Social media platforms like X (formerly Twitter) generate vast volumes of user-generated content that provide real-time insights into public sentiment. Despite the widespread use of traditional machine learning methods, their limitations in capturing contextual nuances in noisy social media text remain a challenge. This study leverages the Sentiment140 dataset, comprising 1.6 million labeled tweets, and develops predictive models for binary sentiment classification using Naive Bayes, Logistic Regression, and the transformer-based BERT model. Experiments were conducted on a balanced subset of 12,000 tweets after comprehensive NLP preprocessing. Evaluation using accuracy, F1-score, and confusion matrices revealed that BERT significantly outperforms traditional models, achieving an accuracy of 89.5% and an F1-score of 0.89 by effectively modeling contextual and semantic nuances. In contrast, Naive Bayes and Logistic Regression demonstrated reasonable but consistently lower performance. To support practical deployment, we introduce SentiFeel, an interactive tool enabling real-time sentiment analysis. While resource constraints limited the dataset size and training epochs, future work will explore full corpus utilization and the inclusion of neutral sentiment classes. These findings underscore the potential of transformer models for enhanced public opinion monitoring, marketing analytics, and policy forecasting.

The Chinese film Wolf Warrior II floats all the way at the domestic box office, and jumps into the top 100 of the world's film box office rankings. It has achieved great economic success and ratings are overwhelmingly positive in China. Nevertheless, in stark contrast to this, Wolf Warrior II is cold at the box office abroad, and the word of mouth is not satisfactory. Transcreation is the re-creation or adaptation of content for a group of specific target audience. As an inter-related process of translation, a successful and holistic transcreation can arouse the same emotions as well as connotations produced in the target language as the source language. There are different perspectives to detailed translation analysis of China’s identity as a prominent character of contemporary society. Insofar as this research probes into the branding and in subtitle translation, it also constructs a binary theoretical model based on triadic signs of intersemiotic translation and metafunctional framework of multimodal analysis to testify China’s core values in this film and beyond.

Foods rich in phytochemicals are well recognized for their role in the prevention of chronic disease development, in addition to fulfilling the nutrient requirements. However, different processing methods employed during preparation may affect their levels and functionality as they are sensitive to different processing parameters such as temperature and light. This study aimed to evaluate the effects of three common processing methods; boiling, fermentation, and drying (sun and solar drying, with and without blanching), on total phenolic content and total flavonoid content in cassava (Manhot esculenta Crantz), black jack (Bidens pilosa) and bitter lettuce leaves (Launaea cornuta) grown in Mkuranga District in the Eastern part of Tanzania. Total phenolic content and total flavonoid content were analyzed by using the spectrophotometric method with the use of Folin-Ciocalteu and Aluminum Chloride reagents, respectively. Total phenolic content ranged from 0.9±0.14 to 85.7 ± 0.56 mg Gallic Acid Equivalent (GAE)/100g and flavonoids ranged from 0.03±0.00 to 3.9±0.03 mg/100g across the treatments. Both parameters were adversely affected by fermentation and boiling, while solar and sun drying only reduced the flavonoid content. Results showed that direct solar and sun drying appear to be effective processing methods, for the retention and maintenance of total phenolic content in all samples while, none proved to be effective for flavonoid content.

A diagnosis of the current state of the crops is made regarding the control of weeds, use of pesticides, fungicides; with an assessment of the state of the plant covers in the crop, and its control by different types of herbicides, and we detected a high loss of biological diversity; and some of these compounds are mentioned due to their high toxicity. Similarly, the use of pesticides and fungicides is discussed due to their repercussions on health. In order to avoid the unhealthiness caused by the applications of these products, phytosanitary and educational control strategies are proposed; promoting the inspection of fruit and vegetable markets, and modifying the contents in higher professional and university education. To this end, we propose an active teaching methodology, through which the student acquires skills and responsibility for the use of chemical agents in agriculture, which serves to prevent the entry of these contaminants into the food chain. Of the different polluting chemical agents, in the case of herbicides we highlight Oxyfluorfen and Glyphosate with high toxicity and whose consumption is very high. In the case of pesticides and fungicides, among others are Organochlorine compounds, which have been detected in blood, and Carbon Tetrachloride and Chloroform, considered potent hepatotoxic and neurotoxic. The basic objective of this study is the awareness and acquisition of knowledge by future teachers about polluting agents, which will subsequently have an impact on society.