Faculty Publications
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Item Solid Phase PEGylation of Uricase(Elsevier Ltd, 2017) Nanda, P.; JagadeeshBabu, P.E.Uricase is used as a therapeutic enzyme to treat gout and hyperuricemia which also finds application in cancer chemotherapy. Site-specific PEGylation of uricase using methoxy polyethylene glycol maleimide (mPEG-mal) through thiol PEGylation reaction is an effective way to overcome the demerit of its short plasma half-life in blood as well as for the enhancement of its therapeutic potential. However, conventional solution-phase PEGylation for the synthesis of conjugates leads to lower yields of the desired PEGylated product and thus falls short of commercial attraction. In order to preserve the bioactivity of PEGylated product, selectivity, and extent of covalent conjugation, a methodology for on-column/solid phase PEGylation of uricase enzyme using size-exclusion reaction chromatography (SERC) has been attempted. Sephadex G-100 was used as a chromatographic solid media, wherein synthesis of mono and di-PEGylated uricase molecules was observed which were efficiently separated from their non-PEGylated counterparts. © 2017 Elsevier Ltd.Item Separation Dimension of Graphs and Hypergraphs(Springer New York LLC barbara.b.bertram@gsk.com, 2016) Basavaraju, M.; Sunil Chandran, L.S.; Golumbic, M.C.; Mathew, R.; Rajendraprasad, D.Separation dimension of a hypergraph H, denoted by ?( H) , is the smallest natural number k so that the vertices of H can be embedded in Rk such that any two disjoint edges of H can be separated by a hyperplane normal to one of the axes. We show that the separation dimension of a hypergraph H is equal to the boxicity of the line graph of H. This connection helps us in borrowing results and techniques from the extensive literature on boxicity to study the concept of separation dimension. In this paper, we study the separation dimension of hypergraphs and graphs. © 2015, Springer Science+Business Media New York.Item Novel mixed matrix membranes incorporated with dual-nanofillers for enhanced oil-water separation(Elsevier B.V., 2017) Lai, G.S.; Yusob, M.H.M.; Lau, W.J.; Jamshidi Gohari, R.J.; Emadzadeh, D.; A.F., A.F.; Goh, P.S.; Isloor, A.M.; Arzhandi, M.R.-D.In this work, a new type of mixed matrix membranes (MMMs) composed of dual-nanofillers at different ratios of hydrous manganese oxide (HMO) and titanium dioxide (TiO2) was fabricated with the objective of improving properties of polyethersulfone (PSF)-based membrane for oil-water separation process. The morphology and surface chemistry of the resultant MMMs were characterized by several analytical instruments, i.e., SEM-EDX, contact angle goniometer and FTIR spectrometer prior to separation performance evaluation using oily solution composed of 500 or 2000 ppm. The results showed that the membrane surface hydrophilicity was greatly improved upon addition of hydrophilic nanofillers and HMO in particular showed greater extent of hydrophilicity enhancement owing to the fact that it is associated with higher amount of [sbnd]OH functional groups compared to TiO2. The improved surface hydrophilicity coupled with formation of long finger-like voids in the membrane structure are the main factors leading to greater water flux of MMMs in comparison to control PES membrane. MMM2 (membrane made of HMO:TiO2ratio of 0.75:0.25) and MMM4 (HMO:TiO2ratio of 0.25:0.75) in particular were the best two performing nanofillers-incorporated membranes owing to their good balance between water flux and oil removal rate. They achieved 31.73% and 26.41% higher water flux than that of the control membrane without sacrificing oil removal rate. Most importantly, these nanofillers-incorporated membranes showed significantly lower degree of flux decline as a result of improved surface resistance against oil fouling and are of potential for long-term operation with extended lifespan. © 2017 Elsevier B.V.Item Separation dimension and sparsity(Wiley-Liss Inc. info@wiley.com, 2018) Alon, N.; Basavaraju, M.; Sunil Chandran, L.S.; Mathew, R.; Rajendraprasad, D.The separation dimension ???(G) of a hypergraph G is the smallest natural number k for which the vertices of G can be embedded in Rk so that any pair of disjoint edges in G can be separated by a hyperplane normal to one of the axes. Equivalently, it is the cardinality of a smallest family F of total orders of V(G), such that for any two disjoint edges of G, there exists at least one total order in F in which all the vertices in one edge precede those in the other. Separation dimension is a monotone parameter; adding more edges cannot reduce the separation dimension of a hypergraph. In this article, we discuss the influence of separation dimension and edge-density of a graph on one another. On one hand, we show that the maximum separation dimension of a k-degenerate graph on n vertices is O(k lg lg n) and that there exists a family of 2-degenerate graphs with separation dimension ?(lg lg n). On the other hand, we show that graphs with bounded separation dimension cannot be very dense. Quantitatively, we prove that n-vertex graphs with separation dimension s have at most 3(4 lg n)s?2 edges. We do not believe that this bound is optimal and give a question and a remark on the optimal bound. © 2018 Wiley Periodicals, Inc.Item Automated Method for Retinal Artery/Vein Separation via Graph Search Metaheuristic Approach(Institute of Electrical and Electronics Engineers Inc., 2019) Srinidhi, C.L.; Aparna., P.; Rajan, J.Separation of the vascular tree into arteries and veins is a fundamental prerequisite in the automatic diagnosis of retinal biomarkers associated with systemic and neurodegenerative diseases. In this paper, we present a novel graph search metaheuristic approach for automatic separation of arteries/veins (A/V) from color fundus images. Our method exploits local information to disentangle the complex vascular tree into multiple subtrees, and global information to label these vessel subtrees into arteries and veins. Given a binary vessel map, a graph representation of the vascular network is constructed representing the topological and spatial connectivity of the vascular structures. Based on the anatomical uniqueness at vessel crossing and branching points, the vascular tree is split into multiple subtrees containing arteries and veins. Finally, the identified vessel subtrees are labeled with A/V based on a set of hand-crafted features trained with random forest classifier. The proposed method has been tested on four different publicly available retinal datasets with an average accuracy of 94.7%, 93.2%, 96.8%, and 90.2% across AV-DRIVE, CT-DRIVE, INSPIRE-AVR, and WIDE datasets, respectively. These results demonstrate the superiority of our proposed approach in outperforming the state-of-The-Art methods for A/V separation. © 1992-2012 IEEE.Item Synthesis and characterisation of an ultra-light, hydrophobic and flame-retardant robust lignin-carbon foam for oil-water separation(Elsevier Ltd, 2021) Vannarath, A.; Thalla, A.K.The lignin extracted from Arecanut husk (Areca catechu) was used as an additive in lignin-carbon foam synthesis to enhance oil uptake in oil-water separation. The lignin yield from the arecanut husk increased as the husk fibre size reduced. The extracted lignin and lignin-carbon foam were characterised for morphology, structural, compositional and thermal degradation properties. The synthesised lignin-carbon foam appears to be ultralight (density = 0.0294 g/cm3), excellent hydrophobic (water contact angle was 124°), mesoporous (3D cell-like structure), fire-retardant and thermally stable. The foam showed an excellent sorption capacity for different oils, and the highest sorption was observed for diesel oil (7842.71 mg/g). The optimisation of contact time (30 min), lignin-carbon foam dosage (0.5 g), and initial oil concentration (30 g/L) were done for the diesel oil sorption. The isotherm study and kinetic model evaluation were done for the diesel adsorption on the lignin-carbon foam. The Temkin model was found the best fit for the adsorption isotherm. The adsorption kinetics of the lignin-carbon foam for diesel oil was best described by pseudo-second-order kinetics. The thermodynamic parameters showed that the adsorption was endothermic and spontaneous (standard enthalpy change, ?H° = +4926.46 J/mol and standard entropy change, ?S° = 25.249 J/mol/K). The proposed mechanism depicts that the adsorption primarily influenced hydrogen bonding (H-bonding) and n-? interactions. The enduring adsorption of oil into the lignin-carbon foam within few seconds shows the material oleophilicity and confirms their application prospect in oil spill cleanup. © 2021Item Application of fractional factorial design for evaluating the separation performance of the screening machine(Taylor and Francis Ltd., 2022) Shanmugam, B.K.; Vardhan, H.; Raj, M.G.; Kaza, M.; Sah, R.; Hanumanthappa, H.Implementing the planned execution of experiments will optimize the resources and time of a newly developed process or equipment. In the present work, the screening machine is newly developed equipment designed for the separation of coal. The present work was carried out to evaluate the performance of separation efficiency of the screening machine using generalized and forward selection fractional factorial experimental design. Further, the present work will also determine the significance of each operational variable, such as moisture content, angle, and frequency, for increasing separation efficiency. A cube plot was developed from the experimental design, which shows the highest and lowest condition of separation efficiency for each level of the operational variables. Further, a Pareto chart was developed to evaluate the significant operational variable for the screening machine. The results of the generalized method and forward selection method of fractional design show that the moisture content was the most significant operational variable, followed by angle and frequency. The results also show that the screen blinding of a screening machine plays an important role in reducing the separation efficiency of a screening machine. © 2021 Taylor & Francis Group, LLC.Item Comparison of the predictive model performance of Taguchi’s L27 and Box Behnken design optimization method for separating coal in vibrating screen(Taylor and Francis Ltd., 2023) Shanmugam, B.K.; Vardhan, H.; Raj, M.G.; Kaza, M.; Sah, R.; Hanumanthappa, H.The present research work evaluates the influential process parameters such as moisture content, angle, and frequency for separating coal in the vibrating screen. The design of the experiment for three factors with three levels was obtained using Taguchi’s and Response surface methodology’s (RSM) method. Taguchi’s L27 and RSM Box–Behnken design (BBD) method was used to conduct the separation experiment on a vibrating screen. The main effect plot of Taguchi’s L27 and BBD method was used to evaluate the optimized condition for obtaining the highest separation efficiency of the vibrating screen. The optimized condition obtained was lower moisture content (4%), lower angle (1 degree in upward slope), and medium frequency (9 Hz). The interaction plot of Taguchi’s L27 and BBD method was used to evaluate the interaction between the process parameters. From the interaction plot and ANOVA results, it was clear that the moisture content is the most significant parameter compared with the angle and frequency parameter for separating coal in a vibrating screen. From the prediction results, it was also clear the regression coefficient of Taguchi’s L27 was higher when compared with the RSM BBD method. This shows that Taguchi’s L27 is the most suitable optimization method compared with RSM. © 2022 Taylor & Francis Group, LLC.Item Comparison of the prediction performance of separating coal in separation equipment using machine learning based cubic regression modelling and cascade neural network modelling(Taylor and Francis Ltd., 2023) Shanmugam, B.K.; Vardhan, H.; Raj, M.G.; Kaza, M.; Sah, R.; Hanumanthappa, H.The availability of low-grade coal with a high amount of ash has urged the improvisation of separation equipment with minimal or no water utilization. The present work addresses the study on the separation equipment performance with different moisture coal. The experimental results were obtained in terms of separation efficiency. After obtaining the experimental results, the mathematical modeling results were obtained using different techniques. The cubic regression and cascade neural network models were considered to study the mathematical correlation with experimental results. The R-squared value of each mathematical modeling technique was correlated with the model fitting to check the model’s validity. The results clearly showed that the cubic model fitting for the experimental condition had provided an excellent R-squared value varying from 92% to 99%. The cascade model fitting for the experimental condition has provided a higher R-squared value, i.e., more than 99%. Results show that for all experimental conditions, the cascade model fitting of the neural network technique provides the significant mathematical modeling technique suitable for predicting the separation equipment’s performance compared to the cubic model of the regression technique. © 2022 Taylor & Francis Group, LLC.