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Sudipta Let,Nirjhar Bar,Ranjan Kumar Basu,Sudip Kumar Das 한국화학공학회 2023 Korean Journal of Chemical Engineering Vol.40 No.1
The solid-water fluidized bed was investigated with a binary mixture of irregularly shaped sand particles. A binary mixture was produced by mixing particles of sand for different weight ratios. The influence of various operating parameters on minimum elutriation velocity was investigated. It was observed that the Ume decreases with the increase of the lighter particles in the binary mixture, and the Ume increases with the increase of column diameter. A simplified empirical correlation has been developed to predict minimum elutriation velocity with acceptable statistical parameters. Application concerning a hybrid of artificial neural network (ANN), and genetic algorithm (GA), is successfully predicted.
( Sudipta Majumdar ),( Kalyan Kumar De ),( Somenath Banerjee ) 한국식물학회 2004 Journal of Plant Biology Vol.47 No.2
Cyanogenesis-the production of toxic hydrogen cyanide (HCN) by damaged tissue-in Trifolium repens L (white clover), a type of most important pasture legume, has been studied at different elevations of Darjeeling Himalaya (latitude-27° 2` 57`` N, longitude- 88° 15` 45 E). Release of HCN takes place due to reaction between cyanogenic glucosides stored in vacuoles of the leaf cell and the corresponding enzyme ß-glucosidase present in another compartment, often cell wall. Cyanogenesis, a defense system in plant, protects the clover from herbivore and inhibits grazing. Biochemical analysis showed the presence and absence of the cyanogenesis trait within the population in different proportions at different elevations. Acyanogenic individuals also showed variations with respect to presence or absence of either cyanogenic glucosides or ß-glucosidase enzyme or both. The distribution of cyanogenic and acyanogenic plants was found in all places, but at lower altitudes (2084-2094 m) the dominating plants were cyanogenic whereas in higher altitude (2560 m) the dominating plants were acyanogenic. It was observed that blister beetle (Mylabris pustalata Thunb.) and the mollusc (Macrochlamys tusgurium Benson.) were the most common consumer of leaflets of T. repens. Six categories of damage on white clover leaf by these animals were recorded. Our results suggest that the two selective factors or forces i.e. very cold temperature (harmful to cyanogenic plants) at higher altitude as well as indiscriminate but preferential predation (harmful to acyanogenic plants) interact to affect the system of cyanogenesis and also to cause the stable and protective polymorphism in T. repens rather than genotypic differences present among the plants.
Tuberculous Constrictive Pericarditis: A Classical Case and Review
Sudipta Mondal,Arun Gopalakrishnan,Sivadasanpillai Harikrishnan 아시아심장혈관영상의학회 2023 Cardiovascular Imaging Asia Vol.7 No.3
Clinical manifestations of constrictive and restrictive physiology often overlap, posing a challenge in choosing among treatment options. This dilemma is increased when significant pleural effusion contributes to the symptomatology. We present a case of chronic constrictive pericarditis as a sequela of tubercular pericarditis and causing right heart failure and pleural effusion in subsequent presentation.
Hyaluronic Acid–Ceramide-based Liposomes for Targeted Gene Delivery to CD44-Positive Cancer Cells
Sudipta Mallick,박정현,조현종,김대덕,최준식 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.3
Hyaluronic acid–ceramide (HACE)-modified liposomes were designed using 1,2-dioleoyl-sn-glycero-3-phoshphoethanolamine (DOPE) and 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) for targeted delivery of therapeutic genes to the CD44 receptor-overexpressing cancer cells. Liposomes were prepared with different molar ratios of HACE; the most efficient formulation was tested for further in vitro experiments. The size and zeta potential of HACE-based liposomes were characterized by a Zetasizer. Lipoplex was then prepared at different nitrogen/phosphate (N/P) ratios; the gel retardation test showed strong DNA-binding affinity of liposomes for targeted gene delivery. Cytotoxicity of liposomes was evaluated by colorimetric assay (WST assay) for different cell lines such as MDA-MB-231 and NIH3T3 cells. HACE liposomes showed negligible cytotoxicity both in MDA-MB-231 and NIH3T3 cells that endow them for further therapeutic studies. We then examined the transfection efficiency of liposomes using luciferase reporter plasmid DNA. We found transfection efficiency of HACE-based liposomes was remarkably higher in case of MDA-MB-231 cells as compared to NIH3T3 cells. This result was indicative for higher receptor-binding endocytosis uptake of HACE liposomes and subsequent transfection in CD44 receptor-positive cell lines. Our findings have shown interesting prospective for tumor-targeted delivery of therapeutic gene in CD44 receptor-positive cells with less cytotoxic effects.
Sudipta Chowdhury,Mohammad Marufuzzaman,Huseyin Tunc,Linkan Bian,William Bullington 한국CDE학회 2019 Journal of computational design and engineering Vol.6 No.3
This study presents a novel Ant Colony Optimization (ACO) framework to solve a dynamic traveling sales-man problem. To maintain diversity via transferring knowledge to the pheromone trails from previous environments, Adaptive Large Neighborhood Search (ALNS) based immigrant schemes have been devel-oped and compared with existing ACO-based immigrant schemes available in the literature. Numerical results indicate that the proposed immigrant schemes can handle dynamic environments efficiently com-pared to other immigrant-based ACOs. Finally, a real life case study for wildlife surveillance (specifically, deer) by drones has been developed and solved using the proposed algorithm. Results indicate that the drone service capabilities can be significantly impacted when the dynamicity of deer are taken into consideration.
Sudipta Goswami,Jagesh Kumar Ranjan 한국섬유공학회 2020 Fibers and polymers Vol.21 No.5
Interpenetrating polymer networks of vinyl ester (VE) resin and polyurethane (PU) was synthesized using blendratio of 93:7 (w/w). Bio-composites with Kenaf fibre reinforcement in VE/PU IPN matrix were prepared by hand-lay-up. Similar bio-composites were prepared with vinyl silane treated kenaf (SKF) and fibre content was varied by 15, 25, 35 and40 wt. % of the matrix in both the cases. Hybrid composites consisting of both silica nano filler (2 wt. %) and 35 % of kenaffibre together in VE/PU IPN (93:7 w/w) matrix were prepared. Analysis of these composites showed that 93VESi35SKFhybrid composite possessed improved tensile strength, Young’s modulus and Interlaminar Shear Strength by 3.12, 0.24 %and 4.13 % respectively in comparison to that of the 93VESi35KF. Thus silane treatment of natural fibre caused better fibre/matrix adhesion in these hybrid composites. Also the same properties increased by 9.22, 18.53 and 22.07 % respectively for93VESi35SKF in comparison to that of 93VE35KF showing that the hybrid composite was stronger than the correspondingbio-composite without nanofiller.
Sudipta Dey,Somnath Mukherjee 대한토목학회 2013 KSCE Journal of Civil Engineering Vol.17 No.7
Phenol and resorcinol compounds are found to co-exist in real-life wastewater, especially in petrochemical, coking and coke-oven wastewater. An indigenous mixed microbial culture isolated from effluent treatment plant of a coke oven industry has been employed to investigate for its biodegradation capacity of bi-solute mixture of phenol and resorcinol under aerobic batch reactor operation. A 22 full factorial design with the two substrates at two different levels of initial concentration ranges (high and low) was explored to design the biodegradation experiments. The effect of individual substrate concentrations and their interaction on rate of phenolics biodegradation were also determined. The phenol and resorcinol as substrates were completely utilized after 22 hrs when the solutes are present at low concentrations of 100 mg/L each. But the culture has taken total 58 hrs to biodegrade completely higher initial concentrations i.e., 400 mg/L of each substrate. This study also observed that both specific growth rate of the culture and the specific substrate degradation rate have descended to lower value in presence of phenol and resorcinol as dual substrate in the solution compared to their presence as single substrate, showing the interaction and inhibition by each substrate. Sum kinetic model was used to describe the variation in the specific substrate degradation rates by the mixed culture. From the interaction parameters obtained from this model, it has been observed that resorcinol inhibits specific substrate degradation rate to a higher extent than inhibition caused by phenol (I Resorcinol, Phenol = 0.5, I Phenol, Resorcinol = 0.1, RMSE = 0.04361)
Brain Tumor Classification using Adaptive Neuro-Fuzzy Inference System from MRI
Sudipta Roy,Shayak Sadhu,Samir Kumar Bandyopadhyay,Debnath Bhattacharyya,Tai-Hoon Kim 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.3
Detecting correct type of brain tumor is a crucial task for diagnosis and curing the tumor. Identifying the correct type of brain tumor can provide a fast and effective way to plan the diagnosis of tumor. The proposed system provides a fast and efficient way to identify the correct type of tumor and classify it to the respective class label. Our proposed system is comprised of multiple stages. In the first stage MRI image is taken as input and is normalized. The second stage includes extraction of feature vectors from the image which results in reducing redundancy of data and will serve as the input to the classifier. The classifier takes each tuple of feature extracted vector to produce classified output. Performance analysis shows that our proposed methodology has performed very efficiently and accurately. In our work we demonstrate the application of Fuzzy Inference System (FIS) based classifier known as Adaptive Neuro Fuzzy Inference System (ANFIS) to successfully classify the input tuples in comparison to other two selected classifiers namely: Artificial Neural Network with Backpropagation Learning Model and K-Nearest Neighbors.