Mangifera indica L. (Mango, Anacardiaceae) is a popular tropical evergreen tree known for its nutritional and medicinal values. It is native to India and Southeast Asia and is known as the “king of fruits” in India and the Philippines. It is considered important in Ayurveda and other systems of medicine. Mango fruit is unique in its taste, colour, aroma, and nutritional qualities. Mangoes are a rich source of polyphenols (Mangiferin, Gallotannins, Quercetin, Isoquercetin, Ellagic acid, Glucogallin, Kaempferol, Catechins, Tannins, and the unique Xanthonoid), phenolic acids (Hydroxybenzoic acids- Gallic, Vanillic, Syringic, Protocatechuic, and p-Hydroxybenzoic acids, Hydroxycinnamic acid derivatives-p-Coumaric, Chlorogenic, Ferulic, and Caffeic acids), flavonoids (β-carotene, α-carotene, β-cryptoxanthin, and Lutein), Vitamin A, Vitamin-B6 (pyridoxine), Vitamin-C, Vitamin-E, Carbohydrates, Amino acids, Organic acids,  micronutrients (Potassium, Copper), fats (Omega-3 and 6 polyunsaturated fatty acids), dietary fibre and certain volatile compounds. About 25 different types of carotenoids have been isolated from the fruit pulp, which contributes to the colour of the fruit. Phytochemical and nutrient content may vary depending on the cultivar. Mangoes possess potential medicinal properties such as antioxidant, gastro-protective, anti-inflammatory, analgesic, immunomodulatory, anti-microbial, and many more. Mango fruit is an abundant source of all essential nutrients and phytochemicals; it could be ultilized as a nutritional supplement in the prevention and cure of several diseases. A comprehensive report on the nutritional and medicinal properties of fruit is presented below.

The US Infrastructure Investment and Job Act (IIJA), also commonly referred to as the Bipartisan Infrastructure Bill, passed in 2021, has drawn international attention. It aims to help to rebuild US infrastructure, including transportation networks, broadband, water, power and energy, environmental protection and public works projects. An estimated $1.2 trillion in total funding over ten years will be allocated. The Bipartisan Infrastructure Bill is the largest funding bill for US infrastructure in the recent history of the United States. This review article will specifically discuss funding allocations for roads and bridges, power and grids, broadband, water infrastructure, airports, environmental protection, ports, Western water infrastructure, electric vehicle charging stations and electric school buses in the new spending of the Infrastructure Investment and Job Act and why these investments are urgently necessary. This article will also briefly discuss the views of think tank experts, the public policy perspectives, the impact on domestic and global arenas of the new spending in the IIJA, and the public policy implications.

Olive production is threatened by a fungal pathogen, Armillaria mellea (Vahl. Fr.) P. Kumm.,causing decline in trees worldwide. Effectiveness of once and twice applications of fungicides hexaconazole, propicoconazole and thiophanate-methyl and application of biological agent (Trichoderma harzianum) to control A. mellea was studied at orchard scale during four years. T. harzianum inhibited the pathogen growth on agar media. This antagonistic fungus provided a 25% control efficiency of A. mellea on olive trees younger than 15 years which was the same as control efficiency of once application of hexaconazole. Control efficiencies as perfect as 100% were determined on younger (<15 years old) diseased olive trees treated with once applications of thiophanate-methyl and hexaconazole, and twice applications of thiophanate-methyl. Moreover, olive tree age was significantly effective on fungicidal control efficiency. Hence, this four-year research advanced our understanding of sustainable olive production in study region and other geographical areas with similar agro-ecological characteristics.

In the Indian context, financial planning for salaried individuals has gained increased importance due to economic fluctuations, rising living costs, and the need for robust retirement planning. Despite its importance, there is limited research on the specific factors that influence financial decision-making among salaried employees in India. Understanding these determinants is essential for developing effective strategies to enhance financial well-being among employees. This study explores the key factors influencing financial decision-making among employees, including financial goals, emergency savings, retirement planning, budgeting, financial confidence and literacy, financial stress, use of tax-saving instruments, income level, risk tolerance, and debt levels. A sample of 549 employees from diverse sectors in Uttar Pradesh participated in this research, highlighting the critical aspects of personal financial management that impact financial well-being. The study used a questionnaire-based survey to gather data on factors affecting financial decision-making. Descriptive statistics, correlation, and regression analyses were employed to identify significant predictors. The results reveal that financial literacy, access to resources, attitudes toward retirement planning, and cultural norms significantly influence financial decisions. Additionally, income level, job stability, and social support are crucial in shaping employees’ financial planning. The study recommends enhancing employees’ financial decision-making by offering financial education programs, budgeting tools, retirement planning assistance, debt management programs, tax planning workshops, financial counselling services, and employer match programs for retirement savings. These initiatives aim to boost financial literacy and confidence, enabling employees to make informed financial decisions and improve their financial well-being.

Background: According to the 2023 World Economic Forum report, the impact of Artificial Intelligence (AI) and automation on the job market was more significant than originally projected. Although 2018 research forecasted significant job losses balanced by job creation, current data indicates otherwise. Between 2023 and 2027, it is anticipated that 69 million new jobs will be created due to advancements in AI, however, this will be offset by the loss of 83 million jobs, leading to a net decrease of 14 million jobs worldwide. Roles related to AI, digitalization, and sustainability, such as AI specialists and renewable energy engineers are expected to grow, while those in clerical and administrative sectors are most at risk of decline. This shift underscores the need for reskilling and adapting to evolving fields, as nearly 44% of workers skills will face disruption by 2027. The demand for analytical thinking, technological literacy, and adaptability will grow as companies increasingly adopt frontier technologies. Objectives: (1) identify key variables influencing adaptability of college graduates in Indonesia, (2) quantify the strength of relationships between these variables to understand the combined effect on graduate adaptability. The research also aims to (3) develop theoretical and practical recommendations to strengthen ICIL policy and equip students with the relevant skills needed to thrive in an ever-changing job market. Methodology: The research focuses on predicting future employment trends, adaptability, and learning agility (LA), along with the implications for improving the Independent Campus Independent Learning (ICIL) policy. It focused on the significant unemployment rate among college graduates, along with the lack of research on the relationship between job change predictions, graduates’ adaptability, and the impact on graduates’ general well-being. The mixed-method strategy with quantitative analysis was used to conduct this research with data collected from 284 ICIL participants through online survey. The gathered data was evaluated using Structural Equation Modeling (SEM) with Lisrel version 10. Results: The result showed that job trend projections significantly influence responsiveness, which demonstrated a robust association between employment trend predictions and LA. Responsiveness significantly influenced learning agility which indicated no significant direct association between job trend projections and graduate adaptability. Conclusion: The research emphasized the need to consider adaptability as a concept with multiple dimensions. It proposed incorporating these factors into strategies for education and human resources development in order to better equip graduates for the demands of a constantly changing work market. Unique contribution: This research focused on adaptability as a multifaceted concept that consist of the ability to forecast job trends, be sensitive, and possess LA. It offered a deeper understanding of the relationships between these variables as discussed in the human resources literature. Technology, corporate culture, and training played a critical role in connecting employment trend prediction with the ability to respond effectively. Key recommendation: Institutions should implement a comprehensive approach to the development of human resources, with emphasis on fostering critical thinking, analytical abilities, and the practical application of information. By employing these tactics, higher education institutions may effectively equip graduates with both academic proficiency and the ability to adapt and thrive in quickly changing organizational environments, leading to the production of robust and versatile workers.

The aim was to examine the relationships between selected demographic and psychographic factors and consumers' willingness to accept content generated by advanced technological innovations (AIGC) in social infrastructure. The sample consisted of 1,308 respondents. Spearman's correlation coefficient was used to examine the relationships between ordinal variables. To assess the differences between groups of respondents, a one-way analysis of variance was used, during which multiple linear regression analysis was used to confirm the predictive power of awareness and experience in relation to AI-generated content in relation to the tendency to accept such content. The study confirmed a statistically significant but weak negative relationship between the age of respondents and their willingness to accept AIGC, with younger age groups showing a slightly higher rate of acceptance. Respondents' attitudes toward the use of personal data through AI and their overall awareness of technological trends had a more significant impact on acceptance. The findings show that respondents who are open to data collection through AI technologies show a significantly higher level of acceptance of automatically generated content. Similarly, respondents who positively evaluate the current quality of AIGC have higher expectations for the future transformation of marketing strategies and media practices. The decisive factors in the social infrastructure for the acceptance of AIGC are not so much the age of the respondents, but rather their awareness, technological literacy, and level of trust in the technology itself. The study therefore recommends increasing transparency and public awareness about the use of AI in marketing and media practices in order to strengthen consumer confidence in automated content.