Medicinal herbs have been extensively utilized in the remediation of various health conditions. Dialium guineense fruit pulp, also well known as Velvet Tamarind is widely consumed in West Africa for its dietary and medicinal properties. The study aims to analyze the phytochemical constituents, vitamin content and the in vitro antioxidant effect of Dialium guineense fruit pulp (DGFP). The phytochemical constituents, vitamins (C, E, B1-12) composition, and in vitro antioxidant activity were examined utilizing standardized analytical methods. The qualitative and quantitative phytochemical screening of the fruit pulp of Dialium guineense was also carried out; the result indicated the presence of flavonoids, alkaloids, saponins, tannins, terpenoids, phenols, steroids, and cardiac glycosides in varying concentrations. The vitamin composition revealed that vitamin C was higher than other vitamins in the fruit pulp. The DPPH (2,2-diphenyl-1-picrylhydrazyl) and nitric oxide scavenging assay showed high radical scavenging activity while the FRAP (Ferric reducing antioxidant power) assay revealed significant reducing power. This indicates that Dialium guineense fruit pulp has potential health benefits.

This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

This research investigates the impact of digital academic supervision (DAS) on teacher professionalism (TP), with a focus on the mediating role of personal learning networks (PLNs) and their implication for educational policy. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), data were collected from 276 teachers in prestigious secondary schools in East Java, Indonesia. The study uses a regression model design to explore direct and mediated effects between DAS, PLNs, and TP. Findings demonstrate that DAS directly impacts both PLNs (0.638) and TP (0.550), while PLNs also directly influence TP (0.293). Mediated analysis indicates that DAS enhances TP through PLNs (0.187). These results underscore the importance of digital tools in academic supervision, fostering collaboration, and promoting teacher professional development. The empirical evidence supports the effectiveness of DAS in enhancing teacher professionalism, suggesting significant implications for educational policy and practice in Indonesia in terms of regulatory framework, such as data privacy and security, standardization, training programs, and certification and accreditation.

Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.

There are several factors that generate postharvest losses of Citrus sinensis, but none have been focused on the central jungle of the Junín region of Peru. The objective of this research was to evaluate postharvest losses of Citrus sinensis in the province of Satipo, Junín region of Peru, considering the stages of the production chain. The methodology was applied to descriptive and cross-sectional design. A sample of 10 orange trees, 3 transport intermediaries and 5 traders selected for compliance with minimum volume and quality requirements were used. The °Brix, pH and acidity characteristics of the fruit were determined. Subsequently, absolute and percentage losses were quantified through direct observation, surveys and interviews. The main postharvest losses of Citrus sinensis were 1.50% in harvesting and detaching, 1.75% in transport to the collection center, 2.23% in storage and transport by intermediaries, and 2.90% in storage and sale by retailers. The overall loss was 8.12% throughout the production chain and US$5.75 per MT of C. sinensis harvested. The main damages found were mechanical and biological, caused by poor harvesting and packaging techniques, precarious storage and careless transport of the merchandise.

Public signs in scenic spots play the role of guidance, instruction and warning, and are of great significance to promote the development of scenic spots. Guang’an District has a strong historical and cultural heritage and the rapid development of tourism, but the English translation of public signs in the scenic spot has become increasingly prominent, mainly including nonstandard translation, spelling errors, logical confusion and grammatical errors. In order to promote the solution of such problems, this paper will analyze the current situation of English translation of public signs in Guang’an scenic spots, and put forward solutions to the problems of English translation of public signs through hiring professional translators, cultural difference training and regional cooperation.