Banana (Musa spp.) productivity is limited by sodic soils, which impairs root growth and nutrient uptake. Analyzing root traits under stress conditions can aid in identifying tolerant genotypes. This study investigates the root morphological traits of banana cultivars under sodic soil stress conditions using Rhizovision software. The pot culture experiment was laid out in a Completely Randomized Design (CRD) under open field conditions, with treatments comprising the following varieties: Poovan (AAB), Udhayam (ABB), Karpooravalli (ABB), CO 3 (ABB), Kaveri Saba (ABB), Kaveri Kalki (ABB), Kaveri Haritha (ABB), Monthan (ABB), Nendran (AAB), and Rasthali (AAB), each replicated thrice. Parameters such as the number of roots, root tips, diameter, surface area, perimeter, and volume were assessed to evaluate the performance of different cultivars. The findings reveal that Karpooravali and Udhayam cultivars exhibited superior performance in terms of root morphology compared to other cultivars under sodic soil stress. These cultivars displayed increased root proliferation, elongation, and surface area, indicating their resilience to sodic soil stress. The utilization of Rhizovision software facilitated precise measurement and analysis of root traits, providing valuable insights into the adaptation mechanisms of banana cultivars to adverse soil conditions.

Eucalyptus is an important source of cellulose and a widely cultivated plant. Biotechnology tools can save time spent in breeding and transcriptomic approaches generate a gene profile that allows the identification of candidates involved in processes of interest. RNA-seq is a commonly used technology for transcript analysis and it provides an overview of regulatory pathways. Here, we selected two contrasting Eucalyptus species for cold acclimatization and focused in responsive genes under cold condition aiming woody properties – lignin and cellulose. The number of differentially expressed genes identified in stem sections were 3.300 in Eucalyptus globulus and 1370 in Eucalyptus urograndis. We listed genes with expression higher than 10 times including NAC, MYB and DUF family members. The GO analysis indicates increased oxidative process for E. urograndis. This data can provide information for more detailed analyses for breeding, especially in perennial plants.

Objective: This study aimed to examine the psychometric properties of the 21-item Depression, Anxiety, and Stress Scale (DASS-21) in a sample of Moroccan students. Method: A total of 208 Moroccan students participated in this study. The dimensionality of the DASS-21 scale was assessed using exploratory factor analysis. Construct validity was assessed using the Stress Perception (PSS-10), State Anxiety (SAI), and Depression (CESD-10) scales. Results: Correlation analyses between Depression, Anxiety, and Stress subscales showed significant results. The exploratory factor analysis results confirmed the DASS’s three-dimensional structure. Furthermore, correlation analyses revealed positive correlations between the DASS-18 sub-dimensions and the three scales for Stress (PSS-10), Anxiety (SAI), and Depression (CESD-10). Conclusion: In line with previous work, the results of this study suggest that the DASS-18 reflect adequate psychometric properties, making it an appropriate tool for use in the university context.

Purpose: This research aims to investigate the impact of technological challenges, including techno-overload, techno-complexity, and techno-insecurity, on employee job satisfaction within the banking sector of Saudi Arabia. Additionally, the study examines the mediating roles of supervisor support and job clarity in buffering the effects of technological challenges on job satisfaction. Method: The study employs a quantitative research design, utilizing an online questionnaire to collect data from banking employees in Saudi Arabia. The sample size of 135 participants was determined using the rule of thumb technique. Random sampling was utilized to ensure representativeness. Data analysis was conducted using Statistical Package for Social Sciences (SPSS) to explore the relationships between technological challenges, supervisor support, job clarity, and employee job satisfaction. Findings: The findings of the study reveal a significant negative impact of techno-overload, techno-complexity, and techno-insecurity on employee job satisfaction within the banking sector of Saudi Arabia. Moreover, supervisor support and job clarity were found to mediate these relationships, highlighting their importance in mitigating the adverse effects of technological challenges on job satisfaction. Originality/Significance: This research contributes to the existing body of knowledge by providing empirical evidence on the relationships between technological challenges, supervisor support, job clarity, and employee job satisfaction within the specific context of Saudi Arabian banks. The findings have significant implications for organizational leaders and managers in developing evidence-based strategies to manage technological challenges and promote employee well-being in the banking sector of Saudi Arabia.

This study addresses the rising concerns of technostress experienced by teachers due to the increased reliance on educational technology in both classroom and online settings. Technostress, defined as the adverse psychological effects arising from the use of information communication technologies, has been documented to impact teacher performance and overall well-being. Despite the importance of educational technology in enhancing teaching and learning experiences, many educators report elevated levels of anxiety, stress, and pressures associated with their use of these tools. This study presents practical strategies to help teachers alleviate or prevent technostress while using educational technology. This study used a quantitative approach with a survey conducted among 113 university and schoolteachers. The data analysis included frequency and percentage distribution of categorical variables, Cronbach’s alpha for reliability, chi-square test, and exploratory factor analysis to identify strategies for symptom prevention. The results indicated that while many teachers experienced symptoms of technostress due to several factors, some did not. The study concluded with specific strategies, and many teachers agreed highly. The implications of this study are profound for educational institutions, policymakers, and teacher training programs as they underscore the necessity of providing comprehensive training, support, and resources to help educators manage technostress effectively. By integrating these strategies into professional developmental programs and fostering a supportive teaching environment, schools and universities can promote better mental health for teachers, improving students’ educational outcomes.

Heat stress amplified by climate change causes excessive reductions in labor capacity, work injuries, and socio-economic losses. Yet studies of corresponding impact assessments and adaptation developments are insufficient and incapable of effectively dealing with uncertain information. This gap is caused by the inability to resolve complex channels involving climate change, labor relations, and labor productivity. In this paper, an optimization-based productivity restoration modeling framework is developed to bridge the gap and support decision-makers in making informed adaptation plans. The framework integrates a multiple-climate-model ensemble, an empirical relationship between heat stress and labor capacity, and an inexact system costs model to investigate underlying uncertainties associated with climate and management systems. Optimal and reliable decision alternatives can be obtained by communicating uncertain information into the optimization processes and resolving multiple channels. Results show that the increased heat stress will lead to a potential reduction in labor productivity in China. By solving the objective function of the framework, total system costs to restore the reduction are estimated to be up to 248,700 million dollars under a Representative Concentration Pathway of 2.6 (RCP2.6) and 697,073 million dollars under RCP8.5 for standard employment, while less costs found for non-standard employment. However, non-standard employment tends to restore productivity reduction with the minimum system cost by implementing active measures rather than passive measures due to the low labor costs resulting from ambiguities among employment statuses. The situation could result in more heat-related work injuries because employers in non-standard employment can avoid the obligation of providing a safe working environment. Urgent actions are needed to uphold labor productivity with climate change, especially to ensure that employers from non-standard employment fulfill their statutory obligations.