In this mini review it is to focus that how can pollutants be removed from the environment by utilizing microalgae which are deliberately increasing and causing hazardous effects to our environment. Microalgae are sunlight-driven cell factories that convert carbon dioxide to potential biofuels, foods, feeds and high-value bioactives. Various types of pollutants continuously causing damage to the environment and after a long-term observation it is found that there is a best option of using microalgae in different techniques for reducing environmental pollutants. Since, versatile species of microalgae has been a part in reduction and removal of environmental pollutants as we observed in different bioremmedial techniques such as in waste water treatment plants, heavy metal removal techniques, bio-degradation of azo-dyes, phenol and other organic aromatic compounds which are dangerous to the environment. It is reappraised that one of microalgae specie which is named as chlorella vulgaris is found to be very effective in removing of heavy metals, waste water treatment and also in biodegradation of azo-dyes. This article basically explained the usefulness of using microalgae for the remediation of pollutants.
Research in Natural Language Processing (NLP) and computational linguistics highly depends on a good quality representative corpus of any specific language. Bangla is one of the most spoken languages in the world but Bangla NLP research is in its early stage of development due to the lack of quality public corpus. This article describes the detailed compilation methodology of a comprehensive monolingual Bangla corpus, KUMono. The newly developed corpus consists of more than 350 million word tokens and more than one million unique tokens from 18 major text categories of online Bangla websites. We have conducted several word-level and character-level linguistic phenomenon analyses based on empirical studies of the developed corpus. The corpus follows Zipf's curve and hapax legomena rule. The quality of the corpus is also assessed by analyzing and comparing the inherent sparseness of the corpus with existing Bangla corpora, by analyzing the distribution of function words of the corpus and vocabulary growth rate. We have developed a Bangla article categorization application based on the KUMono corpus and received compelling results by comparing to the state-of-the-art models.
Solid waste is considered as a biggest pollution problem in Pakistan. Improper management of solid waste creates many problems in Pakistan like health problems by causing different disease; create unpleasant smell, land pollution and also effect the beauty of the country. The country spends lot of income for the management of solid waste. The aim of this research is to identify that solid waste is consider as an economic burden or an economic assets. For this research work, we choose the pharmacy faculty found in university of Karachi, Pakistan. We collect different type of data related with solid waste from the members of the faculty and the result of the project shows that our little effort can make lower this burden and we can convert this economic burden into economic assets.
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