Beta macrocarpa, Guss is an interesting species showing very low germination rates. The leading objectives of this work were to investigate the dormancy mechanism and to find methods to break dormancy in order to achieve rapid, uniform and high germination. Macro and micro-morphologic analyses were performed by stereo microscopy and scanning electron microscopy showed two fruit coats. The yellow external coat or persistent perianth coat (PPC) was accrescent with 5 erect segments contiguous to the operculum of the seed capsule. This coat forms spongy layers (50 to 300 µm thick) that could be eliminated manually. The narrow internal coat or pericarp or achene coat (AC) forms woody joined seed capsules, each presenting a pressed operculum that cannot be manually opened. This coat was not adherent to seeds and was composed of compressed cells (50 to 200 µm thick) which form pockets for salt cristal. Seeds were lentiform (1 to 2 mm diameter and 0.5 to 0.8 mm thick) and highly fragile. The embryo was whitish surrounded peripherally by the perisperm with two highly developed cotyledons and radical. Polyphenol concentrations in both coats showed that after 4 months of collection, total polyphenol concentrations were 4-fold higher in the pericarp than in the persistent perianth. However, after one year, this parameter decreases significantly in the pericarp, whereas, it increases to a larger extent in the perianth. Different germination tests indicated that the pericarp provides a chemical and a physical resistance to seed germination during the first 4 months of the experiment after collection. The chemical dormancy was released to higher levels of total polyphenol compounds that inhibited seed germination and seedling growth. However, the physical dormancy was associated with the hardness of this intern coat which caused a mechanical resistance to radicle emergence. After one year of storage, total polyphenol pericarp concentration decreased notably, and chemical resistance disappeared, whereas the physical one persisted. Consequently, one year of storage pericarp removal is sufficient to break this exogenous dormancy.

The study aimed to investigate the concept of workplace equality as experienced and perceived by female librarians of Punjab, Pakistan. Through this investigation, the study aimed to contribute to the broader discourse on creating equitable and inclusive workplaces for women in the field of library and information science. A qualitative research method based on semi-structured interviews was employed to meet the objectives of the study. The interview guide was used to collect data from female librarians working in the Higher Education Commission’s (HEC) recognized public and private sector universities of the Punjab, Pakistan. According to the results, female librarians shared that they have faced gender-based discrimination in job allocation as male librarians were favored for tasks with additional wages or representation at corporate events. Private sector candidates reported issues related to career development opportunities as managers often restrict participation in seminars, conferences, and higher education pursuits. The study also highlighted that inequalities or discriminations affect employees motivation and enthusiasm. This study highlights issues of inequality from a female perspective in the library and information science field, contributing to a deeper understanding of the key factors to ensure equitable workplaces. This study may be a useful contribution to the body of research literature, as well as the findings may help in sensitizing the management and authorities to control the work environment to facilitate females, and to make female-oriented policies.

The business world is currently undergoing a significant shift towards sustainability and intelligent automation, which presents both promising prospects and formidable hurdles for business owners. The increasing demand for sustainable goods and services, driven by pressing social and environmental issues, opens doors for entrepreneurs to establish companies that address these concerns. Moreover, automation and technological advancements have revolutionized the operational landscape of firms, providing entrepreneurs with novel opportunities to enhance efficiency and foster creativity. However, thriving in this dynamic environment necessitates a fresh skill set and innovative approaches. Entrepreneurs must actively acquire the requisite technological expertise to leverage the potential of intelligent automation while navigating the intricate legislative and social frameworks surrounding sustainability. Furthermore, they must demonstrate agility and adaptability, adept at pivoting strategies and offerings to align with the evolving business panorama. This study’s exploration of the intersection of automation and entrepreneurship resonates deeply with the principles of sustainability. By dissecting the challenges and strategies entrepreneurs use to embrace automation, the research contributes valuable insights to the ongoing discourse on feasible business practices within the context of burgeoning sustainability. The findings will assist policymakers by providing useful information to cultivate an environment conducive to sustainable, technology-based entrepreneurship.

In this study, the authors propose a method that combines CNN and LSTM networks to recognize facial expressions. To handle illumination changes and preserve edge information in the image, the method uses two different preprocessing techniques. The preprocessed image is then fed into two independent CNN layers for feature extraction. The extracted features are then fused with an LSTM layer to capture the temporal dynamics of facial expressions. To evaluate the method's performance, the authors use the FER2013 dataset, which contains over 35,000 facial images with seven different expressions. To ensure a balanced distribution of the expressions in the training and testing sets, a mixing matrix is generated. The models in FER on the FER2013 dataset with an accuracy of 73.72%. The use of Focal loss, a variant of cross-entropy loss, improves the model's performance, especially in handling class imbalance. Overall, the proposed method demonstrates strong generalization ability and robustness to variations in illumination and facial expressions. It has the potential to be applied in various real-world applications such as emotion recognition in virtual assistants, driver monitoring systems, and mental health diagnosis.