the cavity. The energy consumption of the oven with the welded cavity is found to be 12.00–14.22% less than that of the oven with the screwed cavity. The energy efficiency classes of the two ovens were determined. According to the energy efficiency index (EEI) averages of the prototypes, the oven with a screwed cavity (EEI =112.92) is in class B, and the oven with a welded cavity (EEI= 98.38) is in class A. In order to show the environmental impact of the appliances, the carbon footprint of the ovens for nonintense and intense use over a period of 1 year and 10 years was determined. It was found that the carbon footprint from ovens with screwed cavities is 12.92% higher than that of ovens with welded cavities due to excess fuel consumption.[</p

Generating landslide archive inventories for Türkiye using web scraping and natural language processing techniques

Landslides are among the most frequent natural hazards that cause significant loss of life and serious economic damage worldwide. Although many inventories have been created using different approaches to understand landslide events, these inventories are rarely updated automatically or in real time. Traditional approaches are time-consuming and labor-intensive and are often limited in timeliness because of reporting delays. To address these challenges, we developed an automated approach that integrates web scraping, natural language processing (NLP), and geocoding techniques using digital media news sources in Türkiye to create a landslide archive inventory. Our algorithm verified 1727 of the 3051 news articles it captured between 1997 and 2024 as landslides and identified a total of 478 fatalities in 212 deadly incidents. A total of 66.5% of the landslides captured on the web were located at the neighborhood/village level, providing substantial spatial accuracy. This location accuracy also enabled risk estimation at the neighborhood/village level. A comparison with the manual national inventory revealed moderate agreement, with F1 scores ranging from 0.434 to 0.552 in the ± 1 and ± 7 daytime windows, respectively. The automated method not only captures spatial and temporal patterns of landslides but also extracts key attributes such as location, number of fatalities, and triggering factors (i.e., natural and anthropogenic). Our study demonstrates the potential of web-based automated approaches to complement traditional landslide inventories by providing near-real-time and verifiable data. Finally, we suggest adopting common reporting standards for natural hazard digital newspapers so that this approach can be applied globally