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A list of 350 words that deviate in pronunciation from the standard English pronunciation of these words has been suggested in the present study. To highlight the deviant pronunciation of these words from the standard pronunciation, a wordlist based on observation has been suggested. Transcription of the words according to the British, American, and Pakistani phonetic variants has been given. The general phonological patterns of the pronunciation of these English words by Pakistani speakers as non-native learners of English have also been suggested. The deviation can be found in terms of the elongation of sounds, insertion or omission of schwa, pronunciation of diphthongs as monophthongs, stress patterns, and focus on spellings than sounds. The study not only highlights the unique phonological features of Pakistani English but also offers an opportunity for Pakistani teachers and learners to focus on these words while teaching or learning how to pronounce English words correctly. The study has implications for TESOL, EFL, SLA, and contrastive phonetics and phonology.

English as an international language has left its impact on all the languages being spoken in the world. This impact has led to a world-wide language variation on a large scale. This variation can be evidently observed in the form of code-mixing and code-switching. The study explores and analyzes the frequency of code-mixing in the TV ads broadcasted in Pakistan so as to determine the level of variation that took place in Urdu due to English. Seventy commercials that have been shown during the years 2011-2015 have randomly been selected and the frequency of English words has been checked. The results show that so far as the language of commercials is concerned, Urdu has clearly been influenced by English due to multiple reasons such as fashion, ease and technological advancements etc.

In data analysis, the first step for broad analysis is outlying items. Outlying items cause false results, biased parameter estimation and model misspecification. Some of the methods for detection of outlier are: Distance based method, Distribution based method, Density based method and Clustering based method. In this research, clustering based method is used for outlying items. The purpose of this study is to detect outlier in multivariate data by performing cluster analysis. The K means and Partitioning Around Medoid (PAM) methods were performed. After cluster the data outliers are detected by measuring distance. The comparison of the clustering techniques in outlier detection methods are analyzed. The secondary data was used for analysis. In this data set impact of zinc phosphide with three sub lethal doses (concentrations) on different body tissues of rat are used to find any anomalies. R software was used for data analysis. [ABSTRACT FROM AUTHOR]

The study highlights the discursive representation of fear in the images used in news, articles, and blogs on Covid-19. Various dimensions of the impact of fear on tourism, trade, health, industry, and technology, etc. have been pinpointed by studying the ideational signs in relation to the proximization strategies used in the images. Ideational metafunction suggested by Kress and van Leeuwen(2006) has been applied to 80 images taken from 80 news articles or blogs to highlight the patterns of Covid-19 fear and its impact. Besides, Cap's(2017) understanding of spatio-temporal and axiological proximization strategies for the construction of fear in health discourse also inform the analysis. The results not only show how fear is linked to the display of human values and evils but also bring to light how various ideational choices of signs serve as rhetorical proximization strategies in the construal of disease as an imminent danger and apocalyptic hazard. The study has implications for multimodality, medical semiotics, sociology, and the 'discourse of fear'. [ABSTRACT FROM AUTHOR]