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Titlebook: Marine Pollution and Microbial Remediation; Milind Mohan Naik,Santosh Kumar Dubey Book 2017 Springer Science+Business Media Singapore 2017

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發(fā)表于 2025-3-21 16:40:11 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Marine Pollution and Microbial Remediation
編輯Milind Mohan Naik,Santosh Kumar Dubey
視頻videohttp://file.papertrans.cn/624/623991/623991.mp4
概述Complies state-of-the-art research of eminent scientists in the field of marine sciences.Covers the cutting edge technologies facilitating marine microbial bioremediation.Presents the very first and c
圖書封面Titlebook: Marine Pollution and Microbial Remediation;  Milind Mohan Naik,Santosh Kumar Dubey Book 2017 Springer Science+Business Media Singapore 2017
描述Marine environment is the largest habitat covering approximately 70% of the total earth surface. Oceans are the main regulatory agent of earth’s climate and harbour a huge diversity of living organisms. Marine environment provide a unique ecological niche to different microbes which play a significant role in nutrient recycling as well as various environmental activities. However with rapid industrialization, urbanisation, ship trafficking and mining activities enormous amounts of waste including heavy metals, hydrocarbons, chemicals,dyes, organic load, agriculture waste, pesticides, antifoulants (e.g. tributyltin) and bacterial pathogens have accumulated in marine/estuarine environments over several decades and pose a serious threat to marine macro and micro biota and humans and therefore require special attention. Howeversome natural marine microbes are known to possess diverse resistance mechanisms and degradation pathways to variety of toxic pollutants and these unique characteristics of marine/estuarine bacteria proved to be an ideal tool in bioremediation of contaminated marine and estuarine environmental sites.Reclamation of marine polluted environments using marine microbes
出版日期Book 2017
關(guān)鍵詞Bio-monitoring; Bioremediation; Environmental Hazards; Marine Environment; Marine Pollution; marine and f
版次1
doihttps://doi.org/10.1007/978-981-10-1044-6
isbn_softcover978-981-10-9314-2
isbn_ebook978-981-10-1044-6
copyrightSpringer Science+Business Media Singapore 2017
The information of publication is updating

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Savita Kerkar,Kirti Ranjan Dasam data is essential to enhance the accuracy and robustness of automated methods. However, due to the visual disparity of the data, deriving cross-view context information remains a challenging task, and unsophisticated fusion strategies can even lower performance. In this study, we propose a novel
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Siddhardha Busi,Jobina Rajkumarint planning. Though deep learning based methods have attained high performance, they rely heavily on large-scale pixel-level annotations that are time-consuming and labor-intensive to obtain. Due to its low dependency on annotation, weakly supervised segmentation has attracted great attention. Howev
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