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Leyla Nazari, Vida Ghotbi, Mohammad Nadimi and Jitendra Paliwal
This study proposes a hybrid gene selection method to identify and predict key genes in Arabidopsis associated with various stresses (including salt, heat, cold, high-light, and flagellin), aiming to enhance crop tolerance. An open-source microarray data...
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L. G. Divyanth, D. S. Guru, Peeyush Soni, Rajendra Machavaram, Mohammad Nadimi and Jitendra Paliwal
Applications of deep-learning models in machine visions for crop/weed identification have remarkably upgraded the authenticity of precise weed management. However, compelling data are required to obtain the desired result from this highly data-driven ope...
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M. DAS GUPTA,S. BASU,R. K. PALIWAL,U. C. MOHANTY,N. V. SAM
For accurate determination of the three-dimensional structure of atmospheric circulation, it is very important to assimilate every observation from all available sources, especially over the data sparse oceanic regions. During the ...
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D. RAJAN,B. SIMÓN,P. C. JOSHI,V. B. BHATIA,A. K. MITRA,R. K. PALIWAL
A realistic three-dimensional distribution of moisture in the initial condition is essential for successful numerical weather prediction. The moisture profile serves as direct input to any forecast model. Since the ocean surrounding ...
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D. RAJAN,A. K. MITRA,S. R. H. RIZVI,R. K. PALIWAL,A. K. BOHRA,V. B. BHATIA
In recent years space instruments and remote sensing tools are allowing us to look at the Earth with new eyes; they have extended the scope of vision. India has the world's most gigantic monsoon system which is extremely important for the Indian agric...
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