The determinants of both perceived walkability and walking satisfaction have been studied frequently in the past years. However, less is known on how they relate to each other. This study addresses this research gap and investigates how perceived walkability may impact walking satisfaction. As part of an EU project, we surveyed respondents in three case study cities: Dortmund, Gothenburg and Genoa. By using the validated and tested Short Perceived Walkability Scale (SPWS) and Satisfaction with Travel Scale (STS), we first analysed how walking satisfaction differs according to varying levels of perceived walkability. In a second step, we applied hierarchical linear regression models, exploring effects of perceived walkability on walking satisfaction while controlling for socio-demographics, trip characteristics and walking attitudes. Finally, we explored the determinants of walking satisfaction for various travel purposes. The results suggest that walking satisfaction is significantly affected by various types of perceived walkability. Respondents with high levels of perceived walkability are more satisfied with their walking trip than respondents with low(er) levels of perceived walkability. Additionally, mobility restrictions, trip duration, walking attitudes and weather conditions seem to influence walking satisfaction, albeit differently according to trip purpose. Our findings suggest that policy makers should focus on improving (perceived) walkability levels in order to increase walking satisfaction and stimulate more frequent walking.
Traditional solar stills have low evaporation rates and low thermal efficiency which limits their practical applicability in decentralized production of freshwater. Corrugated absorber designs have become a promising passive approach to improve heat transfer through the augmentation of the effective surface area and by encouraging the evaporation of thin films. A systematic review (2020-2026) conducted in accordance with the PRISMA guidelines is presented in the study, which combines experimental evidence with a single mathematical modeling approach that adds a corrugation factor (ϕ) to measure geometry-enhanced heat transfer. It has been shown by the analysis that corrugated absorbers are much more effective than the traditional flat-plate designs, and the productivity of these absorbers improves by 28-300%. Hybrid systems with V-corrugated absorbers with nanofluids and phase change materials attain thermal and exergy efficiencies of up to 78 and 93% respectively. Economically, levelized water prices are 0.0038‐0.042 $/L, payback period is frequently less than 1.5 years, which proves a high cost-effectiveness. Environmental analysis also underscores the huge potential of CO2 mitigation and the attendant carbon credit incentive. The review finds that corrugated absorber solar stills, especially when combined with novel materials like nano-enhanced phase change materials, nanofluids, and wicking structures are highly efficient economically feasible and scalable alternative to sustainable desalination. Other important research gaps such as geometry optimization, multi-physics model, and intelligent control strategies are also outlined to inform future development.
Natural disturbances are fundamental in shaping forest ecosystems, yet management decisions in production forests can aggravate or mitigate their impacts. Understanding the interplay between forest adaptation strategies and susceptibility to damage is important for sustainable forest management. Here, we review the scientific literature to explore the relationship between natural disturbances and the impact of forest adaptation strategies on the forest susceptibility to damage. To do so we reviewed seven different adaptation strategies (mixed-species stands, shorter rotations, longer rotations, few or no thinnings, logging residue removal, prescribed burning and uneven-aged forestry), and how they affect forest susceptibility to damage by ten different disturbances. Each of the strategies offers opportunities to improve the forest's resilience to damage in different ways and against specific disturbances. A combination of these strategies may have a greater impact on reducing forest susceptibility to damage. The review informs the development of adaptation strategies considering relevant forest characteristics coupled to natural disturbances.
Accurate species delimitation and identification are crucial for assessing biodiversity and conserving species. The Diachrysia cryptic moth complex, comprising D. chrysitis and D. stenochrysis, exhibits overlapping morphological traits, complicating species identification and rendering their status as distinct species debatable. We applied a target enrichment approach leveraging 1753 nuclear single-copy orthologs to clarify their relationships and test the power of this method in addressing complex taxonomic questions. Phylogenetic and population structure analyses revealed clear nuclear differentiation between the two taxa, contrasting with the variability in wing pattern observed within each species. We also detected rare cases where the mitochondrial DNA barcode region (COI) is shared between the species. This discordance between genetic and morphological variation suggests that wing pattern alone is often unreliable for species diagnosis. Our study advances understanding of the evolutionary and speciation history of Diachrysia and provides an efficient genomic model for addressing complex taxonomic questions of recently diverged sibling taxa.
Lean Six Sigma (LSS) helps to enhance environmental performance (EP), which helps to adopt environmental sustainability-related practices and augment operational productivity by focusing on organizational waste elimination and defect reduction. Although the successful adoption of LSS has numerous benefits for small and medium-sized enterprises (SMEs), which ultimately help improve EP. This study examines Organizational Cultural Practices (OCP) and Sustainable Supply Chain Management (SSCM) as the mediating variables between LSS and EP. Our dataset is extracted from 382 respondents from Pakistani SMEs, whom we approached through LinkedIn, an industrial engineering consultancy, and professional training centers. We used three different software packages for data analysis, including Smart-PLS, Jamovi, and the Statistical Package for the Social Sciences. We executed Structural Equation Modeling, Confirmatory Factor Analysis, and an Artificial Neural Network Modeling (ANNM) to analyze relationships among LSS, OCP, SSCM, and EP. The results confirm that LSS positively influences EP at (beta=0.245, p<0.001), with OCP and SSCM acting as partial mediators at (beta=0.173, p<0.001), and (beta=0.201, p<0.001) respectively, and R-2 for EP is 0.649. Moreover, we found that the ANNM results have RMSE of 0.429 for training and 0.428 for testing. This study extends the literature of Goal Setting Theory.
