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To evaluate the health impact of spraying organophosphorus insecticides (OPs), 34 male sprayers in the mango belt of Malihabad, a small town located 27 km from Lucknow in North India was selected. Plasma butyryl cholinesterase (PBChE) and complete blood count were assessed among sprayers after spraying pesticides and the findings obtained were compared with those determined in a reference group (n = 18). The most common symptoms observed were burning sensation in the eyes (8.82%), itching/skin irritation (23.52%) and chest symptoms (32.35%) in the exposed workers. Plasma butyrylcholinesterase (PBChE) was significantly decreased in workers. The results indicated significant decrease in the mean value of hemoglobin, hematocrit and platelets count; however, significantly higher count of leukocytes was also observed in the exposed group (sprayers) compared to that observed in the control group (P < 0.05). Monitoring of PBChE in pesticide sprayers could be useful to predict and prevent health hazards of OPs.

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Part-of-speech (POS) tagging is a process of assigning the words in a text corresponding to a particular part of speech. A fundamental version of POS tagging is the identification of words as nouns, verbs, adjectives etc. For processing natural languages, Part of Speech tagging is a prominent tool. It is one of the simplest as well as most constant and statistical model for many NLP applications. POS Tagging is an initial stage of linguistics, text analysis like information retrieval, machine translator, text to speech synthesis, information extraction etc. In POS Tagging we assign a Part of Speech tag to each word in a sentence and literature. Various approaches have been proposed to implement POS taggers. In this paper we present a Marathi part of speech tagger. It is morphologically rich language. Marathi is spoken by the native people of Maharashtra. The general approach used for development of tagger is statistical using Unigram, Bigram, Trigram and HMM Methods. It presents a clear idea about all the algorithms with suitable examples. It also introduces a tag set for Marathi which can be used for tagging Marathi text. In this paper we have shown the development of the tagger as well as compared to check the accuracy of taggers output. The three Marathi POS taggers viz. Unigram, Bigram, Trigram and HMM gives the accuracy of 77.38%, 90.30%, 91.46% and 93.82% respectively.

In this paper we present a Marathipart of speech tagger. It is morphologically rich language. it is spoken by the native people of Maharashtra. The general approach used for development of tagger is statistical using Trigram Method. The main concept of Trigram is to explore the most likely POS for a token based on given information of previous two tags by calculating probabilities to determine whichthe best sequence of tag is. In this paper we show the development of the tagger. Moreover we have also shown the evaluation done.