Technological Educational Institute of Western Macedonia

Barley (Hordeum vulgare L.) seed quality traits were evaluated to investigate the relative genetic and environmental contributions to their variation, the stability of genotypes across environments, and the interrelationships among traits. Fifteen genotypes, including classical pedigree-derived lines (G1–G5), PYI-selected lines (G6–G10), YC-selected lines (G11–G12), cultivars (G13–G14), and a local population (G15), were assessed for crude protein content, fat content, ash content, starch content, crude fiber content, carbohydrate content, soluble fraction, and non-starch fraction. Field trials were conducted across six environments under a randomized complete block design with four replications per environment. Combined ANOVA revealed significant differences among genotypes for all evaluated traits, while environmental effects and genotype × environment interactions also contributed significantly to trait variation. Stability analysis using the Stability Index (SI) showed that classical pedigree lines (G1–G5) demonstrated the highest overall stability across most traits. Lines selected via the Plant Yield Index (PYI) and Yielding Coefficient (YC) criteria exhibited greater stability compared to the local population, while cultivars showed intermediate and trait-dependent stability. Broad-sense heritability (H2) was high for all traits (>92%), with crude protein, fat, ash, and crude fiber content showing particularly strong genetic control. Genetic advance (GA) and genetic advance as a percentage of the mean (GA%) indicated a favorable expected response to selection for protein- and fiber-related traits. Traits such as starch content, carbohydrate content, soluble fraction, and non-starch fraction were more strongly influenced by environmental variation, highlighting the need for multi-environment testing. Correlation analysis revealed significant associations among traits, highlighting both trade-offs and coordinated accumulation patterns. Crude protein content was negatively correlated with carbohydrate content, soluble fraction, and non-starch fraction, whereas fat content showed positive correlations with ash content and fiber-related components, indicating potential targets for breeding programs. Overall, advanced barley lines combine high performance and stability, providing material suitable for further breeding under Mediterranean conditions.

Maize seed quality and kernel morphological traits are important determinants of grain utilization and are influenced by both genetic factors and growing-season conditions. This study evaluated the stability of seed quality and kernel morphological traits in two commercial maize hybrids (Costanza and LG 3535) across four growing seasons, three row spacing systems, and two plant density levels. Seed quality traits (protein, fat, ash, starch, crude fiber, and moisture content) and kernel morphological traits (length, width, and thickness) were evaluated using univariate and multivariate statistical analyses. Significant effects of hybrid, growing season, row spacing, and their interactions were detected for most evaluated traits. Growing-season variability influenced seed composition and kernel morphology, while row spacing and plant density further contributed to trait expression. Costanza exhibited greater stability for most traits, particularly starch content and kernel morphology, whereas LG 3535 showed more variable responses across growing seasons and row spacing combinations. Correlation and multivariate analyses revealed strong associations among starch content, kernel width, and kernel thickness, whereas protein, ash, and crude fiber were less closely associated with kernel size traits. These findings demonstrate the importance of hybrid & times; growing-season interactions in shaping maize kernel characteristics and highlight the value of multi-environment evaluation for identifying hybrids with stable kernel quality traits under Mediterranean production conditions.

Economic integration facilitated international trade within the EU with overall benefits for its economy. However, the importance of intra-EU trade varies by country and industry. This paper aims to estimate the efficiency of the intra-EU trade for particular Member States and economic sectors. The trade efficiency of the Member States is measured with the net export index and the difference in export and import growth. Correlation and regression analysis is used to assess sector-specific effects. The results show that South European Member States perform better in the efficiency of intra-EU services trade and worse in merchandise trade, but the difference is decreasing. Western European countries tend to have medium efficiency of services trade and stability in the efficiency of merchandise trade. North European countries are likely to have less than average trade efficiency and no major changes in it. Central European countries perform better than average and have an upward trend in merchandise trade efficiency. Ireland, Poland, Czechia, Slovenia, and Bulgaria have the best performance in the total intra-EU trade. The EU has a well-diversified intra-bloc trade with the domination of manufactured goods. The elasticity of value added to exports is the highest for apparel, automotive industries, agriculture, and travel services (0.8-1.2). Other sectors have lower elasticities: 0.3-0.7 (goods) or 0.4-0.6 (services). Export demand has little effect on the food industry, fuel industry, construction, and insurance sectors. The negative correlation in financial services was a prominent exception among industries.

Background: During the COVID-19 pandemic, several instruments were developed to measure the psychological impact of COVID-19, such as fear, anxiety, post-traumatic stress, phobia, etc. Objective: To adapt cross-cultural and validate the COVID Stress Scales in Greek. Methods: We conducted a cross-sectional study with 200 participants between November 2021 to February 2022. All participants were adults, and a convenience sample was obtained. We applied the forward-backward translation method to create a Greek version of the COVID Stress Scales. We assessed the reliability of the questionnaire with the test-retest method in a 10-day window, and we assessed the validity of the questionnaire with exploratory factor analysis. Results: Our five-factor model explained 72% of the variance and totally confirmed the factors of the initial COVID Stress Scales. In particular, we found the following five factors: (a) COVID-19 danger and contamination (eleven items), (b) COVID-19 socioeconomic consequences (six items), (c) COVID-19 xenophobia (six items), (d) COVID-19 traumatic stress (six items), and (e) COVID-19 compulsive checking (six items). Cronbach coefficients alpha for the five factors that emerged from the exploratory factor analysis were greater than 0.89 indicating excellent internal reliability. Conclusions: We found that the COVID Stress Scales is a reliable and valid tool to measure stress due to the COVID-19 in the Greek population.

Surface roughness, an indicator of surface quality is one of the most specified customer requirements in a machining process. Mastering of surface quality issues helps avoiding failure, enhances component integrity, and reduces overall costs. Copper alloy (GCCuSn12) surface quality, achieved in turning, constitutes the subject of the current research study. Test specimens in the form of near-to-net-shape bars and a titanium nitride coated cemented carbide (T30) cutting tool were used. The independent variables considered were the tool nose radius (r), feed rate (f), cutting speed (V), and depth of cut (a). Process performance is estimated using the statistical surface texture parameters Rα, Ry, and Rz. To predict the surface roughness, an artificial feed forward back propagation neural network (ANN) model was designed for the data obtained.