On the frontiers of Twitter data and sentiment analysis in election prediction: a review.

Election prediction using sentiment analysis is a rapidly growing field that utilizes natural language processing and machine learning techniques to predict the outcome of political elections by analyzing the sentiment of online conversations and news articles. Sentiment analysis, or opinion mining, involves using text analysis to identify and extract subjective information from text data sources. In the context of election prediction, sentiment analysis can be used to gauge public opinion and predict the likely winner of an election. Significant progress has been made in election prediction in the last two decades. Yet, it becomes easier to have its comprehensive view if it has been appropriately classified approach-wise, citation-wise, and technology-wise. The main objective of this article is to examine and consolidate the progress made in research about election prediction using Twitter data. The aim is to provide a comprehensive overview of the current state-of-the-art practices in this field while identifying potential avenues for further research and exploration.

Degradation of chlorpyrifos residues in apple under temperate conditions of Kashmir Valley.

The present studies were carried out to observe the dissipation pattern of chlorpyrifos on apple in Kashmir Valley. Persistence of chlorpyrifos in apple was studied following two applications rates of chlorpyrifos (Dursban 20 EC) at 200 g a.i. ha(-1) (single dose T 1) and 400 g a.i. ha(-1) (double dose T 2). The average initial deposit of chlorpyrifos was found to be 1.61 and 1.98 µg g(-1) for T 1 and T 2 application rates respectively on apple. The residues dissipated to 0.09 and 0.06 µg g(-1) after 15- and 30-day post treatment with half-life periods of 3.34 and 5.47 days in T 1 and T 2 application rates, respectively. The residues of chlorpyrifos dissipated to below limit of quantification (LOQ) of 0.04 µg g(-1) after 30 day at T 1 application rate. A waiting period of 6 days must be observed for chlorpyrifos on apple at recommended application rate for the safety of consumers. Theoretical maximum residue contribution (TMRC) values were found to be far less than maximum permissible intake (MPI) at 0 day in both the dosages suggesting chlorpyrifos on apple in Kashmir is unlikely to cause health risks.