Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

Collaboration among individuals with diverse skills and personalities is crucial in producing high-quality software. The success of any software project depends on the team’s cohesive functionality and mutual complementation. This study introduces a data-centric methodology for forming Software Engineering (SE) teams centred around personality traits. Our study analyzed data from an SE course where 157 students in 31 teams worked through four project phases and were evaluated based on deliverables and instructor feedback. Using the Five Factor Model (FFM) and a variety of statistical tests, we determined that teams with higher levels of extraversion and conscientiousness and lower neuroticism consistently performed better. We examined team member interactions and developed a predictive model using extreme gradient boosting. The model achieved a 74% accuracy rate in predicting inter-member satisfaction rankings. Through graphical explainability, it underscored incompatibilities among members, notably those with differing levels of extraversion. Based on our findings, we introduce a team formation algorithm using Simulated Annealing (SA), built upon the insights from our predictive model and additional heuristics.

Fisheries and bottom seawater data were collected in July in 2022 and 2023 from 15 sampling stations in the Huanghe River Estuary and adjacent seas in China. The patterns of functional alpha- and beta-diversity of fish communities in this area and their relationship with environmental factors were studied using trait-based analysis. Five functional classifications, which included 16 functional traits, four functional alpha-diversity indices (functional richness, functional evenness, functional divergence, and community-weighted mean), three functional beta-diversity indices (functional beta-diversity and its turnover and nestedness components), and 14 bottom environmental factors were considered. The dominant traits of fish communities were: benthivorous feeding habits, small and front-facing mouths, high trophic level, demersal, anguilliform, low growth coefficient, medium resilience, low vulnerability, and adapted to warm temperate conditions. The dominant migration traits and types of fish eggs varied by year, and fish abundance was the main factor affecting the dominant traits of the communities. The results of multiple regression on distance matrices and variance partitioning analysis indicated that ammonia nitrogen content, total phosphorus content, and pH were the main environmental factors that affected fish functional diversity. The N/P ratio had an upward control effect on fish functional diversity. Our findings also revealed that high pH gradients and distant geographical distances can inhibit trait turnover in fish communities.

Conduct problems (CP) in childhood and adolescence have a significant impact on the individual, family, and community. To improve treatment for CP, there is a need to better understand the developmental pathways of CP in boys and girls. Prior research has linked the child’s fearlessness and callous-unemotional (CU) traits, as well as experiences of parental warmth and punitive parenting, to CP. However, few studies have tested the interplay of these factors in contributing to future CP development. The present study aimed to test the InterFear model (Fanti et al., 2023), which suggests that fearlessness in early childhood leads to CP through an indirect pathway involving low positive parenting, high negative/punitive parenting, and callous-unemotional (CU) traits. The sample included 2,467 Spanish children (48.1% girls; Mage = 4.25; SD = 0.91), followed-up across a five-year period. In addition to a direct association between fearlessness in early childhood and future CP, the results found an indirect pathway whereby fearlessness reduces positive parenting and increases punitive parenting, which contributes to the development of CU traits and sets the stage for CP in later childhood. The specific indirect effect from fearlessness to CP via CU traits accounted for most of the variance, suggesting the existence of a temperamental pathway independent of parental variables. Further, two additional indirect pathways, exclusive of fearlessness, were found and started with low parental warmth and positive parenting leading to CP via CU traits. These findings support the InterFear model, demonstrating multiple pathways to CP with the involvement of fearlessness, parenting practices, and CU traits. This model may play a pivotal role in the development of targeted prevention strategies for CP.

Quinoa is a resilient crop known for its adaptability to diverse environmental conditions. This study examined the agronomic performance and ecological adaptability of quinoa across four distinct altitudes in the northwestern regions of China. Six quinoa genotypes were assessed for agronomic traits, phenology and yield performances, and nutritional quality characteristics in Yining city, Nilka County, Tekes County and Zhaosu County under varied environmental conditions. Our findings demonstrate significant variations in all measured traits including agronomic and nutritional quality traits across the various altitudes and genotypes. In Yining City, a warmer and lower altitude area, genotypes exhibit superior traits for fodder production, including increased branches, longer panicles, robust stems, and high seed protein content. Genotypes Jinli 1 and Beijing 2 achieve yields exceeding 3 tons per hectare (T/ha), highlighting the region’s productivity. Nilka and Tekes counties boasted the shortest quinoa crop cycles, with Jinli 1 yielding 4.05 T/ha seeds in Tekes County, exhibiting high protein and fat content alongside low saponins, making it prime location for yield production. Zhaosu County, with its cooler climate and fertile chernozem soil, elicited high 1000 seed weight and more robust protein response than Nilka and Tekes counties, illustrating the impact of soil fertility on nutritional composition. Correlation analyses further elucidated that the plants characterized by shorter flowering times, crop cycles, compact inflorescence, and taller heights exhibited superior seed yields. Our study contributes significant insights into the ecological adaptability and nutritional dynamics of quinoa, with implications for sustainable crop production and food security in diverse agroecosystems.