Phytochemical and antioxidant analysis of some varieties of Capsicum was evaluated. Mature Capsicum varieties were collected across the State. The seeds were removed, sun-dried for 3 days, stored for 2 weeks at 15 ºC–25 ºC in polythene bags before planting. Saponins, tannins, flavonoids, alkaloids and cardiac glycosides were present in abundant, moderate and trace amounts. Combined anthraquinones were absent in all varieties. Yellow (0.810 ± 0.0006 µg/mL), red long dry (0.211 ± 0.0006 µg/mL) and round peppers (2.527 ± 0.0003 µg/mL) had the largest values for total phenol, flavonoids and tannins. Shombo and yellow peppers had the largest (0.270 ± 0.002 µg/mL) and least (0.102 ± 0.001 µg/mL) capsaicin content. The antioxidant activities varied across the varieties. At 100 µg/mL of methanol, yellow (45%) and round peppers (45%) had largest mean absorbances for 2,2-Diphenyl-1-Picrylhydrazyl (DPPH) Radical Scavenging Activity while sub-shombo pepper (23%) had the least. For Ferric Reducing Antioxidant Power (FRAP), yellow (0.63 ± 0.001 µg/mL) and sub-shombo peppers (0.55 ± 0.001µg/mL) had the largest and least values at 100 µg/mL of methanol. At 100 µg/mL of methanol, red long dry (0.112 ± 0.001) and shombo peppers (0.101 ± 0.001) had the largest and least values for the nitric oxide scavenging activity. This study shows that Capsicum varieties exhibit bioactive componds similarities and variations with implications in hybridization, taxonomy and conservation.
Project risk management in the mining industry is necessary to identify, analyze and reduce uncertainty. The engineering features of mining enterprises, by their nature, require improved risk management tools. This article proves the relevance of creating a simulation model of the production process to reduce uncertainty when making investment decisions. The purpose of the study is to develop an algorithm for deciding on the economic feasibility of creating a simulation experiment. At the same time, the features and patterns of the cases for which the simulation experiment was carried out were studied. Criteria for feasibility assessment of the model introduction based on a qualitative parameters became the central idea for algorithm. The relevance of the formulated algorithm was verified by creating a simulation model of a potassium salt deposit with subsequent optimization of the production process parameters. According to the results of the experiment, the damage from the occurrence of a risk situations was estimated as a decrease in conveyor productivity by 32.6%. The proposed methods made it possible to minimize this risk of stops in the conveyor network and assess the lack of income due to the risk occurrences.
This study presents a comprehensive bibliometric analysis of the literature on public financial management (PFM), aiming to identify key trends, influential publications, and emerging themes. Using data from Web of Science and Scopus, the study examines the evolution of PFM research from 1977 to 2024. The findings reveal a significant increase in PFM research output, particularly after 2010, with countries like the United States, the United Kingdom, and China contributing the most publications. Central themes such as financial management, transparency, and accountability remain prominent while emerging topics like gender budgeting, health insurance, and blockchain technology reflect shifting priorities in the field. The study employed performance analysis and science mapping techniques to assess the structure and dynamics of PFM research. The analysis highlights key focus areas, including fiscal decentralization and sector-specific management, and identifies gaps in the existing literature, particularly regarding interdisciplinary and international collaboration. The results suggest that while PFM remains rooted in traditional governance and financial control, there is a growing emphasis on modern, innovative solutions to address contemporary challenges. This study’s insights provide a roadmap for future research, emphasizing the importance of transparency, technological integration, and inclusive financial policies. In conclusion, this bibliometric analysis contributes to understanding PFM’s evolving landscape, offering scholars and policymakers a clearer perspective on current trends and future directions in the field. Future research should focus on expanding interdisciplinary approaches and exploring the practical impacts of emerging PFM trends across different regions.
Mapping land use and land cover (LULC) is essential for comprehending changes in the environment and promoting sustainable planning. To achieve accurate and effective LULC mapping, this work investigates the integration of Geographic Information Systems (GIS) with Machine Learning (ML) methodology. Different types of land covers in the Lucknow district were classified using the Random Forest (RF) algorithm and Landsat satellite images. Since the research area consists of a variety of landforms, there are issues with classification accuracy. These challenges are met by combining supplementary data into the GIS framework and adjusting algorithm parameters like selection of cloud free images and homogeneous training samples. The result demonstrates a net increase of 484.59 km2 in built-up areas. A net decrement of 75.44 km2 was observed in forest areas. A drastic net decrease of 674.52 km2 was observed for wetlands. Most of the wastelands have been converted into urban areas and agricultural land based on their suitability with settlements or crops. The classifications achieved an overall accuracy near 90%. This strategy provides a reliable way to track changes in land cover, supporting resource management, urban planning, and environmental preservation. The results highlight how sophisticated computational methods can enhance the accuracy of LULC evaluations.
The soundscape studied has gained increasingly frequent attention across multiple disciplines, especially in tourism and leisure domain. While it has already indicated a unique soundscape provides dynamic and memorable tourism experiences, a clearly mapped perspective across different segmentations of soundscapes, both natural and acoustically created, remains missing. Therefore, a comprehensive mapping and review of soundscape studies is imperative to understand its implications for potential inbound tourism research in future. This article aimed to explore potential soundscape studies by assessing trends and developments in recent decades (2013–2023). We applied a bibliometric approach, using a PRISMA framework and under NVivo 12 Plus, VOSViewer, and Biblioshiny-R-Studio software as analytical tools. Significant yield discoveries showed that tourism soundscape research is undergoing steady growth, as evidenced by quantity of publications and citation trends. Single and multi-country international collaborations characterized by soundscape outreach research playing an influential role were highlighted. We identified multiple research themes, such as anthropogenic noise and music heritage, and pointed out how we approached this research from two perspectives: environmental/natural and manufacturing/acoustics. In our review, several keywords and predominant themes were identified, which suggested soundscape studies have recently become an increasingly popular topic in tourism research. The broad spectrum of key themes, such a tourism, tourists, sustainability, areas, and development perspectives, are evidence points of significant diversity in these topics. Most importantly, our research offers significant theoretical and conceptual implications for future direction of soundscape studies. We identified three originality main focus domains in soundscape tourism research: urban and natural environments, technological advancements, and tourists’ perceptions and behaviors.
Tourism plays a crucial role in driving economic development, and there is a growing demand to integrate sustainability into the sector, particularly in the financial practices of governments. This study introduces the Quintessence Sustainable Tourism Public Finances (QSustainableTPF) model, which combines five established financial models commonly used in the tourism industry. The research aims to identify statistically significant relationships between these models and assess their impact on sustainability and financial performance in tourism. A quantitative methodology was employed, with data collected from financial reports and budget documents of both local and central governments, along with a survey of 2099 citizens and visitors conducted during the 2023–2024 period. Statistical analysis was performed using SPSS and AMOS, incorporating exploratory factor analysis (EFA), reliability testing using Cronbach’s alpha, and confirmatory factor analysis (CFA). The findings underscore the essential role of public finance in supporting tourism sustainability, particularly through transparent budgetary practices, efficient allocation of resources, and targeted investment in local tourism initiatives. The analysis reveals key insights into the benefits of financial transparency, citizen-centred budgeting, and the promotion of innovation in tourism finance. The interconnectedness of the five models highlights the importance of responsible public financial management in fostering tourism growth, enhancing investment, and ensuring long-term financial sustainability in the sector. The study offers practical implications for policymakers, advocating for the adoption of transparent and innovative financial practices to boost tourism development. It also recommends further research to broaden the scope across different regions, integrating additional public finance dimensions to strengthen sustainable tourism growth.
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