This paper investigates strategies to address climate change by promoting sustainable energy technologies and consumption practices. It examines renewable energy sources such as solar, wind, and geothermal and their potential to reduce greenhouse gas emissions. The study also explores energy optimization techniques, focusing on genetic algorithms (GAs) and smart energy systems like smart grids and microgrids, which enhance energy efficiency and sustainability. The research highlights the role of the circular economy in fostering sustainable consumption through recycling and waste management. Furthermore, the paper explores the economic trade-offs between energy consumption and environmental harm, focusing on the impact of both renewable and fossil fuel energies. A dual methodological approach is employed: first, an endogenous growth model excluding environmental factors, followed by a modified version incorporating environmental considerations. Using a continuous genetic algorithm and data from 2000 to 2025, the study forecasts the optimal trajectory for renewable energy’s share in global energy consumption under two scenarios. The findings suggest that by 2025, renewable energy could represent 82.4% of the total energy consumption under environmental constraints, up from the current share of 45%. This growth is hindered by challenges like droughts, which impact hydropower production. The study concludes that achieving a sustainable energy transition requires comprehensive policies integrating renewable energy expansion, energy efficiency, and environmental protection. These findings provide important insights into optimizing energy pathways for economic growth and environmental sustainability. They also serve as a foundation for future research and policy recommendations, aiming to ensure a low emission future by balancing the need for energy consumption with the preservation of the environment.

Objective: This study aims to explore the relationships among hopelessness, cognitive flexibility, intolerance of uncertainty, and perceived stress in a non-clinical sample by proposing a multiple mediation model. It was suggested that hopeless individuals have low cognitive flexibility and high intolerance of uncertainty; consequently, they are more likely to perceive stress. Method: The participants of this study comprised 302 university students (46.7% female and 53.3% male) between 18 and 40 years of age who were recruited from a state university in Turkey. To collect data, Beck Hopelessness Scale, Cognitive Flexibility Inventory, Intolerance of Uncertainty Scale, and Perceived Stress Scale were applied. Results: The results showed that hopelessness is negatively correlated with cognitive flexibility and positively correlated with intolerance of uncertainty and perceived stress. Cognitive flexibility has been found to be negatively correlated with intolerance of uncertainty and perceived stress. There is also a positive correlation between intolerance of uncertainty and perceived stress. The mediation of cognitive flexibility and intolerance of uncertainty in the relationship between hopelessness and perceived stress is also statistically significant in the model, and all variables explain approximately 37.0% of the variance in perceived stress. Conclusion: The findings of the study are considered to provide a guide for mental health professionals and researchers. Amaç: Bu araştırma klinik olmayan bir örneklemde, çoklu aracılık modeli önererek umutsuzluk, bilişsel esneklik, belirsizliğe tahammülsüzlük ve algılanan stres arasındaki ilişkileri incelemeyi amaçlamaktadır. Araştırmada umutsuz bireylerin düşük düzeyde bilişsel esnekliğe ve yüksek düzeyde belirsizliğe tahammülsüzlüğe sahip olduğu; dolayısıyla algılanan stres düzeylerinin daha yüksek olacağı varsayılmıştır. Yöntem: Araştırmanın katılımcıları Türkiye’deki bir devlet üniversitesine devam eden ve yaşları 18 ile 40 arasında olan 302 öğrenciden (%46.7’si kadın % 53.3’ü erkek ) oluşmaktadır. Verilerin toplanmasında, Beck Umutsuzluk Ölçeği, Bilişsel Esneklik Envanteri, Belirsizliğe Tahammülsüz Ölçeği ve Algılanan Stres Ölçeği kullanılmıştır. Bulgular: Araştırma bulguları, umutsuzluğun bilişsel esneklik ile negatif yönde, belirsizliğe tahammülsüzlük ve algılanan stres ile pozitif yönde ilişkili olduğunu göstermiştir. Bilişsel esneklik; belirsizliğe tahammülsüzlük ve algılanan stres ile negatif yönde ilişkili bulunmuştur. Ayrıca belirsizliğe tahammülsüzlük ve algılanan stres arasında pozitif yönde ilişki vardır. Bilişsel esneklik ve belirsizliğe tahammülsüzlüğün, umutsuzluk ve algılanan stres arasındaki ilişkide aracılığı istatistiksel olarak anlamlıdır ve tüm değişkenler algılanan stresteki varyansın yaklaşık %37’sini açıklamaktadır. Tartışma: Araştırma sonuçlarının ruh sağlığı alanında çalışan profesyoneller ve araştırmacılar için yol gösterici olacağı düşünülmektedir.

This study presents a novel approach to managing the cost–time–quality trade-off in modern agriculture by integrating fuzzy logic with a genetic algorithm. Agriculture faces significant challenges due to climate variability, economic constraints, and the increasing demand for sustainable practices. These challenges are compounded by uncertainties and risks inherent in agricultural processes, such as fluctuating yields, unpredictable costs, and inconsistent quality. The proposed model uses a fuzzy multi-objective optimization framework to address these uncertainties, incorporating expert opinions through the alpha-cut technique. By adjusting the level of uncertainty (represented by alpha values ranging from 0 to 1), the model can shift from pessimistic to optimistic scenarios, enabling strategic decision making. The genetic algorithm improves computational efficiency, making the model scalable for large agricultural projects. A case study was conducted to optimize resource allocation for rice cultivation in Asia, barley in Europe, wheat globally, and corn in the Americas, using data from 2003 to 2025. Key datasets, including the USDA Feed Grains Database and the Global Yield Gap Atlas, provided comprehensive insights into costs, yields, and quality across regions. The results demonstrate that the model effectively balances competing objectives while accounting for risks and opportunities. Under high uncertainty (α = 0\alpha = 0α = 0), the model focuses on risk mitigation, reflecting the impact of adverse climate conditions and market volatility. On the other hand, under more stable conditions and lower market volatility conditions (α = 1\alpha = 1α = 1), the solutions prioritize efficiency and sustainability. The genetic algorithm’s rapid convergence ensures that complex problems can be solved in minutes. This research highlights the potential of combining fuzzy logic and genetic algorithms to transform modern agriculture. By addressing uncertainties and optimizing key parameters, this approach paves the way for sustainable, resilient, and productive agricultural systems, contributing to global food security.

Lamiaceae (Labiatae) is the third largest family in Turkey. It is represented by 48 genera and 782 taxa ( 603 species, 179 subspecies and varieties) in the country, 346 taxa ( 271 species, 75 subspecies and varieties) of which are endemic. Endemism ratio is ca. % 44. The largest genera in the country based on the taxon number are Stachys L.(118 taxa), Salvia L.(107 taxa), Sideritis L.(54 taxa), Phlomis L.(53 taxa), Teucrium L. (49 taxa), Thymus L.(47 taxa). Endangered genera according to IUCN criteria; Salvia L.(43 taxa), Stachys L.( 19 taxa) Thymus L. (16 taxa), Sideritis L.(14 taxa), Teucrium L. (10 taxa), Lamium L.(8 taxa), Phlomis L. and Scutellaria L. ( 7 taxa), Micromeria Bentham and Nepeta L. ( 6 taxa), Ajuga L.and Origanum L. (5 taxa), Marrubium L..( 4 taxa), Acinos Miller, Satureja L. and Calamintha Miller (2 taxa), Ballota L., . Dorystaechas Boiss. & Heldr. ex Bentham, Cyclotrichium (Boiss.)Manden. & Scheng. and Lopanthus Adans.(1 taxon). Lamiaceae has 160 taxa endangered in Turkey of which are categories; 43 taxa critically endangered, 59 taxa endangered and 58 taxa vulnerable. Phytogeographic distribution of rare and endemic Turkish Lamiaceae taxa are 79 taxa in the Mediterranean, 63 taxa in the Irano-Turanien, 5 taxa in the Euro-Siberian phytogeographic region, and 11 taxa in unknown or multiregional phytogeographical elements.

This article looked at the situation of university teachers in Poland during the COVID-19 epidemic as a result of their need to work remotely. The study was conducted in the first stage (I) on 21 academicians and in the second stage (II) on 18 academicians. The study was conducted to determine the level of productivity of the study group in their online learning competencies in relation to their well-being, as well as during the height, and weakening of the epidemic. The results of the survey conducted, especially during the height of the epidemic, indicated varying levels of self-evaluation of their productivity in relation to their digital competencies linked to the need for them to work remotely, which also affected their psychological well-being. Several cases of respondents indicated a negative assessment of their own productivity, and thus their quality of work life and sense of psychological well-being. However, some respondents, on the contrary, showed a desire to work, the need for self-improvement, and to continue their mission of teaching.