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Titlebook: Microorganisms in Saline Environments: Strategies and Functions; Bhoopander Giri,Ajit Varma Book 2019 Springer Nature Switzerland AG 2019

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樓主: 可擴(kuò)大
31#
發(fā)表于 2025-3-26 22:37:55 | 只看該作者
Microbial Ecology of Saline Ecosystemse usual culture-dependent and culture-independent techniques are also helpful in these studies. India has large numbers of biodiversity hotspots including diversified saline ecosystems. There are only limited reports on the culturable and yet to be cultivated halophilic bacteria from the country, which needs great endeavour in the future.
32#
發(fā)表于 2025-3-27 02:56:35 | 只看該作者
Microbial Diversity of Saline Habitats: An Overview of Biotechnological Applicationso the production of new bioactive molecules such as enzymes, antibiotics, osmolytes, and polymers. Further applications of these microbes in bioremediation, enzyme industry, drug development, biofuels, bioplastics, and compatible solutes have been extensively discussed.
33#
發(fā)表于 2025-3-27 07:42:43 | 只看該作者
34#
發(fā)表于 2025-3-27 13:17:45 | 只看該作者
1613-3382 ives overview on plant-microbe interactions under saline con.This book gathers the latest findings on the microbial ecology of saline habitats, plant-microbe interactions under saline conditions, and saline soil reclamation for agricultural use. The content is divided into four main parts: Part I ou
35#
發(fā)表于 2025-3-27 16:37:44 | 只看該作者
Book 2019l reclamation for agricultural use. The content is divided into four main parts: Part I outlines the de?nition of salinity, its genesis and?impacts, and microbial diversity in saline habitats. Part II deals with impact of?salinity on microbial and plant life/health. Part III highlights plant – micro
36#
發(fā)表于 2025-3-27 18:52:24 | 只看該作者
37#
發(fā)表于 2025-3-28 00:54:29 | 只看該作者
38#
發(fā)表于 2025-3-28 04:02:08 | 只看該作者
39#
發(fā)表于 2025-3-28 08:03:24 | 只看該作者
40#
發(fā)表于 2025-3-28 11:52:01 | 只看該作者
Mohamed Magdy F. Mansour,Karima Hamid A. Salamacarried out on a database of histopathological images of renal cell carcinoma (RCC) and then tested on both own RCC and open-source TCGA datasets. The results show that the proposed MTL-SSL model outperforms the conventional supervised-learning segmentation approach.
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