A5110510869- Advanced Control Systems Optimization
- Process Optimization and Integration
- Advanced Image and Video Retrieval Techniques
- Dental Research and COVID-19
- Visual Attention and Saliency Detection
- Synthesis of heterocyclic compounds
- Synthesis and Reactivity of Sulfur-Containing Compounds
- Phenothiazines and Benzothiazines Synthesis and Activities
- Asymmetric Hydrogenation and Catalysis
- Catalysis for Biomass Conversion
- Synthesis and Reactions of Organic Compounds
- Fault Detection and Control Systems
- Catalysts for Methane Reforming
- Enzyme function and inhibition
- Neural Networks and Applications
- EEG and Brain-Computer Interfaces
- Synthesis and Catalytic Reactions
- Generative Adversarial Networks and Image Synthesis
- Dental materials and restorations
- Oral microbiology and periodontitis research
- Microbial Metabolic Engineering and Bioproduction
National Chemical Laboratory
1998-1999
University of Mumbai
1993
Experiments in a pilot-scale fixed-bed reactor system have been conducted to obtain the process input−output data for titanium-based zeolite-catalyzed hydroxylation of phenol dihydroxybenzenes. An artificial neural-network-based strategy has used identifying model covering range experimental conditions. The identified neural network design predictive controller that tested on rig.
Aims This study aims to evaluate and compare the antibacterial activity of three self-etching primers (SEP), namely, Transbond plus, Reliance, Gluma against commonly encountered oral microflora ( Streptococcus mutans, Lactobacillus acidophilus , Actinomyces viscosus). Subjects Methods The SEPs was examined microorganisms using agar diffusion test (ADT) minimum inhibitory concentration (MIC). In ADT, Whatman’s filter paper disc 5 mm loaded with primer polymerized. placed on previously...
Abstract ChemInform is a weekly Abstracting Service, delivering concise information at glance that was extracted from about 100 leading journals. To access of an article which published elsewhere, please select “Full Text” option. The original trackable via the “References”
Abstract ChemInform is a weekly Abstracting Service, delivering concise information at glance that was extracted from about 100 leading journals. To access of an article which published elsewhere, please select “Full Text” option. The original trackable via the “References”